Newmarket July Meeting: A Ten Year View

7 July 2025/in Dave Renham/by Dave Renham

Newmarket July Meeting – a look at the past 10 years

Later this week racing fans will enjoy the three-day Newmarket July Meeting, writes Dave Renham. Expect top quality action headlined by two Group 1s, the July Cup and the Falmouth Stakes, as well as four Group 2s. There will also be several decent handicaps to get stuck into. In this article I am going to look at stats for the most recent ten meetings going back to 2015. Profit / loss has been calculated to £1 level stakes using Betfair Starting Price (BSP), with 2% commission taken out of any winning selections.

Contents

Newmarket July Meeting: Market Rank (Exchange)

I would like to start by examining the betting market, more specifically the market rank of Betfair. Here are the splits:

It seems the sweet spot over the past decade was horses ranked third to fifth in betting preference. Favourites by contrast suffered fairly significant losses equating to more than 17 pence in the £. Splitting the favourite data into handicaps versus non-handicaps, it was handicaps that offered better results, albeit losses were still over 11p in the £. Losses in non-handicaps were over 23p in the £ for the jollies. Eye-watering stuff!

If we look at the Betfair A/E indices for Market Rank, we can see excellent correlation with the earlier table:

Horses ranked third to fifth in the betting have offered excellent value over the past ten years. It will be interesting to see if this pattern continues this year.

Newmarket July Meeting: Price movement

Now I want to look at price movement data comparing Early Morning Odds to final Starting Prices. I am going to share the win strike rates for horses that lengthened in price over the day, stayed the same price, and shortened in price.

Horses that shortened in price were the most successful, as is the norm, but the differential between ‘shorteners’ and those that drifted in price is huge. Horses that were backed over the day won more than 2.5 times more often than those that drifted. If we now look at the profit / loss for the three groups, based on their final BSP we see the following:

It seems that following the money would have been a good strategy over the past ten meetings. Despite the prices shortening, 'line trackers' still would have seen a 10p in the £ return to BSP on horses that were shorter prices at the off than they were in the morning.

There are two trainers in particular that were worth noting when the money was down: Andrew Balding and Ralph Beckett. Balding was 7 from 31 (SR 22.6%) with shorteners, just 2 from 28 (SR 7.1%) with drifters. Beckett meanwhile was 7 from 29 (SR 24.1%) with shorteners and just 1 from 21 (SR 4.8%) with drifters.

Newmarket July Meeting: Age in 3yo+ & 4yo+ races

Let me next look at the performance of different aged runners in races open to 3yos and over / 4yos and over. It should be noted that the vast majority (87% of them) were 3yo+ races. Here are the age splits:

This is illuminating. Three- and four-year olds have clearly outperformed their elders both from a win rate perspective as well as a profit / loss one. It looks like we can pretty much write off any horse aged seven or older based on these figures.

The contrast between younger and older has been strongest in non-handicaps where horses aged five or older have won just three times from 97 attempts (SR 3.1%) for losses of over 80 pence in the £. In handicaps three-year-olds fared extremely well as the graph for win strike rate below shows:

I would think the starting point for any all-age handicap would be the 3yos based on this data. It should be noted, too, that 3yos that shortened in price from Early Odds to SP in these races won over 24% for a healthy 18% ROI%.

Newmarket July Meeting : Recent form

Moving on to ‘last time out’ factors, let's start with recent form and the position the horse finished on their most recent start. Here is the breakdown:

It is unusual to see similar win rates for horses finishing first, second, third or fourth last time out (LTO). The LTO winners’ group made a BSP profit, but those figures are skewed somewhat by three decent priced winners – BSP 66.34, 50.0 and 40.0. All in all, I would not be paying too much heed to LTO performance as in the past, for this meeting at least, it has not been much of a guide.

Newmarket July Meeting: Course LTO

Another LTO factor is the course at which the horse ran last time. Below are the LTO courses that have provided at least 50 of the Newmarket July meeting runners:

A good chunk of the runners raced at Ascot last time, many of which were racing at the Royal meeting a few weeks previously. There were also a significant number of horses that raced at Newmarket LTO and these had the best record in terms of strike rate as well as delivering a fair profit. Sandown and York were the other two LTO courses to turn a profit here, and York’s figures look particularly solid. LTO York runners that started in the top three in the betting at the Newmarket July festival secured a 31% strike rate and returns of over 100p in the £. In contrast, the Newcastle and Windsor figures have been poor, and both have commensurately disappointing place percentages, too.

Newmarket July Meeting: Course form

Onto course form now and looking at the performance of past course winners compared to those that had not won at the track. To make this a fair comparison I will compare only horses that had already run at the track: clearly horses that were yet to run there could not have previously won! I am going to compare the win strike rates and the win & placed (Each Way) strike rates first:

It seems therefore that a previous course win is preferable both from a win and a place perspective. This is also reflected in the profit/loss and return columns in terms of win bets:

In terms of betting on the Place market on Betfair, there has been a big discrepancy there as well. Previous course winners produced a £38.41 profit to £1 level stakes; non-course winners lost £52.24.

With regards horses that raced at the course previously and had been placed before (includes winners of course), they too have a strong edge as these stats show:

Taking all these stats into account a previous win or placed effort at the track has been a definite positive at this meeting.

Newmarket July Meeting: Trainers

The final area I want to look at is trainers: which handlers have excelled at this meeting and which ones have found it a struggle? Only trainers with 30 runners or more are shown. As far as Charlie Johnston is concerned, I have combined his record with his father’s, Mark. The table is ordered by return on investment at Betfair Starting Price (BSP ROI).

Several trainers were in profit through the decade although Ralph Beckett, Michael Bell, Karl Burke and the Johnston stable's performance figures were boosted by a few bigger priced winners dropping in. Charlie Appleby, Andrew Balding, Richard Hannon, Aidan O’Brien and Saeed bin Suroor have more solid looking overall profiles and all five showed good profits with horses in the short to mid-price range.

There are a couple of extra stats worthy of note. Firstly, when William Buick rides for Appleby the strike rate has been a smidge under 30% for a 49p in the £ return. Secondly, Aidan O’Brien should be noted when any of his runners pivot from Royal Ascot. This cohort won 27% of the time for a 63p in the £ return.

The records of William Haggas, Charlie Hills, Hugo Palmer and Kevin Ryan have been poor, although Haggas has had plenty of near misses. Palmer and Hills have a poor record in terms of placed runners as well, and they may be two trainers worth avoiding at the fixture.

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Newmarket July Meeting: Key Positives

The key positives are as follows:

Horses third to fifth in the betting market
Horses that shorten in price from Early Morning Odds to SP
3yos in 3yo+ handicaps
Ran at Newmarket or York LTO
Previous course form (both win and placed)
Trainers - Appleby, Balding, Hannon, O’Brien and bin Suroor

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I hope this piece has provided a few pointers that will prove useful over the three days of Newmarket's always excellent July meeting. Good luck to those punting, and don’t forget to use the Tix software if playing the Jackpot, Placepot, Scoop 6 or Quadpot.

- DR

How to Use Tix for Multi-Race (Placepot) Bets

Using Tix for Jackpots, Placepots, Quadpots & the Scoop 6, primarily focusing on Placepots

Geegeez readers should by now be aware of the online software called Tix, which Matt built in conjunction with the developer who built much of the coding for the original geegeez.co.uk racecards and form tools, writes Dave Renham. The Tix software is designed to be used for tote multi-race pool bets such as the Jackpot, Placepot, Quadpot and Scoop 6. It enables punters to produce more sophisticated and strategic permutations than the bog-standard perm approaches most punters use.

Contents

Tote Bets: A Quick Intro

Before discussing the software, it should be noted that the Tote take a percentage out of any final pool, the amount depending on the bet. Below is a table showing the percentage take-outs for the main pool bets:

Pool bet	Percentage taken out
Jackpot	29%
Placepot	27%
Quadpot	26%
Scoop 6	30%

As we can see they are all in the same ballpark. If we consider the Placepot, therefore, if 27% is taken out that leaves 73% of the original pool being shared between winners.

To help understand the maths, here is an example. For a final total of £100,000 bet into a particular Placepot pool where there was £200 remaining at the end of the six races, the dividend would be worked out thus:

£100,000 x 73% = £73,000

£73,000 divided by 200 = £365

£365 is the dividend is to a £1 stake.

The lure of Placepots and Jackpots is the chance of a big payout for relatively small outlays. Personally, I have never regularly played the Jackpot but play plenty of Placepots. I’ve been fortunate enough to have enjoyed some reasonable wins, and one very big win, but of course there have been many occasions when I have lost all of my stake. As far as this article is concerned, I am going to focus on using Tix for Placepots, because it is the most commonly played of the tote multi-race bets.

Playing Placepots the Traditional Way

Let's first look at how we could play these pool bets without the aid of Tix.

One line 'Hail Mary'

The first method is to simply pick one horse in each race. In a Placepot, there are six legs and so that would be six horses. In order to win a share of the Placepot all six must either win or place. This would be the case even if we pick six favourites. For those wanting to put the favourite in as the only selection in each of the six races, this is possible because there is a Placepot option to back the unnamed favourite.

Tthere are plenty of races where the market is quite tight at the top and we would be guessing which horse is sent off favourite, so for ‘favourite’ fans this is a useful option. However, the chance of all six favourites winning or placing is surprisingly rare. Indeed, looking at the 177 flat race meetings held in the UK in April and May of this year only 13 times did six favourites win or place in each of the first six races on the card.

However, that did not mean there would have been 13 theoretical winning Placepots for favourite only backers. This is because three of these 13 did not count due to a situation where a joint favourite won or placed, but the other joint favourite did not. When this happens there can only be one horse deemed to be favourite so the horse with the lowest racecard number becomes the favourite for pool bet purposes. Hence, if we had gone down the unnamed favourite Placepot route in April and May we would have had 177 Placepots bets of which 10 won.

The problem with all favourites placing is that the dividend tends to be very low when this happens, and that was the case with all ten dividends as the table below shows:

Date	Course	Dividend to £1 stake
7^th April 2025	Kempton	£6.20
12^th April 2025	Brighton	£12.40
12^th April 2025	Thirsk	£8.00
1^st May 2025	Redcar	£11.50
3^rd May 2025	Goodwood	£9.90
5^th May 2025	Windsor	£10.50
9^th May 2025	Nottingham	£7.30
21^st May 2025	Chepstow	£13.20
23^rd May 2025	Goodwood	£5.90
26^th May 2025	Windsor	£8.00

If we had placed let’s say a £2 bet on each of the 177 Placepots our outlay would have been £354. Our returns would have been £185.80 showing a LOSS of £168.20. Ouch!

Favourites obviously command the most amount of money wagered in Placepots which is why, when all six win or place, the dividends are so low. Interestingly, there were two meetings in April and May where no favourites placed in any of the six races – the dividends for these meetings were somewhat different.

Date	Course	Dividend to £1 stake
19^th April 2025	Musselburgh	£1954.50
31^st May 2025	Lingfield	£4022

The '2x2'

For seasoned Placepot players selecting a single horse in each race is not a credible strategy. In the period discussed we have seen that putting the favourite as the only selection in each race secured a winning Placepot less than 6% of the time, and delivered significant losses.

An alternative and more popular approach is to choose two horses in each race giving players more coverage. We call this a permutation, or perm. If we choose two horses per race rather than one, the number of bets or lines goes up drastically from one to 64 because we multiply the number of selections per race to get the total number of selections.

1 x 1 x 1 x 1 x 1 x 1 = 1 while 2 x 2 x 2 x 2 x 2 x 2 = 64

Take three horses per race and we are looking at 729 bets or lines.

Obviously, the chances of winning part of the pot increase but the more bets/lines we have the more we are staking, which will have an impact on any final returns.

Variable perms

To try and reduce the number of perms, some Placepot players vary the number of horses chosen for each race. Hence, they may have a couple of races where they choose just one horse – a so called ‘banker’; perhaps they have three horses in two of the other races, and five in each of the final two races.

In this scenario the number of bets or lines would be calculated 1 x 1 x 3 x 3 x 5 x 5 which equals 225 bets. This idea covers 18 horses in total (the same as the three horses in every race perm) but cuts the number of bets/lines down considerably.

Thus, varying the number of horses chosen per race is the most sensible method discussed to date; but it is time to talk Tix and a more sophisticated approach to adjusting the Placepot perms.

Introducing Tix

The Tix software allows us to use what is known as the ‘ABCX’ approach. This approach essentially allows players to group horses by order of confidence / perceived chance. In terms of a Placepot the thinking would be along these sorts of lines (or at least this is the way I think!) -

A Horses – horses that I believe are genuine contenders to win or place; or horses that I perceive to be overpriced within the mid-range of prices such as a 10/1 shot that I think ought to be 5/1, or a 12/1 shot that is 6/1 on my reading of the race.

B Horses – the next best options that we can make a case for especially if one or more of the A contenders underperform.

C Horses – horses that are unlikely to win but have some chance of placing. An example may be a horse overpriced at 33/1 we perceive should half that price at least. Or a less fancied horse well drawn over a course and distance that has a strong bias.

X Horses – horses that are excluded from calculations as their win or place chance seems extremely unlikely or I feel they are significantly over-factored in the market.

For Placepots my preferred approach is to have more A’s than B’s and maybe one or two C’s. However, for bigger meetings such as Royal Ascot, I tend to load up on A’s and have more C’s than B’s. I am sure others will have alternative approaches that may well be better than mine. Hopefully the more I use the software the more I can finesse my methods.

In terms of the Tix software the A horses will occur in more bets/lines than the B’s that in turn occur in more bets/lines than the C’s. The table below shows all the possible combinations or perms for each individual Placepot ticket – I have colour coded them to help make it clearer. A rated selections are in red, B are in black and C are in green.

This way of combining the horses is far more efficient and a lot cheaper! The way Tix is designed is that we can have a maximum of 28 individual tickets and this only occurs if we pick at least one horse in each of A, B and C positions in every race - as per the image above.

Tix Selection Flexibility

Keeping to the ‘three horses in a race scenario’, here are total number of bets/lines based on the Tix options, assuming we keep to the same combination for all six races. It includes the two I have already shared:

Combos	All 3 on A	2 on A, 1 on B	2 on A, 1 on C	1A, 1B, 1C	1 on A, 2 on B	1 on A, 2 on C
Total Bets	729	496	256	28	73	13

The table shows the flexibility of the Tix software in terms of being able to offer various ‘number of bet’ scenarios, and remember, these example numbers are based on choosing the same A, B and/or C combination for all six races. Assuming we wanted to put three horses into each race we of course could choose a different three-way combination for each race such as:

Race no.	Column A (no. of selections)	Column B (no. of selections)	Column C (no. of selections)	Total no. of horses in race
1	2	1	0	3
2	1	1	1	3
3	1	2	0	3
4	3	0	0	3
5	1	0	2	3
6	2	0	1	3

This particular Tix construction of three horses per race would equate to 138 lines. It would take several pages to list all possible Tix bet constructions of three horses in each of the six races, so I’ll spare readers that! On the Tix site, our ticket with this type of perm/construction would potentially look something like this:

To be clear, the green column is for A picks, the yellow is for B picks, and C picks are in the right hand sandy coloured column. And these numbers in the specific columns would give us the following ten tickets:

As we can see, for this example there are ten specific groupings (tickets), and we would need at least one of those of ten groupings to have a win or placed horse in each of the six races to get a return. Of course, we may achieve a return that is less than our original stake, so six ‘win or placers’ on one of the tickets does not guarantee a profit.

If all eighteen horses manage to place then we probably would be dreaming but in that unlikely scenario these ten specific groupings/tickets would combine to have all 138 bets/lines as winning ones.

Tix Staking Flexibility

So, one of the brilliant parts about using Tix is this selection flexibility. A further feature in terms of flexibility is that we can adjust our stakes in terms of the four main groupings. This is the default position with the same stakes on each:

However, anyone who has seen Matt post his Tix selections on the site (like he did brilliantly at Royal Ascot 2025, I might say) will know he has a favoured strategy thus:

- All A's: 4x unit stake

- Five A's with one B pick: 3x unit stake

- Four A's with two B picks: 2x unit stake

- Five A's with one C pick: 1x unit stake

Using the ‘Matt Method’ we would simply tick the relevant boxes thus:

Using the example of my ten tickets shared above, this means ticket 1 (all A's) has a 4x amplification, tickets 2 to 4 (any 5 A's with 1 B) are 3x unit stake, tickets 5 to 7 (any 4 A's with 2 B's) are 2x normal stakes, and tickets 8 to 10 (any 5 A's with 1 C) are 1x stakes.

Of course, this stake amplification on certain tickets will increase the overall outlay but we're pressing up our strongest opinions whilst mixing in some 'big dividend' prospects.

In this specific example based on an original 1p per bet/line, and having no increase in stakes (so betting all lines with the same stake of 1p), it would cost £1.38.

Using the 4-3-2-1 Matt method would increase stakes to £3.00. The reasoning behind Matt’s staking plan is logical. The A horses are more likely to win or place than the Bs, who in turn should outperform the Cs. Hence the all-A column should have the highest stake, the 5A 1B column should come next and so on.

This staking method is one option, possibly the best one; obviously there are plenty of others that could be used. Also, at this point, it should be noted there is another way to adjust our stakes. We can adjust individual tickets by clicking on the ‘stake’ box at the bottom of each ticket and changing the default stake.

For those readers who have yet to use Tix, how to use the software is specific to each individual. Some I’m sure will not adjust stakes, some will. Some will load up with A’s, some may spread their horses more evenly. However, it is important to appreciate that each race meeting is different, and we are likely to play a Placepot at Carlisle with very few runners on the card differently to one at Royal Ascot where field sizes are much bigger and very competitive.

Wider Coverage

Thinking of the bigger meetings like Royal Ascot with their huge and competitive fields, it is likely that there will be an increase in the number of horses that will be used in our placepots. Earlier I looked at an imaginary three horses per race scenario sharing how placing them in different columns affected the total number of lines. Now let's look at the same idea using four horses per race (24 horses in total). Again, I have assumed that we have split the horses into the same columns for each race. Obviously placing four horses in the exact same columns for each of the six races is something that in practice we would almost definitely not do, but my reasoning is two-fold. Firstly, it is easy for me to calculate and share the total number of bets for each grouping. And secondly it gives us a decent understanding of the ‘number of total bets’ differences we can get using this flexible software:

Combos	All 4 on A	3 on A, 1 on B	3 on A, 1 on C	2 on A, 2 on B	2 on A, 2 on C
Total Bets	4096	3402	2187	1408	448

Combos	2 on A, 1 on B, 1 on C	1 on A, 3 on B	1 on A, 2 on B, 1 on C	1 on A, 1 on B, 2 on C	1 on A, 3 on C
Total Bets	688	154	79	34	19

We can see that if selecting all 24 horses in the A column (four in each race) the number of bets/lines is a massive 4096. However, when we spread them more evenly but keep mostly A’s, such as a 2A, 1B and 1C scenario for each race, this cuts the bets/lines down to 688.

