‘SR’ Ratings on the Flat (Turf)

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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 2nd 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.

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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

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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

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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 8th 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.

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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

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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.

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

/in /by

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 29th 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.

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 30th 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

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

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 30th 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

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 30th (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 30th 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

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

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

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 30th of April have varied much more as the table shows:

 

William Haggas early season metrics

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

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

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

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

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

 

Looking at Past Cheltenham Festival Trends

/in , /by

As I am penning this piece, the excitement for the upcoming Cheltenham Festival has gone up a further notch with the big days less than a week away, writes Dave Renham. In this article I will analyse some past Cheltenham race trends. Here on geegeez.co.uk we get specific race trends shared all year round with all the big races covered by Andy Newton. The Cheltenham Festival trends are available already for each day and can be accessed here.

Introduction

From 2007 to 2013 I wrote a weekly column on big race trends in the Racing & Football Outlook and over time got an excellent feel for which races suited past trends. Past race trends can be very good indicators of how a future race is likely pan out, and this is usually the case with the Cheltenham Festival. Many people use trends to help narrow down the field making the eventual selection process less daunting. If we can reasonably confidently eliminate say 50% of the field, then it drastically increases our chances of success. Obviously, there will be times when the race trends are ‘bucked’ where the winner does not fit the typical winner’s profile, but fortunately for many Cheltenham races this happens quite rarely.

For the main part of this piece, I will examine the last 20 renewals of the Gold Cup. I am going to first examine the ten Gold Cups held between 2005 and 2014 and then compare those findings with the Gold Cups from 2015 to 2024. After this I will be in a position to hopefully pick out the very strongest trends. I will also highlight some of the strongest trends from three other races at the meeting at the backend of the article.

Cheltenham Gold Cup Trends

So let's look at the blue riband race, the Gold Cup. From 2005 to 2014 these were the most powerful trends:

2005-2014 Gold Cup Trends

Market Factors: 2005-14

5 winning favourites from 10.

9 out of 10 winners came from the top three in the betting.

Horses with an SP of 8/1 or shorter produced 9 winners from 36 runners (25%); horses priced 17/2 or bigger produced one winner from 107 (0.9%).

 

Last Race Factors: 2005-14

7 of the 10 winners won last time out (LTO). Those seven winners came from 44 qualifiers (15.9%); horses that finished 2nd or worse LTO provided three winners from 99 (3%).

All of the 10 winners came from one of three tracks – Leopardstown, Newbury or Kempton. This equates to 10 wins from 65 (15.4%). Other courses combined were 0/78 (0%).

All of the 10 winners were priced 8/1 or shorter LTO. Those 10 wins came from 103 runners (9.7%). Those priced 17/2 or bigger were 0 wins from 40 (0%).

Racing in a Grade 1 race LTO produced seven winners from 47 (14.9%). Those racing in Grade 2 or lower were three wins from 96 (3.1%).

 

Other Factors: 2005-14

Horses that had won previously at the Cheltenham Festival produced five winners from 37 (13.5%). Those with no previous Festival win were 5/106 (SR 4.7%).

Horses with an Official Rating of 166 or more produced seven winners from 37 (18.9%); those rated 165 or less were 3/96 (3.1%).

In terms of age, 10yos or older were 0 from 40 (0%). Nine of the winners came from horses aged 7, 8 or 9.

Horses that had previously won at least once that season produced eight wins from 83 qualifiers (9.6%). Horses that had not scored that season won 2/60 (3.3%).

 

Conclusion: 2005-14

During this ten-year time frame, the Gold Cup was dominated by the front end of the betting market. 2014 was the outlier with a 20/1 winner in Lord Windermere and placed runners at 16/1 and 14/1. A win LTO was a plus as was an OR of 166+. All the winners came from either Kempton, Newbury or Leopardstown and all the winners were priced 8/1 or shorter on their previous start.

It was also preferable to have raced in Grade 1 company LTO, to have previously won at the Festival and to have won that season. In terms of age, it was best to avoid horses aged 10 or older.

 

*

 

Let's now compare the data from 2005 to 2014 with that for the most recent ten-year period, 2015-2024.

2015-2024 Gold Cup Trends

Market Factors: 2015-24

5 winning favourites from 10.

Seven out of 10 winners came from the top three in the betting (nine came from the top four).

Horses with an SP of 8/1 or shorter produced eight winners from 40 runners (20%); horses priced 17/2 or bigger produced two winners from 88 (2.3%).

 

Last Race Factors: 2015-24

Eight of the 10 winners won LTO. Those eight winners came from 59 qualifiers (13.6%); horses that finished 2nd or worse LTO provided two winners from 69 (2.9%).