As I mentioned earlier for ease of calculations, I have assumed that each race has the same A, B, C combo or grouping. But, of course, Tix players will play each race according to its make-up. Considerations will be affected by the number of runners, the individual strengths of the runners, the relative prices of those runners, etc. For example, a three-runner race with a 1/12 favourite could see us choose that favourite on A as a stand-alone banker. A three-runner race where all three horses are priced between 13/8 and 2/1 may mean we choose all three in the A column. Only one of them will count in a final Placepot dividend while the other two will be losers and all lines involving those two will ‘die’.

Example Tix Play: Royal Ascot

I now want to share my Tuesday Placepot at Royal Ascot this year and how I played it using Tix. In terms of staking, I didn’t use Matt’s 4-3-2-1 method, I simply kept to the same 1p stakes per ticket.

Leg 1 - Queen Anne Stakes:

This was the race I previewed for Geegeez on the Tuesday and happily my two selections came first and second. The winner, Docklands, returned 14/1 (backed in from 25/1) so that was a good start to the week on an individual punting front. The runner up Rosallion was favourite and pre-race I was tempted to leave him as the stand-alone ‘A’ selection in my Placepot; but the race did have a very competitive look about it. So I played safe taking five selections across two columns. I also split Rosallion and Docklands up putting Docklands on C – silly me as that turned out.

Leg 1 selections

A – numbers 4 and 10

C - numbers 3, 5 and 6

Horses that won/placed: one A, and one C

Leg 2 - Coventry Stakes:

These 2yo races with loads of runners and little form are the ones I fear most in Placepots with only three places available (and so it proved here). I went big trying to cover as many bases as possible with four A’s and four C’s:

A – numbers 1, 2, 13 and 20

C - numbers 8, 9, 11 and 17

Horses that won/placed: one C

This was frustrating from the point of view that two of my A selections finished fourth and fifth. On the flip side, I was still in the pot with one of my C’s placing, and two of the placers were 66/1 and 80/1 meaning very few tickets had those runners on them.

Having played just A’s and C’s I was now needing at least one A horse to win or place in the final four races.

Leg 3 - King Charles III Stakes:

This was another horrible race with 23 runners and only three places up for grabs. My only strong opinion on the race was that American Affair was overpriced and I was happy for that to be one of my A’s. I went four A’s and two C’s. American Affair won.

A – numbers 1, 7, 14 and 16

C - numbers 3 and 12

Horses that won/placed: two A’s

Leg 4 - St James's Palace Stakes:

Although there were only two places available in this seven-runner race, there were four rags and an odds-on fav in Field Of Gold. I had him and Henri Matisse as my A’s. No need for any ‘C’ cover.

A – numbers 1, 3

Horses that won/placed: two A’s

Leg 5 - Ascot Stakes:

There were two at a price I liked here in Nurburgring and Ascending. I decided to split them with Nurburgring on A and Ascending on C. I put one of the well fancied Mullins pair on A and what I hoped was another live outsider on C.

A – numbers 13 and 20

C - numbers 3 and 9

Horses that won/placed: one A, and one C

Ascending beat Nurburgring for a £665 exacta (and no I didn’t have it!). At least I had one A selection that counted so was still in the Placepot game with one to play.

Leg 6 - Wolferton Stakes:

With no eventual non-runners this 16-runner Listed race had only three horses to count in the Placepot. Before the race I was very keen on Sons And Lovers thinking this must finish in the frame. I decided two have two A’s and one C.

A – numbers 9 and 14

C - number 15

Horses that won/placed: one A

Sons And Lovers faded into fifth annoyingly, but fortunately my other A got the job done.

Here's how these selections would have looked in the Tix columns.

Leg	Column A	Column B	Column C
1	4, 10		3, 5, 6
2	1, 2, 13, 20		8, 9, 11, 17
3	1, 7, 14, 16		3, 12
4	1, 3
5	13, 20		3, 9
6	9, 14		15

The numbers in bold are the horses that won or placed, but two of them ended up being redundant (number 5 in leg 1 and number 9 in leg 5). The rest, in red, counted on one of the '5 on A, 1 on C' lines and, because I had two win/placed horses in two of the races, I ended up with four winning lines (1 x 1 x 2 x 2 x 1 x 1).

The Placepot to a £1 stake paid £2767.40 meaning each of my four 1p lines netted £27.67, so the overall return on that winning ticket was £110.68 (£27.67 x 4 winning lines). Taking my stake into account and the 5% bonus the Tote pays on winning Tix tickets (yet another reason for using Tix!), I ended up with a profit on the bet of just over £102.

What if?

One two-word phrase we are all too familiar with is ‘what if?’ - so, just for fun, I am going to play that game now. What if I had put six of my original selections in different columns? More specifically, what if my three ‘placers’ on C had been put on A instead; and three of my ‘losers’ from A had been put on C instead?

To achieve this scenario, I could have swapped horses 4 and 5 over in race one, horses 1 and 9 in race two, and horses 20 and 3 in race five. If I had instead done that, I would have had two places in legs 1, 3, 4 and 5, and one place each in legs 2 and 6. That would have given me 16 winning lines quadrupling the return to over £400. Considering all my selections were in A and C this scenario could have happened. Likewise, if a few of my winning A’s ended up as C's I would have won diddly!

Sticking with the ‘what if?’ line, what if my original ticket had been staked differently using Matt’s 4,3,2,1 method? Well, due to only having one successful 5A 1C combo the same payout of £110.68 would have occurred on that ticket (same 1p stake), but the cost of the overall bet would have increased by £7.68 meaning my overall profit would be slightly down at just over £94. (I appreciate that an extra £7.68 stake would have impacted the real-life pot, but it is such a small amount if I had played the bet this way instead my profit would have been virtually the same, give or take a penny or two).

I also looked at what would have happened if I had put all my C selections as B’s instead, sticking to my original 1p per line staking. This would have added an extra £20 or so to the overall stake but I would have had 12 winning lines so my return would have been around the £300 mark (allowing again for any marginal change in the actual Placepot payout due to the extra £20 of staked funds).

Summary

In this article I feel I have only scratched the surface when it comes to the potential and scope of the Tix software. In the first half of the article, I gave a general overview of how Tix works coupled with the flexibility it has in terms of limiting/varying the number of lines using certain configurations. In the second half I have delved into one of my recent Placepot plays looking at what happened, and what could have happened if I had made some slight alterations via Tix to the make-up of my Placepot.

Before writing this, I was a regular user of Tix. Having spent time researching and writing about it, my appreciation and confidence in Tix has improved even more. I am expecting Tix to help me profit further when tackling Placepots in the future. I might even be tempted into a few Jackpots too...

- DR

Evaluating Jockeys by Percentage of Rivals Beaten, Part 2

25 June 2025/in Dave Renham, Horse Racing Blog/by Dave Renham

This is the second half of an analysis of jockey performance using the Percentage of Rivals Beaten metric, following this one I wrote back at the beginning of June, writes Dave Renham. This time, I will put the same 35 jockeys – those that have had the greatest number of rides on average per year over the past four years - under the microscope.

Contents

Introduction

The data has been taken from UK flat racing (turf + AW) from 2021 to 2024. I have also limited findings to horses the jockeys rode sent off at an Industry Starting Price of 20/1 or less in order to try and eliminate most of the horses that had little or no chance. Also, very big priced winners skew the data.

In the first article I primarily examined the data by using and comparing numbers based on Percentage of Rivals Beaten (PRB). PRB is a calculation based on a horse's finishing position in relation to field size. It makes key distinctions between a horse finishing, say, fourth in seven-horse race (PRB 50%, three rivals beaten, beaten by three rivals) and finishing fourth in a sixteen-horse race (PRB 80%, twelve rivals beaten, beaten by three rivals). We express the PRB as a number between 0 and 1. So, in the examples above, 50% is 0.5 and 80% is 0.8.

For this piece I will be primarily using PRB once more, and I will also be looking at strike rates, profit/loss, returns and A/E indices where appropriate. Using other metrics in conjunction with the PRBs should help to give us a clearer overall picture.

Before I start, I noted last time that certain jockey to jockey comparisons were difficult to evaluate from a PRB perspective due to what I will call ‘jockey price bias’. Essentially, some jockeys have more shorter priced rides than others, and thus conversely, other jockeys have more bigger priced rides. This could potentially skew the PRB, so it is something I am aware of and will address in what follows.

My starting point today is going to field size.

Number of race runners

It should be noted that in races of 2 to 6 runners the average PRB figure for all jockeys riding horses priced 20/1 or shorter stands at 0.55; for 7 to 9 runners, it is 0.57; for 10 to 12 it is 0.59 and for 13+ runner races it is 0.60. Knowing these figures is important to help evaluate each jockeys’ performance within each 'number of runners' grouping. However, based on my findings last time connected with jockey price bias, I also need to consider the average PRB for each jockey to provide better context. Using these two factors in tandem I have used a mathematical formula to establish what are positive PRBs and which are negative for each individual. As in the first article, positives will be highlighted in green, negatives in red:

Let’s look at the very small field size of 2 to 6 runners first. The PRB positives highlight Ghiani, Havlin, Loughnane, Stott and Watson. Let’s see if that translates into an overall profit:

Four of the five made a blind profit with only Rob Havlin in the red. When digging deeper into Jason Watson’s figures it is impressive to note that he made a profit in three of the four years, and his losing year was only 5p in the £. Also, most of Watson's winners were at the shorter priced end of market; if we restrict to runners priced 8/1 or less his record actually improves further to 63 wins from 233 (SR 27.04%) for a profit of £ 50.78 (ROI +21.79).

Meanwhile, Kevin Stott managed four profitable years in a row which is even more eye-catching. Finally for this group of jockeys, geegeez-sponsored rider Marco Ghiani proved himself to be an exceptional judge of pace in these smaller field contests winning 19 of 46 (SR 41.3%) on horses that took the lead early.

Time to look at the jockeys that had a negative PRB. Here are their figures:

All six made a loss although Oisin Murphy and Sean Levey's deficits were modest. Murphy and Danny Muscutt struggled when the runners were bigger prices: restricting to horses priced 10/1 to 20/1 saw Murphy win just once from 40 for losses of 68p in the £, and Muscutt was beaten on all 40 horses he rode in that price range.

There are four other jockeys I would like to highlight when racing in field sizes of 2 to 6 runners and they are Joe Fanning, Paul Mulrennan, Saffie Osborne and David Probert. The ‘graph’ below shows they all had very similar win strike rates (red numbers) and made decent returns (BSP ROI%, black numbers) too:

It should be noted that both Saffie Osborne and Paul Mulrennan were very good from the front in small fields. Both won 35% of the time in such small field races when taking the early lead. It seems likely, then, that both are good judges of pace.

I am not going to go into any depth regarding the 7 to 9 and 10 to 12 runner stats. However, I will take a quick look at the bigger field contests of 13 or more runners in terms of the jockeys who achieved a positive PRB. In bigger fields, being poorly positioned and/or avoiding trouble in running becomes far more relevant. I am guessing that some jockeys are simply better than others at avoiding trouble in running or being poorly positioned.

In terms of those who had positive PRBs the table below shows the splits:

Despite the positive PRBs the results of Callum Shepherd, and particularly Kieran O’Neill, were not good for punters. We cannot really expect all eight to have returned a profit, but the losses for those two were steeper than I expected. On the flip side four made a blind profit, of which three (Jason Hart, Billy Loughnane and Rossa Ryan) produced a very significant profit. The other two made a small loss.

These figures do highlight that PRBs on their own, for this type of research at least, can be flawed. This is the same for any metric – for example a high strike rate does not guarantee profits, a good return on investment can be skewed due to a single big priced winner, and so on. That's why reviewing different metrics where possible is the ideal.

Going back to the table, Rossa Ryan’s figures are outstanding across the board. His returns (ROI%) to BSP by year are shown below:

I believe that one of the reasons for his success in bigger fields has been his ability to win on hold up horses. The win percentage for all jockeys combined in 13+ runner events when they held their mounts up stood at just 7.5% in the study period; Ryan’s was nearly double that on 14.2%. Not surprisingly, his strike rate on hold ups was the highest of all the jockeys. There is definitely something in this because Jason Hart, who also made significant profits in 13+ runner events recorded a strike of 13.6% on hold ups which is the second best of all the jockeys. Being able to manoeuvre your mount successfully through traffic in bigger fields will naturally lead to more wins overall.

Race Class

I want to look at class of race next with the starting focus on the better quality Class 1 and 2 races. I have split their results by price in order to help eliminate any bias. Combining the data for both classes, as some jockeys have limited Class 1 data within certain price bands, helps to get more meaningful datasets. I have chosen four ISP price bands – 7/2 or shorter, 4/1 to 7/1, 15/2 to 10/1, and 11/1 or bigger.

The average figures for all jockeys in the list are shown in blue at the bottom of each column and, because we are dealing with price bands, we have a more level playing field to compare one jockey’s PRB with another. Therefore, I have highlighted any PRB that is at least 3% above the average or at least 3% below the average. The 3% ‘above group’ (positive) are highlighted in green, the 3% ‘below group’ (negative) in red. Any PRB with an asterisk (*) means the dataset was limited so we should probably ignore that number. Here are the findings:

Connor Beasley and Danny Tudhope stand out with three greens and no reds. Those two jockeys seem to have excelled in the better class races, at least according to the PRBs. If we look at their profit and loss figures, we see that Beasley was +£90.43 (ROI +34.8%); while Tudhope was +£60.11 (ROI +9.6%). At the other end of the scale David Allen and Sam James have three reds and no greens. Overall, they lost 17p and 12p in the £ respectively.

What this PRB research is telling us is that some jockeys are almost certainly better than their win rates suggest, they just don’t ride enough horses with good chances. Take Saffie Osborne as an example in Class 1 and 2 races when riding bigger priced runners. Her PRB for the 11/1 to 20/1 price band was an excellent 0.52 qualifying for a ‘green’. However, when you look at her actual overall record with these runners she has won just once in 75 attempts for huge losses if you were backing them all to win. However, if you had backed her horses to place on Betfair she would have made a profit! Her rides within this subset have been outperforming their odds more often than not.

Let's now look at the lower end of the class scale, namely Class 5 and 6 races. I'm using the same price splits and the same colour coding:

There are fewer reds and greens here in total compared to the higher grade of race. James Doyle, David Egan and Rob Havlin have hit two greens, while Joe Fanning's performance looks more modest with three reds.

Courses by Jockey

Finally, in this piece, although there are still plenty of stats to share, I am looking at a selection of the 35 jockeys and comparing their PRB figures at different courses. This should be a very effective use of PRB data as a comparison tool because the comparison is with the individual jockey themselves. I am only using courses where a jockey had enough rides to be meaningful. I am not sharing the course data of all 35 jockeys due to space, but more importantly due to personal time constraints!

David Allan

A look at Allan’s PRBs – the graph below shows the results:

The PRBs range from 0.53 at Haydock and Musselburgh to 0.63 at Pontefract and Southwell. Indeed, Southwell is the course where Allen fared best in terms of profitability having had 25 winners from 97 rides (SR 25.8%) for a BSP profit of £98.13 (ROI +101.16). He did not made a blind profit at Pontefract, but this is probably more down to luck as he had numerous seconds (22 second places compared with 12 wins from 104 rides). Some of those seconds were at fair prices such as BSP 10.63, 11.83, 18.5, 21 and 30. Going back to Haydock and Musselburgh where he had his lowest PRBs, both showed significant losses of 52p and 25p in the £ respectively.

Connor Beasley

A look at Connor Beasley now:

The one course well below the rest in terms of PRBs, Carlisle, has been a poor hunting ground for winners for Beasley, too. He had just had five winners from 68 (SR 7.4%) for losses of £37.33 (ROI -54.9%). The highest PRB came from Southwell, but Beasley made a loss there; although he made an 18% profit if backing place only to Betfair Place SP. Beasley hit a PRB of 0.61 at Beverley, Doncaster and Thirsk, the first two named both producing a blind profit. His record at Doncaster was the best with 16 wins from 82 (SR 19.5%) for a profit of £38.29 (ROI +46.7%).

William Buick

William Buick is the next jockey to share – for his figures I have put them in a table. The five highest have been highlighted in green:

The five greens (Haydock 0.66, Kempton 0.68, Leicester 0.66, Windsor 0.66, Yarmouth 0.69) have produced the following:

Four of the five saw a blind profit with only Kempton failing. However, in the better races (Class 1 and 2) at the Sunbury track he made a small profit thanks to 10 wins from 28 (SR 35.7%) for a profit of £4.65 (ROI +16.6%). There are five more positive course angles for Buick to share which I will share in the following table:

Hollie Doyle

Hollie’s PRBs were perhaps a tad disappointing as I’m a big advocate of hers and of women’s sport generally. Having said that, her overall record speaks for itself and her win percentages across different price bands match up well with other leading jockeys. For her course PRB data I am sharing all the qualifying courses combined with other key metrics. The courses are ordered by PRB highest to lowest:

What this table illustrates, other than Doyle’s individual course PRBs, is that four of the five courses with the highest PRBs produced a blind profit – Bath, Chepstow, Brighton and Kempton. Not only that, the further you go down the list the redder the BSP PL and ROI columns become. The correlation between PRBs and profit/loss and return on investment is more positive than negative.

There are a few extras to share as far as Hollie is concerned - at Bath her record in handicaps has been excellent with 14 wins from 61 (SR 23%) for a profit of £21.58 (ROI +35.4%). Sticking with Bath her 15 winners came from 14 different trainers. Not only that, but her boss Archie Watson is not one of them! At Chepstow she is 8 from 23 for Watson producing a return of 91p in the £, and on favourites at the same track she won 13 of 25 (SR 52%) for a profit of £12.50 (ROI +36.7%).

Joe Fanning

Joe Fanning is still going strong at 54 years old. The PRBs for the courses he rides the most are shown below:

Let’s look at more metrics at the four courses with PRB figures of over 0.60:

As we can see there is excellent correlation between the PRB figures and profit/return columns with all four in profit. Three of the four had very high A/E indices which is equally positive.

In terms of negatives the two courses with the lowest PRBs Hamilton (0.49) and Wolves (0.50) produced the following overall results:

There have been significant losses at both courses, with Hamilton’s win rate particularly poor also.

Oisin Murphy

Oisin Murphy has been Champion jockey four times in the last six years, and he is undoubtably one of the top riders around. There are 18 courses where he has had enough rides / rivals and the PRBs are as follows (courses with a PRB figure of 0.67 or higher are highlighted in green):

The 0.71 figure for Newcastle stands out and his overall record there is impressive as can be seen in the table below. The table shows the results for the six courses with his highest PRBs:

Four of the six secured a profit to BSP, with two (Kempton and Yarmouth) showing very small losses. It is interesting that four of the six courses were all-weather tracks. It is also worth noting that when riding for Andrew Balding at Newcastle Murphy had a 50% strike rate (9 wins from 18) for a profit of £30.50 (ROI +169.5%). For Hugo Palmer he rode six times at Salisbury, winning five, while at Wolves the pair were five from 10. Admittedly these are small samples but eye-catching, nonetheless.

Saffie Osborne

Saffie Osborne has had some solid looking PRBs across both articles and it will be interesting to drill down into her course PRBs. The graph below shows the different course figures:

The four courses with the highest PRBs were Southwell (0.66), Newmarket (0.65), Brighton (0.64) and Newcastle (0.62). The table shows the results for these four courses:

Osborne recorded excellent profits at all four, with very high A/E indices showing positive correlation with the PRBs. She has ridden those four courses very well in the past four years.

The three courses with the lowest PRBs - Doncaster (0.50), Bath (0.51) and Chelmsford (0.52) - saw returns correlate positively too as each showed significant losses. Losses stood at 30p, 49p and 26p in the £ respectively.

Rossa Ryan

Ryan is the last jockey I am looking at here and his course PRB figures are shown in the table below:

The four highest PRBs are highlighted in green, Chelmsford (0.65), Newbury (0.64), Wolverhampton (0.64) and Lingfield (0.63). Here were his overall results at these four tracks.

All four again were in profit suggesting positive correlation once more between the PRBs and other key metrics. For the record most of his rides at Lingfield came on the all-weather (AW) and his AW ROI% at the track stood at 11%.

The lowest PRB occurred when racing at Sandown (0.51) – his overall record there has been relatively poor, as one might suspect. He had 11 winners from 89 (SR 12.4%) for a loss of £30.71 (ROI 34.5%).

Phew! That was a lot of research and a lot of stats.

Ultimately, as punters we 'live or die' by our final profit/loss figure. Having a high PRB does not necessarily equal profit, but this article has shown that higher PRBs tend to outperform lower ones on the ledger front. As I have always said, the more metrics we can use the better. PRBs are definitely a metric we should use where possible in combination with others: they add a lot more depth, especially in smaller sample sizes.

- DR

Royal Ascot 2025: Analysing The Group 1 Races

9 June 2025/in Dave Renham, Royal Ascot/by Dave Renham

There are three festivals a year I get really excited about, writes Dave Renham. The Cheltenham Festival and Glorious Goodwood are two; and the third, which is soon to be upon us, is of course Royal Ascot. Around this time last year I looked in detail at the big 1-mile handicaps at the meeting - you can catch up with that piece here. This year I am concentrating on the Group 1 races.

Contents

Introduction

There are eight Group 1s run at the Royal meeting and they are as follows:

As would be expected, there is a good mix of different race distances and conditions although there is only one Group 1 race at a distance beyond 1m 2f, the Gold Cup.

In this article I am looking back on the last ten years of these Group 1 contests, trying to find any snippets that may help us when tackling the races this year. Profit and losses have been calculated to Betfair Starting Price (BSP) less 2% commission.

Royal Ascot Group 1s by Market Rank

Let me start by examining the market. I have ranked the runners based on BSP, which is the most accurate way of doing it. Further, it eliminates almost all of the ‘joint’ market positions.

These races have definitely been market-friendly with the top three betting positions each producing a blind profit. Those fourth in the Betfair betting lists have performed poorly but due to the modest sample we can perhaps assume this is an anomaly. Regardless, it seems that the top three in the betting are the ones to concentrate on.

Group 1 Favourites at Royal Ascot

Narrowing in on favourites, below are the Percentage of Rivals Beaten (PRB) figures for each individual race to help give a better overview of favourite performance in specific races. For the record the average PRB figures for favourites across the eight races combined stands at 0.76.

There has been quite a variance with Gold Cup favourites performing best, and by some margin. Their actual performance in the Gold Cup has been as follows:

During the ten year study period the Gold Cup favourite secured five wins, two seconds, a third and two fourths, so no BSP jolly has completely bombed out.

Royal Ascot Group 1s: Top 3 Market Ranks

If we undertake the same type of PRB analysis across the top three in the betting, the graph generally becomes more even:

The St James’s Palace has the highest figure now with the Gold Cup a close second. Nine of the ten winners of the St James’s Palace came from the top three in the betting (four favourites, three second favs, two third favs).

Conversely, of all the races the Commonwealth Cup has seen fancied runners struggle the most. Favourites have won three of the last ten Commonwealth Cup renewals, but there were no wins for second favourites (two wins for third favs). Quite a few horses that were in the top three of the betting have bombed out with 10 of the 30 failing to finish in the top ten, three of them being favourites.

It should be noted that the four winning Commonwealth Cup favourites in the past decade more than paid for the other six losing jollies, returning a profit of 2.55 units at BSP.

Royal Ascot Group 1s by Last Time Out (LTO) Position

The second area I want to look at is recent performance and specifically LTO finishing position. Here is a breakdown of performance by last day finishing position (I have grouped all horses together that finished fifth or worse LTO):

The BSP profit for those that finished third LTO has been totalled skewed by the 140.0 BSP winner Khaadem. LTO winners do look the group to concentrate on with over half of the 80 winners having also won on their most recent start. If we combine LTO winners with a position in the top three in the betting, then we see some excellent results: 36 winners from 115 runners (SR 31.13%) for a profit of £30.50 (ROI +26.5%); A/E 1.14.

It is also worth keeping an eye out for LTO winners that won by at least a length in the race prior to Ascot. These runners have scored 18.9% of the time (30 wins from 159) for a profit of £29.13 (ROI +18.3%).

Royal Ascot Group 1s by Last Time Out (LTO) Race Class

Onto looking at the class of race LTO. Here are the splits:

As we would expect horses that ran in Group 1 company last time have won most often. Those that raced in Group 3 or Listed Class LTO have been profitable, but both have been skewed by very big priced winners going in. Still, Royal Ascot is a meeting where horses fairly consistently win at massive odds.

LTO winners that contested a Group 1 race have actually offered poor value despite a strike rate of close to 30%. The 51 qualifiers lost over 28p in the £ if backing them to repeat the Group 1 win at Royal Ascot.

Royal Ascot Group 1s by Days Since Last Run (DSLR)

It is time to see whether the timing of the last run before Royal Ascot makes a difference. It should be noted this data does not include French, American or Australian runners as I do not have facility to check those. However, it still applies to over 90% of Ascot runners. Here are my findings:

As the table shows, I have included 50 to 240 days as a single group simply because there are very few runners within that grouping, and their performance has been poor. I wanted to help highlight the difference between that group and the group absent 241+ days (or eight months-plus).

The biggest cohort had a run between 22 and 35 days prior to Ascot and their results have been positive given the overall context. To give a broader overview let me share the PRB figures for each ‘days off track’ grouping:

These figures correlate with the win strike rates. The figures for 22 to 35 days and 241 days+ are clearly best. Finally in this section, below is the ten-year performance in Royal Ascot Group 1s of horses from the top three in the betting by days since last run:

Again, this points to the same two groups (22 to 35 days; 241+ days) as the areas in which to focus from a positive perspective. They would have offered punters very good value over the past ten years.

Royal Ascot Group 1 Trainers

The final area I will consider is that of trainers although it should be noted that data is limited. There are a handful of trainers who have saddled at least 20 runners in Royal Ascot Group 1s in the last ten years, and they are shown in the following table:

It is important not to take these figures (especially big profit lines) too literally due to the sample sizes. It is probably more prudent to look at the PRB values to give a better general indication of how each trainer's horses have run:

William Haggas, despite having just one winner from 24, has an excellent PRB figure so it looks like he has been somewhat unlucky in recent years. He has endured five second places, as well as four thirds and five fourths. Haggas looks a trainer that may offer some placepot/ each way value at the very least next week.

By contrast, Roger Varian’s runners have really struggled although a good proportion of his charges have been bigger prices. Indeed, Charyn, in last year's Queen Anne Stakes is Varian's sole Royal Ascot G1 winner to date. There are sure to be more in future but his seem a little over-bet.

Other trainer titbits to share include the fact that Aidan O’Brien's 13 Group 1 winners in the past decade have all been ridden by Ryan Moore (from 61 rides). All other jockeys riding for O'Brien are a combined 0 from 43 since 2015, although again most of these runners were outsiders. Sticking with O’Brien it seems best to concentrate on those starting favourite or second favourite. They have combined to produce 12 of his 13 winners (from 34 qualifiers) returning a small 2p in the £. Finally, albeit from a very small sample, the Gosden stable has had four winners and four placed runners from just 13 runners aged four.

Summary

The Group 1 races at Royal Ascot are the races that owners, trainers and jockeys covet the most, although any win at the Royal meeting is huge.

In terms of the Group 1s, the most fancied runners - those in the top three in the betting - have fared much the best. Don’t be put off by horses having their first run in more than eight months (241+ days) and we might also consider a break of 22 to 35 days (three to five weeks) as more of a positive than a negative.

A last day win is preferable to other finishing positions and a last time out win coupled with a top three position in the betting market has been a very strong positive. From the training ranks, William Haggas appears to have been quite unlucky in the past decade and certainly I’ll be popping a few of his runners in my placepots at the very least. Aidan O’ Brien runners are worth noting if starting in the top two of the betting and particularly when ridden by Ryan Moore.

Wishing you the best of luck with your Royal Ascot Group 1 wagers.

- DR

Evaluating Jockeys by Percentage of Rivals Beaten

3 June 2025/in Dave Renham/by Dave Renham

In this article I will put 35 jockeys under the microscope, writes Dave Renham. These are the riders with the most rides per year, on average, over the past four years. The data has been taken from UK flat racing (turf and all-weather (AW) and the full years 2021 to 2024.

Contents

Introduction

I have further limited the findings to mounts sent off at an Industry Starting Price (ISP) of 20/1 or shorter, in order to try to eliminate most of the horses that had little or no chance; and, further, because very big-priced winners tend to skew profit figures.

For this piece I will primarily examine the data using ‘Percentage of Rivals Beaten’, although I also plan to look at strike rates and A/E indices. Percentage of Rivals Beaten (PRB) is a calculation based on a horse's finishing position in relation to field size. It makes key distinctions between a horse finishing, say, fourth in a seven-horse race (PRB 50%, three rivals beaten, beaten by three rivals) and finishing fourth in a sixteen-horse race (PRB 80%, twelve rivals beaten, beaten by three rivals). We express the PRB as a number between 0 and 1. So, in the examples above, 50% is 0.5 and 80% is 0.8.

As racing researchers we can often be blighted by small sample sizes when analysing, for example, win strike rates. Hence, there is a strong argument to suggest that PRB figures are a more accurate metric, simply because they make datasets bigger: they award a sliding performance score to every runner in every race, whereas win strike rate only awards the winner a score with all other finishers getting zero.

Today's offering has a slightly different flow from usual I will be writing it "as I go along". In other words, I’m sharing the research and my thinking process stage by stage, rather than doing all the research and then writing about my findings afterwards. Thus, my main commentary will appear to be in the present tense. If that makes sense, let's crack on (and if it doesn't, it soon will!)

Top Jockeys' PRB: Overall

I will start by sharing the average PRB figures for each of the 35 jockeys over this four-year period. They are ordered alphabetically across two graphs:

To provide a benchmark, the average figure when combining these jockeys was halfway between 0.58 and 0.59, so 0.585 to be precise. Oisin Murphy has the highest PRB figure, 0.64, followed by five jockeys tied on 0.62 – William Buick, James Doyle, Rob Havlin, Jack Mitchell and Danny Tudhope. Tom Eaves, Cam Hardie and Andrew Mullen have the joint lowest PRB figure of 0.54.

It should be noted that all riders in this sample are above the 0.5 PRB benchmark and so even the lowest in the cohort are out-performing the norm.

Top Jockeys' PRB: ISP 6/4 or shorter

Although I have restricted qualifiers to those priced 20/1 or shorter, there are clearly some jockeys who have more rides at shorter prices than others. Hence, I am assuming that jockeys should have higher PRBs because of this. To help analyse and potentially confirm this hypothesis I am going to look at the percentage of rides each jockey had with horses priced 6/4 or shorter. The table shows the splits:

There is a huge variance here, from William Buick with more than 13% of his rides sent off 6/4 or shorter, to Cam Hardie at less than 1%. Of the six jockeys with the highest average PRBs I noted earlier, five of them were in the top six for the highest percentage of rides (highlighted in blue in this table). Therefore, we can see there is a strong looking correlation between price and PRB, as we should expect.

Top Jockeys' PRB: ISP 12/1 to 20/1

It makes sense next to look at the percentage of rides each jockey had when the qualifiers were bigger prices in order to consider both ends of the price spectrum. Therefore, below is a table showing these percentages when considering percentage of rides from runners priced 12/1 to 20/1.

The three jockeys with the highest percentages (shown in blue) are the jockeys who had the lowest overall PRB figures shared earlier, namely Tom Eaves, Cam Hardie and Andrew Mullen: this is further evidence of clear positive correlation. Also, the lowest four percentages in this group are for Messrs Buick, Murphy, Doyle (James) and Mitchell.

At this early point in my research I am starting to appreciate that despite the fact that PRB is a really useful metric, for this type of research the price of runners is also very important and can significantly sway the balance one way or the other. Hence, the market will be factored in for the remainder of what follows.

Top Jockeys' PRB by Price Range

Having established the importance of the starting price, I have decided to calculate PRBs for different price bands for all 35 jockeys. The brackets I am going to use are again based on Industry Starting Price and they are as follows:

In the table below I have collated the PRBs for each jockey for each price band. The average figures for all jockeys in the list are shown in blue at the bottom of each column, and I have highlighted any PRB that is at least 3% above the average or at least 3% below the average. The 3% ‘above group’ (positive) is highlighted in green, the 3% ‘below group’ (negative) is in red.

The colour coding helps to highlight jockeys that seem to perform above the norm and those that may have performed below what might be expected within each price band. There were three jockeys who obtained two ‘greens’: Robert Havlin, Clifford Lee and Kieran O’Neill. And there were four jockeys who obtained two or more ‘reds’: William Buick (3), Holly Doyle (2), Joe Fanning (3) and Rob Hornby (2).

Top Jockeys' PRB: All-Round Performance

I am thinking that another way we could analyse these data is to simply add up each jockey’s six PRB figures in the above table and compare them. Below, then, are the riders with the top ten combined PRB figures when adding the six values together:

It could be argued that these are the top 10 performing jockeys from my original list of 35 as their totals are based on the overall performance across different price ranges. From looking at these findings I would be happy to see one of these ten riding a horse I am keen to back. Rab Havlin, who has consistently shown positive figures in the research to date, tops the list on a combined total of 3.99. (0.88 + 0.76 + 0.68 + 0.65 + 0.55 + 0.47).

Next, here are the lowest ten combined PRB totals from our sample of the top 35 riders:

As can be seen, we are talking small margins here so despite these ten being at the bottom we know that they are all still top-notch riders. However, in terms of PRB figures within certain price bands, they have performed with slightly less success than the rest of the jockeys in this sample.

To complete the set here are the remaining jockeys (positioned 11^th to 25^th) with their PRB totals. Due to the bigger group, I am using a table rather than a graph:

Top Jockeys: Other Metrics

I stated earlier that PRBs are arguably the most accurate metric but it always prudent to consider other metrics where possible in order to attain a stronger 'feel' for the data.

We know that finishing fifth in an 18-runner race will produce a better PRB figure than finishing eighth in the same the race, but usually finishing fifth does not make punters money (unless those generous bookie types are offering extra places).

At this point, then, I am thinking about the key battles in terms of finishing first rather than second and, therefore, I am going to share the wins, runs, strike rate, profit/loss and A/E indices for all 35 jockeys. As with the PRB data this does not include rides on horses priced over 20/1 ISP. Profits and losses have been calculated to Betfair SP less 2% commission. The A/E indices are based on Betfair prices and any figure above 1.00 has been coloured in green:

Somewhat surprisingly, 18 of the 35 jockeys have secured a profit which is impressive considering there are not any really big BSP winners to skew the returns. In fact, the highest winning BSP was 46.0 and there were only three winners in total above BSP 40.0, and only 23 above BSP 30.0 (out of total of nearly 12,000 winners).

Rossa Ryan, Saffie Osborne and William Buick have the best ROI%s (above 7%), and they each have one of the top five A/E indices. Impressively, Ryan has made a blind profit in each of the four years, Osborne and Buick matching that feat in three of the four years surveyed. There are two jockeys that made a loss in each of the four years, namely David Allan and James Doyle.

Conclusions

All this is helping me, and hopefully you, to start building a more complete picture of jockey performance; or, at least, the performance of these 35 top riders. The PRB data have given us an extra layer on top of the usual metrics we focus on. However, it is becoming clear to me that for this type of jockey-based research we do need other metrics (win percentage, profits, A/E indices, etc) to bring betting utility to the party.

I am just starting to expand the jockey PRB research into other areas and there is plenty more to share; so I have come to the realisation that this article will spawn a second piece. Thus, it is probably too early to draw any key conclusions from the research so far as there are more pieces of the puzzle to add.

However, next week I have a Royal Ascot article ready to go, so it affords me a little extra time to do further digging for part two of this jockey deep dive!

- DR

Geegeez Pace Ratings in 5f Handicaps, Part 2

27 May 2025/in Dave Renham/by Dave Renham

Last week I shared my research into how the four-race pace totals on the Geegeez racecards performed across UK 5f handicaps in 2024 (excluding 2yo nurseries), writes Dave Renham. You can catch up with that article here. The results overall were impressive given we were looking essentially at raw figures with minimal additional ‘tinkering’.