Five of the 10 winners raced at Leopardstown LTO from 42 qualifiers (11.9%); Newbury LTO produced two winners from 10 (20%). Kempton LTO runners produced 0 winners from 16 (0%). All other courses combined were three wins from 60 (5%).

All of the last 10 winners were priced 10/3 or shorter LTO. Those 10 wins came from 63 runners (15.9%). Those priced 17/2 or bigger were 0 wins from 65 (0%).

Racing in a Grade 1 race LTO produced five winners from 65 (7.7%). Those racing in Grade 2 or lower had five wins from 63 (7.9%).

 

Othere Factors: 2015-24

Horses that had won previously at the Cheltenham Festival produced five winners from 42 (11.9%). Those with no previous Festival win have scored five times from 86 (SR 5.8%).

Horses with an Official Rating of 166 or more produced eight winners from 65 (12.3%); those rated 165 or less were two from 63 (3.2%).

In terms of age, 10yos or older were 0 from 22 (0%). Nine of the winners came from horses aged 7 or 8.

Horses that had previously won at least once that season produced all ten wins from 90 qualifiers (11.1%). Horses that had not previously won that season won 0 from 38 (0%).

 

Conclusion: 2015-2024

During this ten-year time frame, this race was once again dominated by the front end of the betting market. Five wins for favourites and nine of the ten winners were priced 8/1 or shorter at SP. A win LTO was a plus as was an OR of 166+, while a run at Leopardstown or Newbury LTO could be seen as a positive.

Previous Festival winners comfortably outperformed non Festival winners, while a win that season was paramount with all ten winners having that stat. An even stronger positive stat was horses priced 100/30 or less LTO as they produced all the winners from roughly 50% of the runners. Less horses aged 10yo+ took part during this time frame but once again they drew a blank.

 

*

 

The Gold Cup Comparison

Overall, the vast majority of the key trends from 2005 to 2014 were seen again between 2015 and 2024. The race has been strongly dominated by the more fancied runners. That includes ten winning favourites during the past 20 years, and backing all favourites would have yielded a profit to SP of £14.12 (ROI +70.6%).

Below is a graph mapping the market rank of all 20 winners:

 

 

This is a neat way of illustrating the front end of market dominance. 18 of the 20 winners have come from the top four in the betting so it looks best to concentrate there.

15 of the last 20 winners won LTO – this is a strong positive that has ‘held’ during both ten-year periods. Essentially, a LTO winner has been five times more likely to win the Gold Cup than a horse that failed to win LTO. The graph below shows the A/E indices for different LTO positions:

 

 

These indices are another indication as to why a last day win before the Gold Cup has been a strong positive.

Sticking with last time out factors, all 20 winners were 8/1 or shorter on their most recent start with the last ten being 100/30 or shorter. Horses priced LTO 17/2 or bigger are 0 from 55. Now it is important to note that the vast majority of these 55 losers were decent prices come the big day, but only three of the 55 placed so if we are looking for a big priced placer, which can happen, the trends suggest that we should steer clear of this subset.

A previous Festival win has been a positive in both time frames. Overall, a previous Festival winner has been 2.4 times more likely to prevail in the Gold Cup when compared with runners who had not previously won at the Festival.

Based on the success of the top end of the betting markets it should come as no surprise that higher rated horses have been the most successful. An OR of 166 or more has produced 15 of the winners – this equates to 75% of the winners coming from around 38% of the total runners.

The age dynamic in terms of older horses (those aged 10 or older) has remained constant with these runners failing to register a win since Cool Dawn in 1998. In terms of horses aged nine or younger the last ten years has seen a slight switch with 7 and 8yos winning nine of the renewals.

A previous win that season was a positive in both time frames and that should be something to look out for again this year.

There are, however, a couple of 2005-2014 trends that did not repeat between 2015 and 2024. The first is those horses that raced in a Grade 1 event LTO. In the first ten years it seemed a strong positive if a horse ran in the highest class possible LTO. During that spell, they were roughly five times more likely to win than horses that raced in a Grade 2 or lower LTO. Fast forward to the latest ten-year period and there has been parity between both groups with no edge to horses that raced in a Grade 1 contest LTO.

The second pattern that did not repeat was the LTO Kempton one. This was a positive from 2005-2014, but actually since 2012 no LTO Kempton runner has gone on to win the Gold Cup. This is partly due to the fact that most runners in the past have come from the Boxing Day meeting at Kempton straight to the Festival. Nowadays more horses seem to fit in another run between these two big meetings.

One area I have yet to look at in terms of this race is trainers, and specifically Irish trainers versus British trainers. I will fix that now!

From 2005 to 2014, just 15.5% of the runners in the Gold Cup were trained in Ireland. In contrast, from 2015 to 2024 this has increased to 48.4%. The Irish trainers have dominantly outperformed British trainers over both time frames in terms of overall win rate. The graph below illustrates this:

 

 

Irish trainers have maintained their strike rate and with far more runners in the 2015–2024-time frame, it means they have provided the winner eight times in the last ten years (and all of the last six). British trainers have really struggled in recent years.