Contents

Introduction

This week I am going to focus on the same dataset but combine the pace rating positions / scores with Dr Peter May’s ratings (the SR column in the Gold racecard).

To recap, the pace tab shows the running styles of the horses for a maximum of their last four races. Each past running style is given a score of between four and one. The splits are as follows:

4 – Front runner / early leader

3 – Prominent racer

2 – Raced in midfield / mid division

1 – held up near or at the back early

The SR ratings are derived from a neural network developed by Peter May. They are much more than a measure of speed; they include a number of form considerations making them a sort of composite of, in Racing Post terms, RPR (Racing Post Rating) and TS (Topspeed) - both of which we also publish in the racecards.

SR Ratings by Win Strike Rate and P/L

My starting point for this article is to see how the SR ratings performed in 5f handicaps in 2024 starting with win strike rate. The graph below shows the splits:

The rating position correlates well with the win strike rate, although the 5th and 6th rated are reversed. Top rated runners have won just over 17% of the time, while those rated 7th or higher have definitely struggled from a win perspective.

I want to now look at the profit/loss figures for the top three rated runners from the SR ratings. This is because later in the article I will combining the top three in the SR ratings with the top three horses in terms of their four-run pace totals (which I order highest to lowest and call the Pace Ratings Rank). Here are the results in terms of the top three ranked in the SR ratings:

As we can see, the top-rated SR runners would have lost a small amount if backing all qualifiers blind. Second rated have nudged into profit while the third rated have seen losses around the 8p in the £.

Combining SR Top Rated with Pace Rank Top Rated

Now we know the raw performance of the SR ratings I will begin to combine them with what I call the Pace Ratings Rank. Let's first look at what would have happened if only backing runners that were top rated by both set of ratings. Here are the numbers:

This is a positive start to the Pace / SR collab! The strike rate has equated to just under one win in every five with returns of over 16p in the £. There were also 26 qualifiers that finished runner-up which is another strong positive meaning that 50 of 124 finished in the first two.

If we expand this slightly to the top three of the ratings for both, we get the following results:

We have increased the number of bets by around 6.5 times whilst keeping a similar strike rate, although return on investment is slightly less. On the upside, though, we would have made more money in profit terms (from a bigger outlay of course). There were 126 qualifiers that finished second including some at tasty BSP odds such as 40.21, 47.97 and 46.0. There was also a third that was beaten just over a length in a 28-runner handicap at BSP odds of 123.97. The horse in question, No Half Measures, raced at Ascot (21/6/24) and was arguably very unlucky having been the best finisher in the far side group in a race where nine of the first ten home raced up the centre of the course.

Considering we are just combining two different ratings in this way, to get such positive results for higher rated runners in both sets, with no other considerations, is extremely encouraging. Now, I appreciate it is just one year of handicap results at one distance, but 809 horses is a decent sample.

Performance of the Lowest Rated on Pace and SR

Let's now switch and combine lower rated runners from both the Pace Rankings and SR ratings. I am looking at the results of horses rated 8th or lower in both rating sets. Here are their combined results:

These are very poor results which breeds more confidence in our earlier positive findings when combining higher rated runners from both rating sets.

Top Three Rated on Pace and SR by Handicap Age Restriction

If we split the 809 horses that were top three rated on both Pace Rank and SR Rating into 3yo only, 3yo+ and 4yo+ races we get the following results:

All three returned a profit, and all three had relatively similar ROIs. These figures demonstrate that these higher rated runners from both sets of ratings have performed consistently regardless of the ages of the horses taking part.

Top Three Rated on Pace and SR by Selected Courses: Positive

I want next to examine the performance of the top three rated on both metrics at a selection of courses that between 2017 and 2023 had the strongest front running biases over the 5f trip. I sourced these courses in the first article by examining individual track performances of early leaders / front runners during that seven-year prior time frame. I used a combination of win percentages, placed percentages and A/E indices to formulate the list.

To recap the 12 courses were: Ayr, Chelmsford, Chester, Hamilton, Kempton, Leicester, Lingfield, Redcar, Ripon, Thirsk, Windsor and York. In that piece I examined solely the top-rated runners from their previous four-run pace totals rather than the top three.

Here now are the figures for horses that were in the top three of both the Pace Ratings and the SR ratings when running at one of those 12 courses:

That's another very solid set of results with a strike rate close to 20% and returns of over 21p in the £.

Composite Ranking Performance

My next port of call was to combine the ranking positions of both sets of ratings to create an overall numerical total. Hence if a horse was top-rated in the SR ratings and ranked 5th in the Pace Ratings/totals that would score six (1+5); if a horse was ranked 4th in both it would score eight (4+4) and so on. Now we know already what a total of two has achieved as those were the results shared earlier for the top-rated in both. Below I have combined the numerical totals into bands in a graph that shows the strike rates for each one:

This graph offers further evidence that combining the higher rated runners in each set produces better strike rates. We have the sliding scale of percentages that we always want to see when looking at any type of rating-based data set. Meanwhile, the 2-4 band (i.e. SR 1st/ Pace 1st, SR 2nd/ Pace 1st, SR 1st/Pace 2nd, and SR 2nd/Pace 2nd) have a very solid strike rate close to 19%.

Using the same calculation method and the same bands I thought it would be worthwhile to look at the Percentage of Rivals Beaten (PRB) figures. This metric considers all finishing positions based on the number of runners in each race. It is a useful metric to analyse where possible. Here are the splits:

The chart presents further strong evidence of the positive correlation we have seen throughout this article in relation to the importance of ranking position within the two sets of ratings. 58% of rivals beaten for the 2-4 band is a materially high PRB figure.

Let me now share the runs, wins, profits / losses for each band:

It is pleasing to see the 2-4 band producing the best ROI% and also seeing the 5-7 band in profit. The 11-14 group have proved profitable but essentially, they had the biggest-priced winner in the whole year (BSP 127.21) which skews their bottom line considerably. The 20+ band would, not surprisingly, have produced very poor returns from a very low strike rate.

Top Rated on SR and 15 or 16 Pace Total

In the first article I looked at some of the data for the highest four-race pace totals, namely 15 and 16. Hence, horses that had gained these scores had led early in either three or all four of those runs. Based on historical research, I've shown that it is reasonable to think that these horses are the most likely to lead in their next race. So what would have happened if we had backed the top-rated SR runner when they had a pace total of 15 or 16? The results read:

This gives us a small cohort of runners but even from a small sample the figures look promising. The PRB figure is an excellent 0.62 which adds confidence to this small set.

Top Three Rated on SR and 15 or 16 Pace Total

What happens if we expand this to the top three rated in the SR ratings with runners who had a pace total of 15 or 16? The splits are:

The number of bets has nearly tripled and although the strike rate and the ROI% have dropped a little, the results are still very positive. The PRB has dropped a little too, but it still stands at a very strong 60% of rivals beaten.

Top Three Rated on SR and Pace Rank, ISP 12/1 or shorter

Finally in this piece I am going to go back to look at the results for horses that were in top three of both the SR ratings and Pace Ratings / totals. To date I have not put in any price restrictions, but as we all know a BSP 100.0 winner can skew the bottom line considerably. One of the main reasons I haven't is because all of the bigger priced winners (BSP 30.0 or more) came from horses that were not in the top three of both. If anything, other rating position bottom lines have been the ones that have been skewed.

However, I felt it only right to share the figures for the top three rated in each when we restrict the price, and to make it clean I am using an Industry SP price cap of 12/1. So, just to clarify, the figures below are those for horses that were in the top three of both ratings and were priced ISP 12/1 or less. The figures are as follows:

These figures are better than the overall figures for top three in both. A 14p in the £ profit over 720 bets would have been an excellent return. The PRB for these runners is a very strong 0.60. All of this from just two things that can be very easily found on the Geegeez Gold Racecards.

Now that looks very good value to me!

- DR

p.s. if you're unclear how to find these, follow the steps below:

1 Look for 5f UK (turf or AW) handicaps, and ignore 2yo races

2 On the PACE tab, select 'last 4 races' and 'Data' view, and sort by Total. Then find the top rated or top three rated in the SR column. In this example, from last night, Jeans Maite was top rated on both last-four Pace Score and SR - and, as you can see from the second image below, won at 7/2 (BSP 4.97).

Made all, won!

An Analysis of Geegeez Pace Ratings in 5f handicaps

20 May 2025/in Dave Renham/by Dave Renham

In some recent articles I have extolled the virtues of the Geegeez Racecard for Gold members, for example, when looking at Dr Peter May’s ratings (the SR column), writes Dave Renham.

Contents

Introduction

Another huge bonus of these racecards is the pace tab. The pace tab shows the running styles of the horses for a maximum of their last four races. Each past running style is given a score of between four and one, as follows:

4 – Front runner / early leader

3 – Prominent racer

2 – Raced in midfield / mid division

1 – held up near or at the back early

Long standing Geegeez members will have read previous articles of mine emphasising the importance of running style / early pace in a race under specific conditions. Usually though I am looking at the performance of different run styles in certain races which is based on knowledge gleaned after the race has been run. For example, how well have front runners performed over a particular course or distance.

In this article I will examine the Geegeez pace figures to see if they can help in terms of giving us an edge pre-race. I have looked at a year’s worth of pace ratings data that was published in the Geegeez Racecards before each race. The focus is on 5f handicaps (excluding 2yo nurseries) as these races tend to accentuate any run style bias. To be clear, the words 'ratings' and 'rankings' are used somewhat interchangeably in what follows. Higher ratings generally equate to higher rankings.

Past number crunching has noted the edge early leaders / front runners have at this minimum 5f distance. [Type ‘sprint’ into the search box here for a five-part deep dive into 5f handicaps]

However, the problem of taking advantage of any front running bias is that we do not know which horse is going to take the early lead in any given race. If we did then most of us would have made enough money to retire by now! The one tool that should be able to help us is the Geegeez Gold pace tab. Logic dictates that the higher a horses’ pace rating total, the more likely it is to lead. Let me share an example of a 5f handicap race run last month focusing on the pre-race pace ratings:

The first point to note, before we look at the pace totals for each runner, is the performance of early leaders at Wolverhampton. We can see from the green box that they have won nearly 25% of the time and, if able to back them all, we would have made huge profit.

This goes back to what I said previously about how useful it would be if we knew the early leader pre-race. Looking at the pace totals we can see they range from 13 to 7 with Wedgewood the highest on 13.

Hence, we would expect Wedgewood to be the most likely early leader. This is the result, with some additional sectional data.

As we can see Wedgewood, under geegeez-sponsored jockey Marco Ghiani, did indeed take the early lead and was never headed. Of course, the top-rated runner is not going to lead all the time, and the top-rated runner is not going to win all the time. However, from some past 5/6f research I shared with readers back in January 2021 those with higher pace totals led more often than those with lower ones and therefore we would expect them to win more often.

The sample size in that article was far smaller than I am sharing now but it was big enough to suggest that horses with the highest pace totals of 15 or 16 would take the early lead around 45% of the time, whereas those with the lowest pace totals of 4 or 5 would take the early lead less than 3% of the time.

In this piece I am more interested in the performance of each horse based on their pace totals / positions in the racecard, rather than how many of the top-rated runners led. Essentially, as punters we want to make money and so I wanted to find out answers to questions such as, “has the top-rated runner made a profit?”, “is the top-rated runner better value than those rated say 8 or lower?”, “do horses with pace totals of 15 or 16 perform better than those with totals of 8 or less?”, and so on.

The 2024 5f handicap data I have crunched covers just under 600 races and that means 5200 horses with their individual pace totals. This, then, is a very decent sample, and one that took quite a while to collate! After all the leg work to input the data, I hoped that I would find something worth sharing! Let’s see…

Pace Rating Rank

To begin with let’s look at performance based on the ranking positions of runners from their four-race pace totals. In the earlier Wolverhampton example this would mean the following:

Horses with the same totals such as Four Adaay and Angle Land have been given the same ranking position. I have applied this idea across all the races in the study. On that basis, here are the win strike rates, with those rated 8th or bigger in one group:

This is the type of sloping graph I had hoped for with the top-ranked pace horse winning more often than the second ranked, who in turn has scored more than the third ranked and so on. However, I had not expected it to correlate so neatly.

Below are the Betfair SP profit and loss figures for the same pace rating ranks.

The top two ranked (inc. joints) have both nudged into profit which is obviously a clear positive. The 4th ranked runners have effectively broken even, but the 3rd ranked runners have let the side down for ‘the top four’ with quite steep losses. Once we get 6th and bigger in the rankings, we can see losses have started to mount up with those 8th or bigger losing nearly 20p in the £.

Looking in a bit more detail at the top two ranked (inc. joints) if we restrict races to those with 12 runners or less, we see the following results:

If, therefore, we had stuck to mid-range to smaller field sizes, then the figures improve further for the top two ranked pace runners. These are tidy ‘blind’ profits using nothing other than the Geegeez pace ratings.

Pace Rating Total

Let’s pivot now to the four-race pace totals covering each horse’s most recent four runs. The maximum total a horse can attain is 16 (four 4s), and the lowest is 4 (four 1s). I have looked at win strike rates first below to see if there is a similar pattern to the Pace Rating Rank graph shared earlier. I have grouped the individual totals up so have joined 15 with 16, 13 with 14 and so on. Here are the findings:

We see the same type of pattern as before, although the 4 to 6 group have just ‘spoiled’ my ideal pace score graph by winning slightly more often in percentage terms than the 7 to 8 group. Again, though, this highlights that horses which have shown more early speed in their most recent four races have a better chance of winning 5f handicaps than those which have not shown gate speed. As we know, higher strike rates do not necessarily mean bigger profits, so let’s see how the returns figures have panned out:

Those horses recording a four-race pace total of 15 or 16 have combined to make a sound profit equating to returns of over 16p in the £. The general pattern is that as the rating totals drop the losses start to increase, although the 4 to 6 group buck that trend.

Pace Ratings at Different Courses

I want to look at some course data now although with only races from one calendar year, several tracks have limited samples to potentially analyse. Hence, as Baldrick would say, “I have a cunning plan”. The first phase of this plan was to back check past pace/run style course data in 5f handicaps from a longer prior time frame. I chose 2017 to 2023, and I examined the course performance of early leaders / front runners. By using win percentages, placed percentages and A/E indices, I was able to order the courses from the most front-runner biased to the least.

From there I decided to group the 12 most biased courses together in one group (group A) and the 12 courses with the weakest front running biases in a second group (group B). The idea was simple: I wanted to compare the 2024 performance of top-rated runners across both groups, with the hope being that the Group A stats for front runners would be far superior to those for Group B. Here are my findings:

Group A

The 12 courses in this group are Ayr, Chelmsford, Chester, Hamilton, Kempton, Leicester, Lingfield, Redcar, Ripon, Thirsk, Windsor and York. Funnily enough, due to plenty of past course / run style number crunching, if I had been given the task to decide what I thought the strongest 5f course biases were without any past stats at my fingertips, I would have chosen 11 of the 12. Knowing that gave me good confidence in this past course data.

So, looking at the top-rated runners in the Geegeez Pace Ratings at Group A courses we see the following results:

These results are rather impressive both from a strike rate perspective (4% higher than the figure for all courses) and a bottom line one. Returns of over 41p in the £ are not to be sniffed at.

Group B

The ‘dirty dozen’ courses in this group are Ascot, Carlisle, Chepstow, Doncaster, Goodwood, Haydock, Newbury, Newcastle, Newmarket, Nottingham, Sandown and Yarmouth. When looking at the top-rated runner across all courses combined, we get the following:

Wow! This is an even bigger differential than I had expected. Returns at these 12 courses have created losses of over 26p in the £. It does seem that the 2017 to 2023 data was a very accurate reflection of the relative front-running biases at these courses.

One would hope that we witness a similar difference between the course groups when looking at horses that achieved a pace rating of 15 or 16 although the sample sizes are a little on the small side now:

Again, we have a significant difference between groups in both strike rate and returns. As previously mentioned, the sample sizes are smaller than ideal but with the correlation between the two data groups being so strong we can have more confidence as a result in these second set of figures.

Top Rated by Age Group

The final area I want to delve into today is top-rated pace runners, and the 15-16 pace score runners, across the three main age groupings. These are 3yo only races, 3yo+ races and 4yo+ races. Let’s first compare the strike rates for the top-rated:

I have to confess these figures surprised me. I expected the top-ranked to score more often in 4yo+ handicaps where the runners are more exposed. However, it is the complete opposite with the top-ranked winning more often in 3yo only races. It should be noted that the average field size for 3yo only races was slightly smaller than for both 3yo+ and 4yo+, but not enough to make any significant difference to these percentages. Of course, strike rate is only one piece of the puzzle and when we look at the overall figures for each in terms of top-ranked in the four-race pace totals we see things change around a little:

The 3yo only top-ranked pace runners did make a profit, but the 4yo+ top-ranked pace runners performed especially well on the profit front. It wasn’t such a good read for the 3yo+ top-ranked runners with losses edging towards 16p in the £.

Now it’s time to see if the horses with a pace rating of 15 or 16 have performed in a similar fashion across the different age ranges. Here are my findings:

The sample size for 3yo only races is small, but they once again have secured the highest strike rate, albeit only just greater than 4yo+ qualifiers. Once again though the best value by far has been in the 4yo+ races with some impressive profits and returns achieved.

Whilst this article has looked only at a single year's worth of 5f handicap pace rating data, the findings across the board have correlated positively. Moreover, with nearly 600 races in the sample we should be fairly confident in the data.

I for one will be keeping an even closer eye on 5f handicaps in the future as there seems to be value in the top two rated runners, and those that have totals of 15 or 16 points. Of course, all the horses with totals of 16 will be top-rated (or joint top-rated), while those scoring 15 will often be either top-rated or second top.

For those who have enjoyed this week’s offering the good news is I have a follow-up piece to share next week – and it’s got some excellent payoffs!

- DR

Two-Year-Old Sires in 2025

13 May 2025/in Dave Renham/by Dave Renham

It is several years since I analysed two-year-old (2yo) sire data and so, early in the flat season, I felt now was a good time to revisit, writes Dave Renham. This article examines eight years of UK flat racing data (turf and AW) spanning from 2017 to 2024. I will be comparing win strike rates, as I usually do for this type of article, but for the first time in my sire research I will also share Percentage of Rivals Beaten (PRB for short) data. There is a strong argument to suggest that PRB figures are the most accurate metric, so I am excited to be able to include them. Further, I will include some A/E index calculations and these will be based on Betfair Starting Prices. (For more on A/E and other metrics used on geegeez, and why we use them - and why we think you should, too - check out this post)

If you have not read a sire article before, let me briefly set the scene. Sires are the fathers of the respective racehorses, and they typically have an influence on their progeny (offspring). For example, if the sire was originally a sprinter there is a good chance that his progeny will perform better at sprint distances than over say marathon trips. Sires also vary in quality, which will generally influence the next generation in terms of inherent ability. Some sires, for example, achieve around one win in every five starts with their progeny, others are nearer one win in 20. Using sire data is particularly useful for 2yo races because the actual horse form can be sparse or indeed non-existent if the two-year-old is making its debut.

Contents

Sires: All Two-Year-Old Races

Let's begin by looking at some sire data for all 2yo races. To qualify a sire must have had at least ten progeny runs in 2024, and 275 or more in total over the eight years. In addition, to make the following list they needed to be in the top 50 in terms of win strike rate. I have ordered them alphabetically:

In terms of win strike rate, then, Dubawi heads the list at 23.26%, followed by New Bay (21.23%), Frankel (19.83%), Kingman (19.2%) and Night Of Thunder (18.15%). From a PRB perspective, Dubawi (0.65), Frankel (0.63) and Kingman (0.63) are the top three. They are followed by French sire Siyouni (0.62), Sea The Stars (0.61) and Lope De Vega (0.61).

From a betting viewpoint, however, Dubawi and Frankel have not offered particularly good value with Betfair A/E indices of 0.93 and 0.89 respectively. Backing Dubawi progeny blind would have yielded losses of over 9p in the £, and Frankel over 16p in the £, at Betfair SP.

Sires: Two-Year-Old Races by Distance

I want to look at some distance data now. I have split the full set into three cohorts: races over 5 and 6 furlongs, races over 7 furlongs or a mile, and races over 1m1f or more. For the record there are on average only 30 races per year for 2yos over 1m1f or more, so for some sires there is limited data there. If a sire has had 20 or fewer qualifying runs over the distance range, I have left that entry blank.

The table shows the win strike rates and PRBs for each distance range. Sires are listed alphabetically once more and any individual sire’s PRB distance range value which is 0.05 higher than one of their others has been highlighted in green:

Let me drill down into some of these sires in terms of distance performance/preference starting with New Bay.

New Bay stands at Ballylinch Stud for €75,000 which looks a bit of a steal based on his 2yo results to date. In terms of distance his offspring have run only 22 times at 1m1f or more so it is at shorter ranges I would like to concentrate. His progeny's strike rate over 7f to 1 mile is more than double that of his 5f-6f figure, and the difference in the PRBs is a very significant 0.10. The Betfair A/E indices show a chasm between the two also with an index of 1.01 for the shorter sprint distance and 1.53 over the longer 7f to 1m range.

New Bay had his first crop of 2yos in 2020 and the graph below shows the win and each way (win & placed) strike rates by year for the 7f to 1m distance:

The each way figures are all over 40% with 2024 nudging over 50. 2023 saw a slight dip in the win rate but, overall, this performance has been extremely impressive. Backing all qualifiers blind would have yielded a profit in every year to BSP with three of the five seeing ROI%s of over 80%. In terms of yearly PRBs and A/E indices we see the following:

These figures correlate well with each other and with the pure win strike rates. Over 7f to 1m, New Bay looks a sire to keep on side.

Havana Grey is a relatively new sire on the scene (first crop 2022), but his progeny have already shown a strong preference for sprint trips. Considering his runners over 7f-plus first, this group would have lost us nearly 60p in the £ if betting all 153 of them (14 won).

By contrast, switching to shorter trips (up to six furlongs) his issue have fared particularly well when strong in the market. Those starting in the top two of the betting have secured 74 winners from 204 (SR 36.3%) for a profit of £26.13 (ROI +12.8%). Additionally, Havana Grey progeny that have taken the early lead over these sprint trips have performed well above the norm, winning 38 from 108 (SR 35.2%) for a profit of £108.67 (ROI +100.6%).

For No Nay Never, the 6f trip specifically looks optimal. Below are the yearly win and each way strike rates for No Nay Never two-year-old progeny at six furlongs:

These are consistent figures and, in terms of yearly PRBs and A/E indices, we see the following:

Five of the seven annual PRB figures are above 0.60, while all bar one of the A/E indices are over 1.00 - excellent numbers.

No Nay Never is a fine 2yo sire worth keeping in our corner; and his record at distances other than six furlongs is solid, too. At 7f-plus his runners have secured a BSP profit in five of the seven years (five of the last five).

Soldier’s Call has only thrown two crops of racing age thus far - 2025 will be his third - but already there is a strong suggestion that the shorter the trip the better for his juveniles. That should come as little surprise given that Soldier’s Call was a top-notch sprinter himself (2^nd in the Nunthorpe, 3^rd in the King Charles III (formerly King's Stand), 3^rd in the Abbaye). At a flat 5f only (thus, excluding 5½f) his strike rate was a tad above 16%, while at 6f it was 9.2%, and over 7f+ just 1.4% ( 1 win from 74).

Sires: Two-Year-Old Races by Going

The next area I want to look at is the going. I will share PRB figures for turf versus all-weather, as well as splitting the turf going into four subsets – good to firm/firm, good, good to soft, and soft/heavy. Any value within each sire’s groupings that I perceive to be strong or weak I have coloured green (positive) and red (negative). These are only my interpretations of the PRBs and that may differ slightly from how others may perceive them. Anyway, here are the splits:

This table offers a few useful sire pointers, four of which I'd like to highlight.

Firstly, returning to New Bay we see that his progeny PRB figure on good to firm or firmer has been poor in comparison with his figures for other ground conditions.

Mayson has performed far better on easier ground (good to soft, soft and heavy), while Acclamation has been better with firmer conditions (good to firm+).

Too Darn Hot has had excellent results on easier ground (good to soft or softer) hitting a strike rate of 23.5% (24 wins from 102 runners) for a profit of £38.50 (ROI +37.8%).

Sires: Two-Year-Old Races by Gender

The penultimate sets of 2yo sire PRBs I want to share are connected with the sex of the horse – in other words, whether the progeny was male or female. I have included the win strike rates as well as PRB and, again, I have colour coded some PRBs either positive or negative based on my perception of the specifics of the individual sire’s data:

Possibly the most powerful stats from this table come from Kodi Bear. Looking at the bare numbers it seems as though males have had a significant edge; this is further underlined when comparing the profit/losses, returns and A/E indices:

As the table above shows, there is a differential of around 37p in the £ in terms of returns; males have much better figures across the board.

Sires: Two-Year-Old Races when Betfair Market Leader

Finally in this piece I am going to look at the results when the 2yo has started favourite on the Exchange. In the table I have included the sires that had 50 or more runners start favourite during the eight year study period:

Just over half (19 of 37) returned a profit to BSP which is more than I was expecting. It is interesting to see Dubawi and Frankel again both making losses, with their high profile progeny typically wildly over-bet. The PRBs for the sires listed range between 0.83 (Harry Angel and New Bay) down to a very skinny 0.71 (Muhaarar).

There are seven sires that, based on these past stats, are worth noting when starting favourite in the future. They are Bated Breath, Harry Angel, Kodiac, Lope De Vega, New Bay, No Nay Never and Oasis Dream. All have been profitable, all have A/E indices of 1.10 or above, and all have PRBs of 0.80 or more in this context.

There were a few more tables than usual in this piece, but I felt that was necessary to convey the differences between sires under certain conditions. I hope this will help us when betting on 2yo races this season and beyond.

The fifty sires discussed have combined to father around 40% of all raced 2yos in UK between 2017 and 2024. That is not, of course, to say that we should ignore other sires but these are the most prominent.

It is important also to note that many sires imbue their progeny with no obvious preference for distance or going or whatever else. We must recognise the limitations of datasets, and that even neutral statistics have some utility in our betting, albeit probably less so than positive and negative ones.

- DR

When Horses Change Stable: Part 2

6 May 2025/in Dave Renham/by Dave Renham

This is the second of two articles looking at horses that have switched stables on the flat, writes Dave Renham. The first article looked at horses’ first run for a new yard, while this one examines the second run from that new stable. We’ll call them TC2 (Trainer Change 2^nd Start).

As I mentioned last time, the one stipulation is that the switch is from a horse that has been running on the flat and not National Hunt. This is mainly because there are some dual-purpose horses that switch yards each year from a dedicated National Hunt stable to a flat stable.

The data has been taken from the last ten full years (2015-2024) of flat racing in the UK (turf/AW) and all profit and loss has been calculated to Betfair SP with 2% commission applied on any winners. This is also the first article where the A/E indices (Actual versus Expected) will be based on BSP not Industry SP.

Contents

To recap, the last article noted that all horses that have had their first run for a new trainer having switched stables scored 8.2% of the time and actually made a blind BSP profit of £732.49. This equated to a 4.65% return on investment. Unsurprisingly, these overall figures included some horses winning at huge prices: there were 12 winners that paid 100.0 or bigger ‘on the machine’ with the majority lying between 100.0 and 200.0. The two biggest winners, however, were enormous at 429.02 and 503.82. Having said all that backing all 100.0+ qualifiers actually showed a loss of £279.72 (ROI -11.2%).

All TC2 Runners

So how about all horses having their second start for a new stable. Are the overall figures similar? Let’s see:

Despite a slightly better win strike rate, we see fairly steep losses. Most of these losses have been incurred by the genuine outsiders and, if we ignore the 2153 horses that started 100.0 or bigger at BSP we get much closer to parity:

The returns now show a small loss of just over 1½ pence in the £, and if we further restrict all qualifiers to those priced BSP 20.0 or shorter we hit profit:

These runners on roughly once in every six starts and returned a profit of just under 5p for every £1 staked.

TC2 Runners Sent Off Exchange Favourite

Sticking with the betting market let’s now focus on Exchange favourites.

These figures are very similar to the ones we saw for first-time switchers – but while those runners made a small profit of just under 2p in the £, the second start cohort produced a small reverse of a penny in the £.

Let’s next compare the annual performance of these BSP favourites by examining their ROI%.

As we can see there is a bit of a mixed bag, but this is to be expected based on an average of 130 qualifiers per year. There were three poor years (2018, 2019 and 2021), two profitable years (2015 and 2020), and five years that have been close to breaking even, albeit all showed a small loss.

There are a few angles where horses having their second run for a new trainer have made a profit when starting as favourite. These are:

Favourites in non-handicaps won 90 races from 190 (SR 47.4%) for a profit of £27.55 (ROI +14.5%).
2yos when starting as market leader won 24 races from 54 (SR 44.4%) for a profit of £17.60 (ROI +32.6%).
Favourites racing in Class 1 or 2 company won 25 of 79 starts (SR 31.7%) for a profit of £12.50 (ROI +15.8%).

TC2 Runners Sent Off Exchange 2^nd or 3^rd Fav

Next, let’s now combine second and third favourites to see how they fared.

As we can see a nominal profit has been achieved. It is interesting to note that 2yos sent off second or third favourite made a profit (as we saw earlier when 2yos started favourite). This cohort of runners won 23 races from 88 (SR 26.1%) for a healthy profit of £36.37 (ROI +41.3%); A/E 1.57. The profit was solid in both nursery handicaps and non-handicaps.

Before moving on, it should be noted that 2yos having their second start for a new trainer having switched yards perform really poorly when not in the top three in the betting. This group of runners won less than 3% of the time (12 wins from 421) for a hefty loss of £196.62 (ROI -46.8%); A/E 0.70.

TC2 by Last Time Out Finishing Position

Next, I would like to look at last time out (LTO) performance in terms of finishing position on most recent start. Here are the results for horses that finished in the first three LTO:

Horses that finished second on their most recent start (their first run for their new trainer) did particularly well, but LTO winners also nudged into profit. Horses that finished fourth or worse LTO scored just under 6% of the time and lost over 12p in the £.

TC2 by Gender

It’s time to review any impact the sex of the horse has on performance. In the last piece I showed how male horses tend to slightly outperform females when analysing all races, winning roughly 1.12 times as often. To create this figure, I divided the male win strike rate by the female win strike rate in all flat races over the past ten years. That was, and still is, our benchmark. When we looked at the figures for horses switching stables and racing for the first time this figure increased to 1.27. Do we see a similar widening of the gender gap with the second time start figures?

The male strike rate is nearly 2% higher than the female one and this equates to winning 1.22 times more often. This is still comfortably above the average figure of 1.12, but a little down on the 1.27 mark for first time switchers. It seems logical to assume that a fair percentage of female horses may still not have totally settled into their new surroundings.

Before looking at trainer angles, I would like to share some LTO Industry SP price data. Horses that started 6/1 or less LTO have produced solid looking figures:

A modest 2p in the £ loss for all such qualifiers. If we focus on those that had also raced within 30 days we get to a near break-even stuation.

TC2: Trainer Angles

Onto trainers now which may provide the most worthwhile findings for many readers. Below is a list of all trainers that have run at least 80 qualifiers:

Two trainers noted in the first article for having a decent record with horses having their first run for the stable have fared well again, namely Kevin de Foy and David Loughnane, although Loughnane has performed less well in the last few seasons. His record has tailed off since 2020. Of the other trainers, Iain Jardine, who made a profit from a low strike rate last time, has improved that strike rate to over 12% and hit a profit once again.

Two trainers that stood out positively last time, Mick Appleby and Archie Watson, performed less strikingly on second start for the yards, although both have still produced good strike rates.

Mick Appleby has done brilliantly with horses that finished second LTO – these runners won 18 races from only 46 runners (SR 39.1%) for a profit of £22.62 (ROI +49.2%).

Going back to Kevin de Foy he has hit an excellent strike rate of over 21% and his returns are not skewed by any horses winning at huge odds (his biggest priced winner was BSP 19.13). If you ignore his LTO winners (who did connections a favour obviously on their first start for the yard) his record improves slightly to 14 wins from 68 (SR 20.6%) for a profit of £40.22 (ROI +59.1%).

In the first piece it was noted that Richard Fahey had underperformed significantly with his new recruits on their first start. However, his record on their second start is much better. In that context, he improved the strike rate from just above 7% to nearly 13% and such runners edged into profit. However, as with David Loughnane, his record was better in the earlier part of the ten-year time span.

Jane Chapple-Hyam just failed to make the list in my first article as she did not have quite the required number of runners. Here she does make the cut and has a very solid overall record. However, she did have one huge-priced win which accounts for all of her profit figure. Having said that, horses that started in the top four of the betting performed well for her with 11 of the 33 winning (SR 33.3%) and a tidy profit of £24.89 (ROI +75.4%).

David O’Meara has a very similar record with horses having their first or second runs for him having switched stables. One positive stat to share with those having their second start is that horses which finished 2^nd, 3^rd or 4^th LTO are worth noting. They won 19% of the time (23 wins from 121) for a profit of £41.28 (ROI +34.11).

Trainers to generally avoid with horses having their second run for the yard are Charlie Wallis and Philip Kirby: both have very poor records.

Trainers: TC1 vs TC2

I thought it would be useful to make a trainer comparison between horses having their first starts for a yard with their second, beginning with win strike rate. I have highlighted in green the better figure of the two unless they are within 1% of each other:

Taking this group of trainers as a whole, most of them have similar strike rates for both groups. Attwater, Fahey, G+J Moore, Watson, and Stuart Williams have the biggest differentials.

Now I am going to compare the A/E indices which helps to determine ‘value’. This time I will highlight in green any A/E index which is 0.30 bigger than the other figure which is a significant difference for this particular metric:

For six trainers, horses having their first run for the stable proved considerably better value than when making their second start. The six were Mick Appleby, Julie Camacho, David Evans, Ivan Furtado, David Loughnane and Archie Watson.

Five trainers enjoyed the reverse scenario with second runs for the stable producing much better value than first runs. This quintet comprised Michael Attwater, Mick and David Easterby, Gary and Josh Moore, Rebecca Menzies and Stuart Williams.

The final comparison I will make is with the PRB figures (Percentage of Rivals Beaten). I would expect these figures to positively align to some extent with the win strike rates. I have highlighted in green any PRB that is 5% (0.05) higher than the other. Here are the splits:

For most trainers the win strike rates and the PRB figures align quite well. For example, Watson’s figures of 0.57 and 0.51 highlight the much better performance with first time starters for the stable. Likewise, we have seen that the Moore stable has performed far better with horses having their second start for the stable having switched yards, and the 0.33 vs 0.44 PRBs back this up. There are several more good examples of this including for Caroll, Chapple-Hyam, M+D Easterby and Menzies to name but four. The one real outlier is David Evans whose PRBs are completely the reverse of his strike rates.

Using different metrics for comparisons for individual trainers does help us understand the numbers better and gives us a better overall feel for the data.

So that wraps this piece, and the two-part trainer change series, up. I hope they have been both useful and interesting. These two articles should give us plenty of pointers to help in our quest to make long-term profits from racing. Until next time…

- DR

When Horses Change Stable: Part 1

28 April 2025/in Dave Renham/by Dave Renham

In my next two articles I am going to look at horses that have switched stables on the flat, writes Dave Renham. This one will look at the first run for a new yard, and the next one will examine the second run for new connections. The one stipulation is that the switch is from a horse that has been running on the flat (i.e. not National Hunt). This is mainly because there are some dual-purpose horses that switch yards each year from a dedicated National Hunt stable to a flat stable.

Contents

All Trainer Changes

Let's start by looking at all horses having their first run for a new trainer:

Overall, stable switchers made a profit to BSP but of course these figures are skewed by some very big prices going in. The strike rate is around one win in every 12 so we are relying on enough big prices winning for us to cancel out the numerous losing selections. Below I have shown how these figures have fluctuated year on year in terms of profit/loss to £1 level stakes to BSP:

The journey to the overall 732 unit profit has not been a smooth one, to say the least. It seems clear that we need to be far more selective in our approach.

Trainer Change: Market Factors

Let's now examine market factors in terms of the more fancied end of the market, starting with stable switchers that started favourite on their first start for a new yard. For market rank I am using Betfair Exchange prices, so the Exchange market leaders. Here are the results:

Favourites have just edged into profit which is always good to see. Splitting favourites into non-handicap versus handicap we get the following results:

There have been far more handicap switchers than in non-handicaps, and that group has provided the profits. Handicap favourites have also secured a decent A/E index of 1.00.