Splitting the data into two ten-year time frames for this race has shown that this is a race where many of the strong past trends remain the same. Generally, Grade 1 races for experienced horses are good races from a past trends perspective. However, as we have seen there has been a change in a couple of the trends highlighted between the two decades. As punters we need to be aware that this can happen and obviously react accordingly. Patterns change over time but the Gold Cup retains some very solid looking patterns which for this year’s renewal should help to narrow down the field to a small group of the most likely winners.

 

**

 

I now want to pick out a few other races and highlight the very strongest past trends based on the last 20 years.

Supreme Novices' Hurdle

This is the first race of the meeting, and the strongest trend is around LTO placing. Simply, we want to be looking for horses that won last time. They have provided 16 of the 20 winners from 145 runners for a break-even situation to SP (well a 48p profit to be precise). Horses that finished 2nd or worse LTO have won 4 races from 173 runners for a loss of £108.50 (ROI -62.7%).

Not only that, we have had consistency in both 10-year groups with eight LTO winners from 2005-2014 and eight from 2015-2024. The win & placed (Each Way) percentages also strongly favour the LTO winners’ group. They have been over three times more likely to finish in the first three than horses that failed to win LTO.

Sticking with the win & placed theme, the graph below shows the consistency of performance of LTO winners when tackling the Supreme. I have grouped the LTO winners in five-year batches or groups to show their win & placed percentages in each period.

 

 

The percentages have not fluctuated much with most five-year groups around the 30% mark. Clearly, for the Supreme Novices’ Hurdle, we should be focusing our attention on LTO winners. Of course, a non-LTO winner may be successful this year as was the case last year, when Slade Steel won the race. However, the LTO 1st stats/trends are strongly in our favour.

 

Champion Hurdle

The Champion hurdle is the highlight of the first day and one recent trend that stands out is concerned with unbeaten horses that season. All of the last ten winners fitted that profile, and there were only 18 horses that qualified under that rule going back to 2015. This equates to a 55.6%-win strike rate. In the previous ten years there were also 18 qualifiers, but only three won. Having said that, from 2005 to 2014 horses unbeaten in that season were still three times more likely to win compared to horses that had lost at least once in the season.

As with the Supreme, last day winners are far more likely to win than those that failed to win LTO, amassing 17 successes from 101 runners (16.8%), and an A/E index 1.01 for LTO winners, compared to 3 wins from 134 (2.2%), A/E 0.45 for non-winners. In terms of the ten-year splits, 2005-2014 saw seven wins for LTO winners, 2015-2004 saw all ten wins.

 

Albert Bartlett Novices' Hurdle

This staying novice event is run on Gold Cup day and has one trend that has shifted dramatically in the last ten years. Let us look at the last 20 winners and their SPs:

 

 

The table neatly shows the difference between the ten years from 2005 to 2014 and those from 2015 to 2024 when it comes to the winning SPs. In the first ten-year period (lower half of the table) eight of the ten winners were priced in single figures with four favourites prevailing. In the most recent ten-year period nine of the ten winners were double figure prices and no favourite won.

The profit and loss figures for single figure priced runners during the two-time frames could not be more contrasting:

 

 

This type of switch-up reminds us once more that patterns and trends can change and that we cannot solely put our faith in all trends from past races. As punters we need to be aware that many trends will remain constant while a handful will not. Being able to adapt is part of what helps to make a punter successful over time.

Also, we are dealing with a smallish number of past races which again can seem to make trends fluctuate from time to time, whereas sometimes it was simply that the pattern was coincidence in the first place: we need to use skill and judgement to decide what is a trend and what is an accident of fate. Looking for reasons to justify a trend is a very good starting point in that regard.

- DR

Specific Course/Distance Analysis: Lingfield 1m2f

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I am a great believer in specialising when it comes to betting on horse racing, writes Dave Renham. When I ran my tipping service back in the early 2000s, I focused solely on five- and six-furlong handicaps. At the time I was doing a huge amount of research into draw bias, and it was when there was still a strong edge to be had over some course and distance combinations.

 

Introduction

Draw biases tend to be more prevalent over shorter distances hence the 6f cut-off point in terms of my tips. Focusing on a specific pool of races also meant I got to know many of the horses inside out, as sprint handicappers tend to run regularly during the year. Therefore, when I began to analyse a race I would have a solid knowledge of many, if not all, of the horses. Over time I started to spot other key patterns which would aid my selection process.