Next, let's combine second and third favourites to see how they fared.

We have similar figures here with a very small profit being achieved. It's worth breaking down by race type once more:

We again see a similar scenario here with second/third favourites in handicaps making a decent profit. The non-handicap results are actually quite poor with losses of over 16 pence in the £.

If we now combine the handicap results for those horses that started in the top three in the betting on their first start after switching stables, we get the following yearly splits:

The table shows seven winning years out of ten with the last six years all seeing a BSP profit.

Trainer Change: Last Time Out (LTO) Performance

I would like to look at last time out performance next in terms of a horse's finishing position on its most recent start. Here are the findings:

We have similar strike rates for those that finished first, second or third LTO. As you might expect, this drops considerably for horses that finished fourth or worse. LTO winners were profitable, but it is the bigger prices that have made this happen. Those LTO winners that were priced 18.0 or bigger at BSP produced 26 winners from 454 runners (SR 5.7%) for a profit of £377.15 (ROI +83.1%). Once again if we restrict things to just handicap races these figures improve to 24 wins from 385 (SR 6.2%) for a profit of £399.30 (ROI +103.7%).

Trainer Change: Gender of Horse

Time to compare the sex of the horse next. Male horses tend to slightly outperform female horses, winning roughly 1.12 times as often. To create this figure, I divided the male win strike rate by the female win strike rate in all flat races over the past ten years. That is the benchmark. The win strike rates for first time switchers are as follows:

When dividing these strike rates, we get a figure of 1.27. This suggests perhaps that male horses settle more quickly in their new surroundings compared with female horses.

There is also a big difference between the two in terms of profit and loss too:

Based on the figures, it does seem that male horses are a far better bet than females when having their first run for a new trainer.

It is also worth noting that female runners have performed better when having at least a month at their new yard before running again. Female stable switchers that returned to the track within 30 days lost 36 pence in the £ with an A/E index of 0.71; those which were rested 31 days or more would have lost you less than 2p in the £ with an A/E index of 0.91.

Trainer Change: Individual Trainer Records

I am sure the most interesting data for most readers will be the individual trainer results. Below is a list of all trainers that have run at least 100 qualifiers, ordered by win strike rate:

16 of the 27 in this list proved profitable to BSP and I would like to focus on a few of them, starting with Mick Appleby.

Appleby’s strike rate of close to 19% is exceptional considering his overall strike rate for all runners is just over 11%. He seems to have a knack of getting the best out of his new recruits first time out. Below is a graph detailing his profit and loss by year:

Seven winning years, two losing years and 2023 effectively hitting a break-even scenario. It should be noted that a good chunk of these profits occurred between 2015 and 2019. However, Appleby has still proved profitable overall in the past five years although to a lesser extent as the market cottons on.

Appleby is not one for turning his new recruits out again quickly after acquiring from another yard: only 11% of them have returned to the track within 30 days. This policy of having longer with the horse before its first run for the stable has proved to be a good one.

Do take note of Appleby runners that drop back in distance. This cohort has provided him with 35 winners from 161 qualifiers (SR 21.7%) for a profit at Betfair SP of £138.25 (ROI +85.9%). One key attribute in a trainer is being able to pinpoint the exact best distance that a horse should run: Mick seems very good at this.

Kevin de Foy is a relatively new trainer on the block but his figures are very solid, hitting close to one win in every five runs. He has done particularly well when his runners have started as favourite – 10 wins from 23 (SR 43.5%) for a profit of £8.74 (ROI +38%). Like Appleby he is not a fan of turning his new recruits out quickly, with just five of his 112 runners racing within the first month. Indeed, his record with those runners off the track for 150 days or more is highly impressive. They have won 10 of the their 43 starts (SR 23.3%) for a profit of £19.76 (ROI +46%).

David Loughnane has produced a solid 15% win rate with horses new to his yard, and they have performed particularly well when having their first stable start on the all-weather. This cohort won 16 of 89 starts (SR 19.8%) for a healthy profit of £35.15 (ROI +39.5%). That improves further if restricting runners to those that stick to the all-weather having raced LTO on a non-turf surface as well. These runners have scored 13 times from 53 (SR 24.5%) for a profit of £45.35 (ROI +85.6%). There has been one negative and that is horses aged five or older. They have won just twice from 33 starts (SR 6.1%) and lost 40p in the £. Loughnane has a far better record with his three- and four-year-olds who both have win strike rates of over 17%.

Archie Watson has secured the best strike rate of all the trainers in the table hitting close to 23%. He has been extremely consistent with his win percentage being 19% or higher in every year since 2017. For the record he was 0 from 6 in 2016 and had no qualifiers in 2015. He has been profitable in every year bar one since 2018 with the losing year (2019) producing only small losses of under 4p in the £.

One of the strongest stats Watson has is when he books Hollie Doyle to ride his new recruits. This combo has provided 16 winners from just 47 runners (SR 34%) for a BSP profit of £85.26 (ROI +181.4%). A second very strong stat, arguably even stronger than the Doyle one, is when his new runners race after a break in excess of 300 days. These runners have won an amazing 48% of the time (12 wins from 25) for a mouthwatering profit of £55.89 (ROI +223.58).

Below is a graph highlighting all trainers with 100+ runners that have secured an A/E index of over 1.00 suggesting their runners have offered punters value. Not surprisingly perhaps Appleby, de Foy, Loughnane and Watson are all there:

In terms of trainers with poor records, perhaps the most surprising is Richard Fahey. In fact, he has not had a winner on first switching to his yard since June 2020, a run of 36 consecutive losers. There are a few very poor stats for Fahey including his turf record of just 4 wins from 80, and his record with female horses which stands at 1 win from 32.

Other stables to be cautious about on first start after a switch seem to be Stuart Williams and the Moore's, Gary and Josh.

I think I've unearthed plenty of useful stats in the research to date. Some of my favourites include:

Trainer change runners in the top three in the betting in handicaps have produced solid long-term profits
Male horses running first time for a new yard have performed far better than female horses
Trainers Mick Appleby, Kevin De Foy, David Loughnane and Archie Watson all have very good records with trainer switch runners
Trainers Richard Fahey, Gary/Josh Moore and Stuart Williams have poor records on their first run for the yard

In part 2, I will be sharing my findings on how trainer change runners fare on their second starts for their new yards. See you next time.

- DR

‘SR’ Ratings on the Flat (Turf)

22 April 2025/in Dave Renham/by Dave Renham

For this article I am revisiting the ‘SR’ ratings which can be found each day on the Geegeez Gold racecard for UK races, writes Dave Renham. I wrote a piece in February looking at these ratings on the all-weather and, as the turf season has been going for just over three weeks now, I thought it a good time to analyse the ratings on the turf flat. If you haven’t yet read the first piece allow me explain about these ratings in more detail. If you did read that piece feel free to skip the next two paragraphs.

The SR ratings figure is derived from Dr Peter May’s research. Peter is very well respected within the horse racing community and to have his ratings available daily on the Geegeez Gold racecards is yet another positive for subscribers. Matt wrote an article in September 2023 looking at the performance of the ratings in National Hunt racing. In that piece he explained that Peter’s ratings are not strictly ‘Speed’ ratings. He wrote,

Peter's numbers are derived from a neural network: he's been doing artificial intelligence (AI) since long before it became fashionable. And they're much more than a measure of speed; they include a number of form considerations making them a sort of composite of, in Racing Post terms, RPR (Racing Post Rating) and TS (Topspeed) - both of which we also publish on geegeez.”

Hence Peter’s ratings are unique.

As I stated in my opening salvo the focus for this article is turf flat racing. I have looked at a five-year time frame from January 1st, 2020, to December 31st, 2024. Any profit or loss has been calculated to Betfair SP less 2% commission on winning bets. When I refer to the ratings from now on, I will call them SR Ratings as that is how they appear on the racecards.

Now ratings are just that, a hierarchical set of numbers. The key to a good set of ratings is not whether the top-rated runners make a long-term profit or not. Of course that would be an added bonus but, essentially, to measure the effectiveness of ratings we need to look at the win strike rate. The top-rated runner should have the highest win percentage, the second highest should win next most often, and so on, gradually reducing for the other runners. Ideally there would be a significant difference in strike rate between, say, the top-rated and the fourth highest, and likewise with the fourth rated and the eighth rated, and so on.

Let’s start with looking at the win percentages (strike rates) for the ranked ratings. This covers all races on the turf flat over the period of study. The horizontal axis is labelled from 1, the top-rated runner, 2 the second rated, and so on:

The win strike rate for top-rated runners is 20% or one win in five. This figure correlates well with the AW top-rated figure noted in my first article which stood at 19.6%. The percentages correlate positively with the rating positions showing a sliding scale that we would hope to see. If we look at the Each Way (win & placed) strike rates, a similar pattern can be seen:

The top-rated runner is comfortably clear once more, and the sliding scale is replicated showing positive correlation with the win figures. The top-rated figure of 42.9% is just under the AW one of 44.6%.

Before moving on, it should be noted that there is a good proportion of horses that do not have an SR rating as they are either unraced or yet to race on flat turf in the UK. These unrated runners are far more prevalent in non-handicaps as you would expect.

Overall, 15% of all runners (non-handicaps and handicaps combined) do not have an SR rating. To give some context for their success, these runners have won 8.2% of races in non-handicaps and remarkably the same figure of 8.2% in handicaps.

Sticking with the SR rating ranks as a whole, I would like to share the A/E indices for different positions in the rankings. I have grouped the positions, so ‘1 to 3’ stands for the top three rated runners combined, ‘4 to 6’ is the fourth- to sixth-rated runners combined, and so on.

As we can see, the best value lies with the top three in the ratings and there is then a sliding scale as we progress through the groups, once more indicating that the higher the position in the ratings the better the value. Along with the earlier strike rates, this is a further positive as far as the SR ratings on the flat turf are concerned.

Let me now split the races into handicaps versus non-handicaps and compare win strike rates for the top-rated with the second-rated runners:

In non-handicaps the top rated has won over 27% of the time and is around nine percentage points clear of the second rated (about 50% relatively). In handicap races the gap is significantly closer at 1.4% (about 10% relatively), but this is to be expected given the competitive nature of handicaps.

Here are the overall results for these runners:

The top two rated in non-handicaps have combined to achieve a positive return, with 2^nd rated runners providing virtually all of those profits. The handicap top-rated runners would have lost us just over 1 penny in the £ which is very good going given the competitiveness of such races.

Non-handicap top-rated

I would like to dig deeper into SR top-rated runners in non-handicaps starting by splitting their results by age. Here are the findings:

Top-rated 3yos have won close to 30% of the time producing a small profit. The smaller 4yo group have produced the best returns coupled with a decent A/E index of 0.97. Once we get to 5yos and older these top-rated runners have performed below the norm and look a subset to avoid. Top-rated 2yos have made a small loss of 2p in the £ but considering that a fair proportion of 2yos are unraced (so cannot be rated) this is another solid ratings performance.

Next, I would like to split the results by price. I have done this by creating Industry SP price bands as these are the odds used in the Geegeez Query Tool:

Top rated horses priced Evens or shorter have just nudged into BSP profit, but the best figures have some from those priced 11/2 to 8/1 and 17/2 to 12/1.

It is interesting, too, when we compare the top-rated win strike rates for these two price bands with all remaining runners combined. We would expect the strike rates to be within a decimal place or two as we are effectively talking about the same price point. However, this is not the case as the table below shows (I have included the A/E indices too for comparison purposes):

These findings confirm that, for this price range at least, top-rated runners in non- handicaps have performed well above the norm and have offered punters excellent value.

A look at race class next to see if we can spot any patterns:

Top-rated runners in Class 1 and 2 non-handicaps have both made a profit, as has the Class 5 group. Class 4 results are comfortably the worst in terms of returns. I am guessing here, but it might be because class 4 non-handicaps have had the highest proportion of unraced horses which, of course, are unrated. This could mean we get a few more surprise results because of this.

Handicap top-rated

It’s time to move onto handicap top-rated runners starting as we did for non-handicaps with the age of runners:

The 2yo top-rated runners under-perform a little especially in terms of the bottom line, but 2yo handicaps (nurseries) are notoriously tricky affairs. In terms of returns there is little in it between 3, 4, 5 and 6yos – these are very consistent results. 7yos have a modest record, but I think this is probably a slight anomaly. The oldest runners, those aged eight and older, have turned a profit, but a BSP winner at 60.0 made a significant contribution to those figures.

Let’s now split the top-rated handicap results by Industry SP. I am using different price bands than earlier due to handicaps having less very short-priced runners:

Looking at the profit / ROI columns it seems that focusing on shorter priced runners, those 13/2 or lower, might be the way to go. That has certainly been the case over the last five years.

So, to race class next. There have only been two Class 1 handicaps, so I have ignored those. Here are the splits for the other grades:

The higher class of race for top-rated non handicappers was best, and we see a similar pattern here. Class 2, 3 and 4 handicaps have all made profits to BSP with very solid A/E indices to boot. Class 5 and 6 top rated have still performed OK, but below the level of those higher grades.

The final piece of digging is connected with run style. As regular readers will know, I consider run style to be very important in certain races, especially some handicaps. Here, then, are the win percentages for top-rated SR runners across the four run styles. This covers all handicaps at all distances:

Early leaders / front runners that were top rated on the SR ratings have won nigh on 25% of the time (one win in every four). This follows the pattern we have seen numerous times in the past. Of course, we only know the early leader after the race has started but if we had managed to predict when the top-rated runner would take the early lead in a handicap, we would have won £1006.01 to £1 level stakes. This equates to huge returns of over 51 pence for every £ bet. Nice money if you can get it and, importantly, a reasonable margin for error in picking top-rated runners that didn’t go on to lead in their races.

Geegeez Gold has so many benefits for punters and these SR ratings are definitely one of them. I hope this article has uncovered some useful SR rating angles that can be deployed over the coming weeks and months.

- DR

From a Place, to a Different Place

15 April 2025/in Dave Renham/by Dave Renham

Before I start, I should apologise for the rather clunky title, but hopefully it will soon make sense, writes Dave Renham. We all know that not all form is equal: a win at Ascot may generally be considered more meritorious than first place at Catterick, for example.

I decided to see if there is any pattern in how form translates from one track to another. To do this, I focused on horses that finished in the first three last time out (123LTO), comparing results between the 'placed run course' and today's track. In other words, I'm trying to find a relationship - positive or negative - between the host track of an ostensibly good (first three finish) run last time and the course next time. Confused? Let's break it down.

The dataset is UK flat racing between 2017 and 2024 with the focus mainly on the turf courses. However, there is some all-weather (AW) course data shared when the other course is a turf one. Put another way, there is no comparison between all-weather tracks. Profit and loss figures have been calculated to BSP less 2% commission on winning bets.

To begin with let's look at the results for all races/courses of horses that finished in the first three LTO:

This is our baseline against which to measure our 123LTO course to today's course results. The win rate overall is around one in every six races with losses of just under 4p in the £ at BSP, which is a fairly solid starting point.

Here are the top 20 win strike rates in terms of today's course to 123LTO course. Here are the numbers (80 runners minimum to qualify):

There are some excellent strike rates here, all well above the 16.4% average figure. 18 of the 20 have seen a BSP profit; and 17 of the 20 have seen an A/E index in excess of 1.00. It is interesting to see that Newmarket has been the LTO course in six of the above, five times horses coming from the Rowley course, once from the July. It is equally noteworthy that very few of the Grade 1 tracks appear in the current course column. I will discuss and dig deeper into this area later in the piece.

Next, here are the 20 lowest win strike rates:

These are a huge contrast with the first group: all bar one has a win percentage below 8% (worse than one win in 12) and huge losses were incurred in 19 of the 20. The A/E indices are generally poor as we would expect given the other metrics, but 16 are 0.60 or lower which is extremely low. What also stands out here is that the left hand column showing the 'today' course where the vast majority are Grade 1 tracks, York and Ascot accounting for 12 of the 20 between them. Meanwhile, the second column of 123LTO courses is largely comprised of lower tier tracks.

My next port of call was to classify each course into grades (It will become apparent later why I’m doing this). There are eight Grade 1 tracks on the flat: Ascot, Doncaster, Epsom, Goodwood, Newbury, Newmarket (both courses), Sandown and York. My plan was to grade all courses in the most accurate way possible. I had two ideas. The first was to work out the average prize money at each course over the time frame; the second was to work out the average race class level. I chose the latter because I thought using prize money could see some course averages get skewed due to the very biggest races offering such huge purses; thus, using the average class of race I felt would be more accurate.

Here are my findings for each course. I have put them into three graphs with the courses in alphabetical order:

Ascot has hosted the highest average class of race, with Brighton the lowest; and there is a significant difference between the two. Ascot averages 2.16 (i.e. between Classes 2 and 3 on average, much closer to Class 2), while Brighton is down at 5.43 (midway between Classes 5 and 6). To help give some context, 55% of Brighton’s races have been Class 6 events, whereas at Ascot 34% of races were Class 1 and 31% were Class 2.

From here I decided to grade the tracks (Grade 1 courses seeing the highest class of races, Grade 5 seeing the lowest):

The average bands I chose were partly based on the individual course averages and partly 'feel-based'. For example, Windsor was on 4.52 and I felt it should be in the Grade 3 group, hence I chose 4.55 as the upper range for that grouping. Having decided upon the splits here are the courses that appear in each group/grade:

As you can see the majority of the courses land in Grade 4 or 5. It would be preferable perhaps to have slightly more even numbers in each group but those seemed to me to be the most sensible divisions.

Having embarked on this course grading journey let me explain my rationale. I wanted to group the 'today' and 123LTO course data into bigger sets then individual tracks to see if there were any useful patterns. For example, going back to the lowest 20-win strike rates table I shared earlier, that table highlighted that horses which finished in the first three at some lower grade tracks performed poorly if reappearing at one of the higher grade tracks. Is that the case generally? Let’s find out!

To begin with I have simply compared the results based on the course grade 'today' linked with the 123LTO course grade. The table below shows my findings:

That's quite a mixed bag of results, with eight of the 25 combinations making a profit. However, in order to get a better ‘feel’ for the data I have grouped the 'today' course grade results into one.

The results at all Grade 1 courses combined are the worst, both from a strike rate and returns perspective. Horses racing at a Grade 3 course after a top three finish have done the best and have snuck into profit. It should be noted that the Grade 3 total of runners is the smallest... but there were still over 10,000 qualifiers from this eight-year time frame.

Having grouped the course data above in terms of course grade, it makes sense to do the same for the LTO course data:

This time we see slightly worse returns at either end of the spectrum, but there's nothing too significant to be gleaned from this grouping unfortunately.

My final piece of digging connected with the grading of courses idea was do some ‘rearranging’. My thinking was to create an up-in-course grade / down-in-course grade idea, similar to the one for class change or distance change. To that end, I subtracted the course grade from the LTO course grade to create a ‘difference’ figure. For example, a horse that raced at a Grade 4 course LTO and now racing at a Grade 1 track would have a figure of 3 (4 minus 1). Positive figures can be deemed ‘up in course grade’, negative figures ‘down in course grade’.

Here are the win strike rates:

This graph neatly shows how the change in grade of course affects the win strike rates. Those going from a lower grade course to a higher grade course (the positive figs) have won far less often than those going from a higher grade course to a lower grade one (the negative figures). This is to be expected of course but the correlation is still positive, and beautifully linear. Hopefully we will see a correlation with the BSP returns. Let’s take a look:

The worst return by some margin is for the largest ‘up in course grade’ figure of 4 (i.e. a horse moving from a 123 effort at a Grade 5 track last time to race at one of Ascot, Goodwood, Newmarket Rowley or York this time); with the second worst being the ‘up in course grade’ figure of 3. Those negative returns can be seen on the right hand side of the chart.

The best returns were with the biggest ‘down in course grade’ figure of 4 (i.e. a horse moving from a 123 effort at Ascot, Goodwood, Newmarket Rowley or York last time to race at a Grade 5 track this time). So, at either end of the spectrum we have something of potential use. Unfortunately, the values in between do not show a clear pattern, which is slightly frustrating given the earlier vastly differing strike rates.

It again emphasises that the betting market is so very efficient and not easy to get the better of, despite the huge amount of data collating and crunching one does!

It is time to wind up this piece now. Sometimes, despite how well thought out a research project is, we don't always get the findings we were expecting or hoping for. The second half of this article has been a little like that; I was hoping to find more positive or negative angles using the ideas connected with my grading of courses but little came to light.

The most eye-catching elements might be the top and bottom 20 strike rate tables I shared at the beginning, though it's definitely also worth looking out for any horses dropping from a placed effort at one of the Grade 1 tracks into a low grade fixture. For anyone interested in all of the 'today' course to 123LTO course data I have, I am happy to share it. There were too many combinations to fit in this article (469 with 80+ runners, to be precise). Please just post your request in the comments.

My parting shot is that perhaps I need to re-think the 123LTO course to 'today' course idea by incorporating and classifying the course configuration. What I mean by that is whether the course is, for instance, ‘stiff’ or ‘tight’ or ‘galloping’ etc. The only issue with that is some courses will fit more than one course type ‘descriptor’. Hmm, I need to get my thinking cap on and come up with a plan. If I find a good way to do this I will share my findings in a subsequent article later in the season.

- DR

Comparing Starting Price with Betfair SP

8 April 2025/in Dave Renham/by Dave Renham

Last week Geegeez added Betfair Starting Price (BSP) to numerous areas of the site, writes Dave Renham. For me as a researcher and writer this is fantastic news. As we know, most punters do not bet at Industry SP (ISP) anymore. Some still stick solely with traditional bookmakers, but to improve their bottom line they will use Best Odds Guaranteed (BOG) where available, as well as early or ante post prices. Some will use the Exchanges, primarily Betfair, with BSP one option to be utilised. Others will try and exploit both the bookmakers and the Exchanges to hopefully gain maximum advantage.

In my personal betting I use BSP for around 40% of all my horse racing win bets, so when researching ideas it is very useful for me to see the BSP profit and loss column.

For this article I am going to examine data from UK racing over the last two full years (2023 and 2024). In the overall findings I will be including all race codes, i.e. flat, all-weather (AW) and National Hunt (NH). For BSP profits/losses I will be using 2% commission which is what we, at Geegeez, are using in our calculations.

When we compare ISP to BSP there is no contest – BSP wins hands down. To give an example, if we look at horses priced between 5/1 (6.0) and 6/1 (7.0) combining all race codes in the UK over the designated time frame we see the following:

To BSP a profit of £226.24 to £1 level stakes would have been achieved compared with an £1826 loss if backing to Industry SP. That is some eye-watering difference. Just imagine if we were using £20 stakes and not £1 ones!

Before delving into BSP in more detail I do want to talk very quickly about Best Odds Guaranteed (BOG). This option is still available with 12 main bookmakers on most UK races each day. Essentially this option is a no brainer for those betting with standard bookies. When using BOG, it gives punters the chance to take an early price, but if the starting price (SP) is higher, we get paid out at the higher odds. I am in the process of doing some initial research into potential BOG strategies and at this early stage it seems there is a sweet spot in terms of price – or at least the early price. Early prices around the 5/1 (6.0) to 7/1 (8.0) mark seem to offer the best value long term for BOG bettors. I will need to dig much deeper, but I am fairly confident I am in the right early price ballpark to utilise BOG to its max.

There can be issues though with BOG betting such as limits on stakes and occasionally the BOG option will not be available – normally for those people that are winning consistently using it. Working out potential BOG profit and loss figures based on past prices is not always clearcut because of these aforementioned issues. However, I do hope to be sharing some research on this at some point in the future.

Back to main focus of this piece. Earlier I mentioned that the calculations in terms of Betfair commission across the Geegeez site is 2%. For those who currently 5% and are regular bettors on the machine, then log in to your Betfair account and choose the 'Basic' plan on this page. Once this is done, you'll pay 2% only on net winning Exchange bets.

Paying 2% commission on winning bets rather than 5% commission is clearly preferably but I want to illustrate this numerically by using real data to see what a difference it can make long term. Let me compare the BSP profits (to £1 level stakes) of all horses that had an Industry Starting Price of 13/2 in terms of 2% commission versus 5% commission.

Over this two-year period the difference would have been £116.89. To £20 stakes the difference would be a very significant £2337.80. In the table below I will share some other ISPs in terms of this 2% v 5% difference:

A palpable difference across the board and, for 8/1 shots, as with the 13/2 shots, a loss with 5% commission has been turned into a healthy profit when applying a 2% commission.

My next piece of digging is in connection with the ISP and the average BSP price for that specific price – comparing the difference between the two. The first graph compares a selection of ISPs under 10/1 (11.0) with their BSP average counterparts. The graph uses decimal odds for ease of comparison:

Hence an Even money shot at ISP (2.0) has paid 2.14 on average at BSP (before commission); a 9/1 (10.0) shot has averaged at 12.61. It is just another indication of why ISP on its own is outdated for any serious punter.

Let me now look at a selection of some bigger ISP prices ranging from 11.0 (10/1) to 41.0 (40/1):

As the ISP prices goes to 20/1 (21.0) or bigger the gap to BSP starts to increase considerably. Once we get to 40/1 (41.0) the BSP average is moving closer to double that of ISP. I have always been a fan of backing big-priced outsiders because if I can find a horse with a percentage win chance akin to its likely ISP then I have excellent value.

My next comparison is with average BSP prices for handicaps versus non-handicaps at various ISPs. I wonder how many of us have assumed the average prices would be basically identical – well, within a hundredth of a point or two over two years’ worth of day at least. This is indeed the case for an ISP of Evens (2.0) where the difference is 0.02 of a point (2.13 versus 2.15), but as the prices get bigger, the gaps between the two start to increase. Once again, I’ll share two graphs, the first focusing on an ISP of 9/1 (10.0) or less:

The average non-handicap BSP is higher across the board than the handicap one with the difference between the two gradually increasing as the prices get higher.

Now I would like to examine the bigger prices:

With the bigger prices we see a similar pattern with the non-handicap BSP averages higher than the handicap ones and the gaps between the two once again increase as the ISPs get bigger. Looking at the ISP 40/1 (41.0) comparison we can see the gap between the two prices is close to 10 points (77.34 versus 67.87).

I believe the reason we have these differences, and such differences are more pertinent to these bigger prices, is due to the shape of some non-handicap markets. I am talking primarily about non-handicap markets with a very short-priced favourite. Here is an example of such a race. It was the 6.30 at Southwell on 8^th October 2024. It was a 5 runner 2yo novice race (non-handicap). Here is the result with the relevant ISPs and BSPs:

With a very short odds favourite in Shah at 2/13 (1.15) if we look at all the other BSP prices they are bigger than their non-handicap average price. The table below helps to illustrate this further:

Not only was the BSP comfortably above the average for all four of these runners, in the case of the two biggest priced runners, Something Splendid and Divot, the difference was huge (80 v 47.36 and 328 v 142.53). Of course, such huge outsiders in a race with a super-hot jolly win very rarely but when they do the BSP rewards handsomely.

In my two-year research time frame, there have been 64 races with a favourite priced 2/13 or shorter and 61 of those were non-handicap races. Therefore, having this type of market shape for handicaps is extremely uncommon. Hence, these higher priced outliers in terms of BSP will occur much more in non-handicaps, helping to push the average BSP upwards. Now my guess is that this is not the only reason for the big differences between the average BSP prices of bigger priced runners in non-handicaps versus handicaps, but more on that later.

Continuing the bigger priced theme as well as comparing handicap results to non-handicap ones, let me look at some more BSP data comparing strike rates and BSP returns. In the table below I have split ISPs into three groups – prices from 33/1 to 50/1 (34.0 to 51.0), 66/1 to 80/1 (67.0 to 81.0) and 100/1+ (101.0+).

When looking at horses priced 34.0 to 51.01 the win strike rates imply a small edge to non-handicappers and the returns show a clear advantage to that cohort, too. Once we get to 67.0 to 80.0 though, the strike rates have flip-flopped with handicappers winning nearly twice as often (albeit still very rarely) and with a huge disparity in the ROIs of around 35p in the £ in favour of said handicappers. This disparity just gets bigger once we hit those 101.0 or bigger shots. Although these 101.0+ handicappers have won on average just one race in every 175 they have seen a return of over 60p in the £ to BSP. Non-handicappers in this price bracket have won on average one race in 833 losing 45p in the £.

There are two reasons for sharing this handicap / non-handicap BSP data for bigger price runners, and I would like to clarify that it is not to suggest that we back all 100/1+ handicappers! The first reason is to show that with bigger priced runners the type of race does make a difference, as does the ISP or the likely ISP, in terms of win chance, likely BSP and potential returns. Secondly, this table might help to explain an additional reason for something I was discussing earlier in relation to why the average price of outsiders on Betfair is bigger for non-handicappers than for handicappers.

At this juncture it should be noted that BSP does not beat ISP 100% of the time. However, a BSP ‘win’ does occur 97.5% of the time (and therefore ISP has ‘won’ 2.5% of the time). It is this 2.5% subset of runners I want to look at next.

Given that we know the Betfair market is about as efficient as a betting market can get, when the ISP is higher than its Betfair equivalent, the expectation would be that this industry price ought to be very close to its ‘true’ price.

4486 horses had an ISP higher than their BSP during the two years in review, and if we had backed them at ISP, a profit of £241.69 (ROI +5.4%) would have been achieved. To BSP these runners would have lost us £77.63 (ROI -1.7%).

Of course, we don’t know the BSP or the ISP before the race starts, so you’d be forgiven for thinking this is a pointless piece of intel. However, for those punters who back late on Betfair, literally seconds before the ‘off’, knowing about this unusual state of affairs could offer a potential strategy.

The prices available very late on Betfair are going to be close to the eventual BSP, especially at the front end of the market. Technically, then, a strategy that may offer an edge would be to have both a Betfair live screen along with a couple of bookmaker live screens open on your computer, coupled with a live racing feed. If, a few seconds before the start of the race, the live Betfair price on a horse is lower than an available live bookmaker price, then back the horse with the bookmaker.

The chances are, regardless of the final ISP, that this will beat BSP with the price taken, or at least effectively beaten it after commission is considered. Not all of us have the time to watch live races on a daily basis and employ such a strategy but for those who do, I would be interested to see how this idea panned out over time.

Finally in this article, I want to examine the results when we use a BSP to ISP odds ratio. What I mean by that is if a horse has a BSP of 3.0 and the ISP was 3.0 the ratio would 1.0. If the BSP was 9.8 and the ISP was 7.0 the ratio would be 1.4 (9.8/7.0). I wanted to see if we could find anything useful out of looking at such ratios. To do this I have used ranges for the ratio and the table below shows my findings:

As expected, the strike rates tend to move in a positive direction as we move down the groups. In terms of returns, horses that have a BSP/ISP ratio of 1.01 to 1.24 have offered the best value. This again helps to illustrate how efficient the Betfair market is, especially at the front end of the market.

That’s all for this week. Any price-based research has flaws because as I have stated earlier, we do not know pre-race what the ISP or BSP will be. However, this type of overview analysis is important to understand. For those who never or rarely bet on Betfair I hope this article is enlightening. For those who do, then there should be plenty of new information and stats to be aware of which have the potential to improve one’s bottom line.

- DR

Favourites on the Flat in April

31 March 2025/in Dave Renham/by Dave Renham

Two years ago, I wrote an article looking at some past races in the month of April, writes Dave Renham. At the beginning of that piece, which you can review here, I looked briefly at the performance of favourites. I established then that favourites at this early stage of the season seemed to have struggled a little when compared to other times of the year, but in terms of the stats shared I barely scratched the surface. And so, in this piece, I want to delve considerably deeper and cover a broad array of factors to give Geegeez readers the best possible overview of the ‘jolly’ at this time of the year.

Contents

Introduction

The article looks at favourites in turf flat racing only during the month of April and covers the period from 2018 to 2024 (there was no racing in April 2020 due to Covid). Profits and losses have been computed to Betfair Starting Price (BSP) with any winning commission accounted for in the calculations.

Let me start by sharing the overall figures for all favourites in April. For the record these include clear and joint favourites:

We see a strike rate of just under 30% with losses of between eight and nine pence in the £. Let’s see how these results stack up compared with other months of the year.

Monthly Comparison of Favourite Performance

Firstly, let’s compare the win strike rates (I have ignored March and November due to limited data):

As the graph shows April and October have the lowest strike rates while the remaining months all hit 32% and above. Part, but not all, of this is a function of field size, with the average UK flat turf field being 8.51 runners in July compared with 9.35 in April.

How do the profit and loss figures compare in terms of returns? Let’s see:

The returns for April favourites are comfortably the worst full month of the season, with at the other end of the spectrum July showing a small profit; May and September are within a smidge of breaking even. The A/E indices paint a similar picture as the table shows:

As can be seen, the April figure is the only one below 0.90 showing positive correlation with the ROI%s. Meanwhile, the highest, July (0.97), also correlates well. When I compared the PRB (Percentage of Rivals Beaten) figures for flat turf favourites between April and July, April scored 0.71, July 0.74.

Flat Turf Fav Performance in April by Race type

The next port of call is to examine race types. I have decided to split these into age group race types. Hence, I am comparing 2yo non-handicaps with 3yo only non-handicaps, mixed age non-handicaps, 3yo handicaps and mixed age handicaps. For mixed age races I have combined 3yo+, 4yo+, 3-4yo, and any other such derivative. [There are no 2yo handicaps in April.]

The non-handicap figures are quite similar in terms of returns and A/E indices, but the handicap results are poles apart. 3yo only handicap favourites have performed well above expectations, making a tidy profit with excellent figures across the board. Backing them would have secured a BSP in all years bar one.

Handicaps for mixed age runners in contrast have seen the poorest results by some way. The vast majority of these races are 4yo+ contests at this time of year and, intriguingly, horses aged 4 have the worst record when starting as the market leader. 4yo favourites in 4yo+ handicaps have won just 21.1% of the time (86 wins from 408) for a BSP loss of £103.19 (ROI -25.3%); A/E 0.71.

Flat Turf Fav Performance in April by Race Class

I want now to see if the class of race makes any difference at this time of the year. Now, the majority of races in April are Class 4 or lower, but it is still worth sharing the splits:

Class 2 and 3 races have been the poorest for the jollies albeit from modest sample sizes. Interestingly, non-handicap Class 2 and 3 events have been the worst of all for favourites with losses of nearly 26 pence in the £. In terms of value, Class 6 races have offered favourites the best returns although we are still in the negative zone. In these contests backing favourites would have lost just under 3 pence for every £1 staked.

Flat Turf Fav Performance in April by Sex

The sex of a horse is something I always check when researching any area, and it transpires that there is quite a difference in performance between male and female favourites at this time of the year. Female favourites have won nearly 3% more races than male favourites, and losses for females stand at 2p in the £ compared with 10p for males. There is a big difference, too, in their A/E indices as the bar chart below shows:

Female favourites have been far better value than their male counterparts in April going back to 2018. Indeed, in mixed sex races female market leaders have edged into the black thanks to 79 wins from 251 runners (SR 31.3%) for a small £5.30 profit (ROI +2.1%); A/E 1.02.

Flat Turf Fav Performance in April by Days since last run

This is the first of the last time out (LTO) factors I plan to look at. Due to how the numbers have panned out I divided runners into three distinct groups: horses that are returning to the track within a month (1 to 30 days), horses that have been off the track for over a month but less than five months (31 to 150 days), and horses returning after five months or more (151 days+). These, granted somewhat arbitrary, splits make for interesting reading:

Horses that were off the track for five months or more (151+ days) and started favourite have performed the best by some considerable margin. Horses which were fit from a recent run (1-30 days) are next best, but their record - losing more than 10% at BSP - is modest at best. Runners returning to the racecourse after a break between 31 and 150 days have a quite dreadful record with losses not far off 30p in the £.

Focusing on the 151+ days cohort their record has been very good when contesting a handicap, winning 103 races from 353 (SR 28.9%) for a profit of £40.59 (ROI +11.5%).

They even made a fair profit to Industry SP of £23.72 (ROI +6.7%). Essentially, don’t be put off by any favourite returning to the track after a long break.

Flat Turf Fav Performance in April by LTO Race Code

I want to look at the splits now in connection with which race code the last run was be it turf flat, all-weather or National Hunt. Here are the findings:

There have not been many horses that have switched from a National Hunt race last time, but the small group of qualifiers made a profit. As regards a run on the turf (flat) or the all-weather LTO, clearly a turf run has been preferable. Turf and NH race last time out win rates are almost exactly the same whereas April turf favourites that ran on the AW last time won at a much lesser clip.

These data correlate to some extent to the DSLR (days since last run) data shared earlier because combining days off the track of 31 to 150 days with a run on the all-weather LTO produced these dismal findings for favourite backers – 58 wins from 249 (SR 23.3%) for a BSP loss of £74.57 (ROI -30%).

Flat Turf Favourite Performance in April by Day of the week

I am moving away from LTO factors for this next area to share my findings for favourites on different days of the week. We know the quality of meetings varies from day to day so will that make any difference to the performance of favourites during April? Below is a graph illustrating the Return on Investment percentages across the seven days:

Traditionally, racing at the beginning of the week (Monday and Tuesday) offers more modest fare and favourites have really struggled at this time of year on these two days. Contrast that to the performance of the market leaders on what is usually the most competitive day of the week, Saturday where such runners have made a profit of close to 10 pence in the £.

Flat Turf Fav Performance in April by Class Change

My next stop is to look at favourites and class change. Let’s go straight to the splits:

Favourites raised in grade have the best record, with the highest win rate and A/E index, as well as edging into profit... just. Favourites dropped in class have produced the poorest returns and the lowest A/E index. As a whole, these stats suggest strongly that we should prefer to back a favourite that is taking a step up in class.

Flat Turf Fav Performance in April by Position LTO

A look now at where a horse finished on its last run. I have combined LTO positions to give better sample sizes:

We have the usual sliding scale in terms of win strike rate as we would expect. Last time winners that started favourite performed above the norm and in fact made a small profit. At the other end of the spectrum favourites that finished sixth or worse LTO have performed quite poorly.

Earlier it was noted that female horses had performed well when favourite. If we look at female favourites that won LTO we see some excellent figures – 39 wins from 98 (SR 39.8%) for a healthy profit of £23.88 (ROI +24.3%). One final LTO winning stat links back to class change and horses upped in class after a victory have produced a strike rate of close to 38% (81 wins from 214) and a profit of £36.49 (ROI +17.1%).

Flat Turf Fav Performance in April by Going

A look at underfoot conditions now. I have split the favourite results into two looking at good or softer conditions versus good or firmer. There is a slight difference between the two as the table shows:

It appears that favourites in April have an improved winning chance with firmer conditions underfoot. Such runners are ahead in all three of the main metrics of strike rate, ROI% and A/E index.

Flat Turf Fav Performance in April by Market position Early Morning Odds

In some recent articles I have looked at market movements combining Early odds, Opening Show and SP. Here I want to examine favouritism status in the Early Morning markets for this April group of SP favourites. I have split these early morning market positions into three: horses that were clear favourite when the early odds came out, horses that were joint favourites and horses that were not favourite. Here is what I found:

56% of SP favourites were also clear favourite in the early morning odds published by the bookmakers. However, despite predictably enjoying the best strike rate they still returned losses of close to 11p in the £. Joint favourites early had the worst record, albeit from a smallish sample; while horses that became favourite later in the day (the original ‘not favourite’ group) provided the best outcome from a return’s perspective (they also had the highest A/E index).

Flat Turf Fav Performance in April by Trainer

The last main area I want to look at is trainers, although sample sizes for the majority of them is too small to glean anything useful. Therefore, I have restricted the list to those that have saddled at least 40 UK turf flat favourites in the month of April between 2018 and 2024. The list is ordered alphabetically:

Charlie Appleby and Roger Varian stand out based on all the metrics. Both have produced returns in excess of 20p in the £ and this is impressive. The Gosden stable and David O’Meara have also nudged into profit. On the other side of the coin, Andrew Balding and Kevin Ryan struggled relatively.

Conclusions

Despite turf flat favourites performing below the norm in April there have been several positive findings. Female favourites in mixed sex races, favourites in 3yo handicaps, favourites upped in class, LTO winners sent off favourite, and favourites off the track for five months or more have all produced positive returns.

There have also been some strong negatives which hopefully will help steer us away from potentially bad value favourites.

I have one more positive stat to share and that relates to horses that were favourite last time out. This cohort has won 196 races from 511 qualifiers (SR 38.4%) for a profit of £62.65 (ROI +12.3%); A/E 1.06.

For those of us that will be backing some favourites this month I am hopeful the above will point us in the right direction.

- DR

Early Flat Season Trainer Form

26 March 2025/in Dave Renham/by Dave Renham

After the thrills and many spills of the Cheltenham Festival attention now turns to the start of the turf flat season, writes Dave Renham. Saturday 29^th March is the starting date this year and the crowds will descend on Doncaster for a card that includes the first big handicap of the season, the Lincoln. In this article I am going to look at some early season trainer form and trends. Data are taken from 2019 to 2025, although in 2020 there was no flat racing in the early part of the season due to Covid.

Contents

Selected Trainers: First Ten Runs

We see in the racing press plenty of stats connected with a trainer’s recent form, be it the last seven, 14 or 30 days, or their last ‘x’ number of runs. For some punters this information is really important and forms an integral part of their selection process. With that in mind, one question I am keen to address in this article is connected with recent trainer form. I want to try and establish whether the first few runs of the season from a particular stable is indicative of how their runners perform up to the end of April. Also, I will be looking at whether a similar level of performance each year is achieved by trainers up to the end of the first full month of the season. I just would like to clarify that the data shared in this piece has been collated starting from the day of the first turf flat meeting through to the 30^th April in each season.

In order to make this piece manageable I have decided to focus on a selected group of trainers who tend to have a good number of entries in the early weeks of the season. This includes some of the big guns, namely Charlie Appleby, William Haggas and John/Thady Gosden.

My starting point was to work out the PRB (Percentage of Rivals Beaten) figures for each trainer over their first ten runs of each season. I felt that using the PRBs would be the most accurate way of determining how well a stable was performing over those ten runs. Clearly, I could have used win strike rate but over such a small sample size we could potentially get a blurred picture of how well the horses are actually running. Here are my findings.

N.B. I have combined the figures for the Johnston stable although of course Charlie Johnston is now in sole charge:

Early Season Trainer Form: Selected trainers' PRB figures

Before doing a comparison with their records up to the end of April for each year, the table does highlight that we cannot guarantee exactly how well each stable will get out of the blocks each season. Taking Richard Hannon as one example, in 2023 his first ten runners of the turf season hit a PRB of only 0.46, but last year in 2024 it was up at a huge 0.83. Likewise, the Johnston stable has seen wide variances with three PRBs below 0.35 and two hitting 0.65 and above. Now of course ten runs is a small sample but by using PRBs it does give us a better idea of the very early form of a specific stable compared with other metrics. I believe the numbers shared in this table also help to highlight that each year is different and even if stables traditionally start the season quickly, there will be years that for whatever reason things will progress more slowly. And of course, vice versa.

Selected Trainers: To End of April

Let's now take a look at the annual PRBs for each trainer covering the start of the turf flat up to the end of April. Essentially, for most years this equates to roughly the first five weeks of the season.

Early season trainer form: up to end April annually

As might be expected, fluctuations year by year in the PRBs are now less pronounced due to the much bigger datasets, although two of Charlie Appleby’s figures differ quite markedly - from 0.81 in 2022 down to 0.63 in 2024. Likewise, the Gosden stable saw a big difference between their 2019 figure of 0.71 and their 2023 one of 0.51.

Now that we have these two sets of figures we can try to address the earlier question of whether the first few runs of the season from a particular yard are indicative of how their runners will perform up to the end of April. In order to do this, I have picked out some of the trainers to analyse in more detail.

Specific Trainers: Early Season Form

Charlie Appleby

If we look at Charlie Appleby’s performance with his first ten runners in 2019, 2022 and 2024 we can see he has quite well aligned PRB figures (0.62, 0.64 and 0.66). In 2019 and 2024 he maintained a similar level of performance up to the end of April hitting 0.66 and 0.63. However, in 2022, his PRB figure for the longer timeframe soared to 0.81. That year he had 23 winners from 55 runners up to April 30^th equating to a strike rate of just under 42%. From those similar starting PRBs in 2019 and 2024 he managed a longer-term strike rate of 29.2% and 29% respectively. It is difficult to say why those early five or so weeks of 2022 panned out so well for the stable compared with 2019 and 2024 when they started off in the same vein. It perhaps underlines how challenging it can be to predict future trainer form based on a smallish sample of runs.

Mick Appleby

Next for the microscope is Mick Appleby. The graph below shows the comparison:

Mick Appleby: early season form, 2019-2024

The graph shows that Appleby has been consistent in terms of overall performance in the weeks up to April 30^th (the orange line) - four of the five years saw PRB figures within a very small band ranging from 0.44 to 0.46. In 2022 he did have a better overall start to the season hitting 0.53 over those first few weeks, and that year he had started fast with a 0.63 figure for his first ten runners. The 2023 season saw an even better start with a 0.66 10-run figure, but that form tailed off quickly ending up at 0.46 for the longer time frame. Looking at this data tells me that the first ten runs of the year for Mick Appleby would not necessarily have given us a good guide to how the next few weeks would have panned out for his runners.

Going back to his PRB figures for all runs up to 30^th April, despite having similar ones, the correlation with the win strike rates is not completely ‘positive’ as the graph below shows:

Mick Appleby: early season win strike rate comparison

Yes, the best year was 2022, (16.1%), which correlates with the highest PRB figure of 0.53, but there is a big variance between 2019’s strike rate of 14.3% compared with 2023’s 3.2% figure. This is despite having very similar PRB figures in those two years (0.44 and 0.46 respectively).

As with all metrics, any single one does not necessarily give us the best picture. Clearly in 2019 and 2023 the Appleby runners were generally running at the same level overall – the PRB figures show that. However, in terms of winning races 2019 saw many more winners than 2023.

This type of number crunching is an excellent reminder of why racing can be difficult to profit from. Let’s imagine for example we back 20 horses to win in one month, if all of them run really well but all finish second, we still would have lost all 20 bets.

Andrew Balding

Next is Andrew Balding. Again, I have graphed the comparison between the PRB of the first ten runners with that of all runners to the end of April each year.

Andrew Balding early season form: comparison of first 10 runs with all to end April

2021, 2022 and 2023 mirrored each other with both the 10-run PRBs and the all runs to end of April PRBs very close together. In 2019 and 2024 we saw a similar pattern, with the stable flying out of the blocks in those first 10 runs and then slipping back to more normalised figures based on a larger sample.

When looking at those early weeks of the season up to the end of April, Balding does tend to perform at a similar level year on year. If we look at his win strike rate from the start of the season up to the end of April, we can see that in four of the five years they were between 17 and 19%:

There is positive correlation between the PRB figures and the win strike rate in those four years. We saw earlier with Mick Appleby that we don’t always get that positive correlation, and for Balding the 2022 figures paint a similar story. That year saw a lower strike rate despite a similar PRB figure to other years. This highlights once again why it is a good idea, where possible, to look at more than one metric when analysing a set of results in order to get a broader and better overview.

Tim Easterby

Tim Easterby has a lot of runners but his overall strike rate year on year is quite low, both early in the season and taking the season as a whole. Hence his first 10-run PRB figures are the lowest of the trainers mentioned taking the five years as a whole. 2022 saw a poorer start than usual but, by the end of April, he had pulled back to very similar five-week figures as achieved in other years.

Looking at his PRBs for those early weeks up to the end of April, we can see that there is only 0.04 between the highest and lowest ones. Essentially, at the beginning of the season, Easterby has followed a similar pattern every year with similar outcomes. Not surprisingly his win strike rate up to the end of April each year has been low as the table shows:

Tim Easterby early season win strike rate

Personally, I rarely back Tim Easterby horses even if they appear to have ticks in several boxes. For me, finding good value in his team is tricky. On the plus side, his patterns of performance rarely surprise us.

William Haggas

William Haggas has had very consistent longer-term PRB figures (up to the end of April) ranging from 0.60 to 0.67 over the five different years. His PRBs for the first ten runs are more varied as we would expect given the smaller sample size. However, it seems that, year on year, runners from the Haggas stable perform in a similar fashion. Again though, the win percentages up to the 30^th of April have varied much more as the table shows:

William Haggas early season metrics

As we can see, the two highest PRB figures of 0.67 in 2019 and 0.64 in 2023 did not produce the two highest win rates. In fact, they produced the lowest win rates by some margin. 2019 was definitely unlucky for Haggas in those first few weeks as they had 12 second places from their 42 runners that year. Against that, Haggas had only six winners hence the 14.3% strike rate. We talk about luck in racing, and regardless of how good a punter one is, luck and variance are ever-present, sometimes massively.

I would not worry too much about what sort of numbers Haggas posts after his first ten runners this season. We can be fairly confident that his team over the first month or so will run to a similar level to previous years. Whether they win at around 27% or 14% I cannot say, but for readers that back any of his, let’s hope it is nearer 27!

Richard Hannon

For Richard Hannon I want to compare the two sets of PRB figures side by side as I did for Mick Appleby and Andrew Balding.

Richard Hannon early season PRB figures

The orange line represents the longer-term figures up to the end of April and, aside from the 0.47 figure for 2022, the rest lie between 0.51 and 0.59 showing that Hannon's runners perform at roughly the same type of level at this stage of the season year on year.

What I find interesting is the difference between the first 10-run figures for 2023 and 2024, which was huge. 2024 was his best start at a massive 0.83 PRB, 2023 was his worst at just 0.46. However, by the end of the first month although 2024 ended up ‘better’ in PRB terms, the gap was quite small at 0.06 (0.57 v 0.51). Indeed, looking at the win percentages for these two years there was less than 2% in it. 2023 saw a 10%-win rate, 2024 stood at 11.8%.

This is another reminder that looking at a handful of races may not be as important or as useful as some punters/pundits may think; and I am not just talking about the first ten starts of the year. It is essentially the same thing when looking at any 7-day trainer form snapshot throughout the season when a trainer has had ten runners or so during that period. Is that really a reliable enough sample on which to judge how the next few weeks are going to go for the yard in question?

Charlie Johnston

The final yard I want to look in more detail at is that of Charlie Johnston (and its recent incarnations), formerly run solely by father Mark, then by Mark and his son Charlie, and since 2023 by Charlie on his own. Here are the two sets of PRBs:

Charlie Johnston / Johnston yard early season form

I mentioned earlier the huge variances in their opening 10-run figures (the blue line), but despite that the longer term PRBs are all in the same ballpark lying between 0.50 and 0.57. I don’t think the performance of the first ten runners will be that relevant again this year when it comes to predicting what will happen in the subsequent weeks to the end of April. However, we can be fairly sure how they will perform over the longer five-week time frame.

Selected Trainers: Win Strike Rates to end April Annually

To finish off let me share the win strike rates for all trainers for each of the five years based on their runners from the start of the turf season to the end of April:

Selected trainers: early season win strike rates 2019-2024

These percentages can vary markedly year on year, as I meantioned earlier when looking at the performance of the Haggas yard. Luck plays its part for all trainers every year, be it good luck or bad. A few bobs of the head in a finish can make a big difference to the win rate; hopefully Geegeez members will be on the right end of tight finishes more often than not!

That is almost it for this week but for before closing I will put my head on the block and predict the win strike rates and PRBs for all of the stables mentioned in this article from the start of the Doncaster Lincoln meeting this year to the end of April. Here goes:

Projected early season win percent and PRB figures for selected trainers

Hopefully, most of these projections will be close to their mark.

Until next time,

- DR

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Newmarket July Meeting – a look at the past 10 years

Newmarket July Meeting: Market Rank (Exchange)

Newmarket July Meeting: Price movement

Newmarket July Meeting: Age in 3yo+ & 4yo+ races

Newmarket July Meeting : Recent form

Newmarket July Meeting: Course LTO

Newmarket July Meeting: Course form

Newmarket July Meeting: Trainers

Newmarket July Meeting: Key Positives

Using Tix for Jackpots, Placepots, Quadpots & the Scoop 6, primarily focusing on Placepots

Tote Bets: A Quick Intro

Playing Placepots the Traditional Way

One line 'Hail Mary'

The '2x2'

Variable perms

Introducing Tix

Tix Selection Flexibility

Tix Staking Flexibility

Wider Coverage

Example Tix Play: Royal Ascot

What if?

Summary

Introduction

Number of race runners

Race Class

Courses by Jockey

David Allan

Connor Beasley

William Buick

Hollie Doyle

Joe Fanning

Oisin Murphy

Saffie Osborne

Rossa Ryan

Introduction

Royal Ascot Group 1s by Market Rank

Group 1 Favourites at Royal Ascot

Royal Ascot Group 1s: Top 3 Market Ranks

Royal Ascot Group 1s by Last Time Out (LTO) Position

Royal Ascot Group 1s by Last Time Out (LTO) Race Class

Royal Ascot Group 1s by Days Since Last Run (DSLR)

Royal Ascot Group 1 Trainers

Summary

Introduction

Top Jockeys' PRB: Overall

Top Jockeys' PRB: ISP 6/4 or shorter

Top Jockeys' PRB: ISP 12/1 to 20/1

Top Jockeys' PRB by Price Range

Top Jockeys' PRB: All-Round Performance

Top Jockeys: Other Metrics

Conclusions

Introduction

SR Ratings by Win Strike Rate and P/L

Combining SR Top Rated with Pace Rank Top Rated

Performance of the Lowest Rated on Pace and SR

Top Three Rated on Pace and SR by Handicap Age Restriction

Top Three Rated on Pace and SR by Selected Courses: Positive

Composite Ranking Performance

Top Rated on SR and 15 or 16 Pace Total

Top Three Rated on SR and 15 or 16 Pace Total

Top Three Rated on SR and Pace Rank, ISP 12/1 or shorter

Introduction

Pace Rating Rank

Pace Rating Total

Pace Ratings at Different Courses

Top Rated by Age Group

Sires: All Two-Year-Old Races

Sires: Two-Year-Old Races by Distance

Sires: Two-Year-Old Races by Going

Sires: Two-Year-Old Races by Gender

Sires: Two-Year-Old Races when Betfair Market Leader

All TC2 Runners

TC2 Runners Sent Off Exchange Favourite

TC2 Runners Sent Off Exchange 2nd or 3rd Fav

TC2 by Last Time Out Finishing Position

TC2 by Gender

TC2: Trainer Angles

Trainers: TC1 vs TC2

All Trainer Changes

TC2 Runners Sent Off Exchange 2^nd or 3^rd Fav