In this article I am going to look at one specific all-weather course and distance (C&D), making a deep dive into the plethora of related facts and figures. One could argue that looking for patterns for races from a specific C&D is a type of trends-based approach; I would agree. Trends, as a route into the horse racing puzzle, is much more fashionable than it was 30 years ago. Now we see 10-year race trends regularly in newspapers, and of course they've recently been added to the racecards here on Geegeez (as well as editorially more long-term for the big races, thanks to Andy Newton's contributions).

As I said, at the beginning of this year a TRENDS tab was added to the racecards which displays a range of information about the most recent renewals of the relevant race. Obviously not all races go back ten years, but it is a really useful addition to an already outstanding racecard. Essentially, then, this article could be considered a C&D trends piece looking at hundreds of races rather than just ten.

I am going to focus on handicap races only, ignoring nurseries (two-year-old handicaps) with data taken from 2018 to 2024, seven years' worth. Profits will be calculated to Befair Starting Price (BSP) with returns adjusted for commission. Looking at the results from a specific course and distance should hopefully give us good insight and potentially an edge over fellow punters in such races. For this article, I have chosen Lingfield over 1m2f.

Choosing a C&D on the all-weather means we are guaranteed plenty of qualifying races each year and Lingfield still hosts such races in the summer alongside flat turf contests. Indeed, there are three planned AW meetings in June in the height of the turf season and probably a couple of meetings where turf and AW racing is combined at the course. One or more 1m2f handicaps occur at most meetings.

This 10-furlong trip at Lingfield is not one I have looked at in depth before, mainly due to the fact that personally I still focus on shorter distance races when betting ‘on the level’. So, let’s find out more!

 

Betting market

I'll start with the betting market. The prices shown are to Industry SP, and the splits are shown below:

 

 

The value has been with horses sent off at industry SP's of between 13/2 and 12/1 with a solid overall profit to BSP. In fact, this group also snuck into Industry SP profit, too, albeit only just. Shorter priced runners have performed quite poorly and, looking specifically at favourites, they have lost over 14p in the £ to BSP. That compares very badly against the average for all-weather favourites at all courses in handicaps which stands at just over 6p in the £ during this time frame.

If I adjust the price groups slightly to create fewer price bands, we can see more clearly where the ‘value’ has been on the following graph which tracks A/E indices:

 

 

The graph also helps to confirm the earlier table's findings whereby the bigger price runners (14/1 or bigger) have been exceptionally poor value.

 

Position Last Time Out

Let's now see if the finishing position last time out (LTO) has offered any useful pointers:

 

 

In the time frame from 2018 to 2024 horses that finished first or second LTO have a good record when racing over 1m2f at Lingfield. The strike rate for both LTO winners and LTO runners-up are above the norm, as are the A/E indices. For both of them to be in BSP profit is impressive. When analysing 1m2f handicaps at Lingfield it makes sense to give this subset of runners at least a second glance.

Sticking with LTO winners/runners-up, those that raced at Lingfield LTO have the highest strike rate, at 24.5% (61 wins from 249), showing a BSP profit of £37.62 (ROI +15.1%). These runners would have secured a profit in five of the seven years.

 

Course LTO

We have seen already that a LTO run at Lingfield was a plus if the horse finished in the first two on that prior start. So what about when we look at all horses? How do the stats for LTO course stack up? To give a fairer picture I have restricted the qualifiers to horses priced 12/1 or less. This avoids the BSP bottom line being potentially skewed by huge priced winners. The table below shows the splits:

 

 

No course stands out as a super negative for the LTO run. The LTO Newcastle and Southwell results have been good albeit from modest samples. It is not a surprise that the most runners in Lingfield 10f handicaps also ran at Lingfield last time out; however, for that cohort to be (marginally) profitable from over 600 qualifiers is noteworthy.

 

Sex of horse

Anybody who has read previous articles penned by me on all-weather racing will know that males tend to outperform females in this code from a win rate perspective. That is the case again here as the table below shows:

 

 

Despite the SR% edge though, female runners have provided better returns. However, this is mainly due to two winning fillies going in at BSP odds of 110.0 and 145.1. If we restrict the results as before to horses with an SP of 12/1 or shorter we see the following:

 

 

Males have outpointed their female counterparts across the board here with a higher win percentage, bigger profits and a much higher A/E index. All in all, I would prefer the horse I was backing to be male over this C&D. One final stat worth sharing before moving on is that females aged five or older have struggled even within this price bracket. They secured just 18 wins from 160 runners (SR 11.3%) for a BSP loss of £38.26 (ROI -23.9%).

 

Class change from last race

Let's next examine whether a change in the class of the race has made a difference. Below I share the win strike rates for each group: those who have dropped in class from LTO, those that are racing in the same class, and those that have been upped in class:

 

 

Horses that have been upped in class have the best strike rate by far and they also have the highest A/E index across the three groups at 1.02. Horses dropped in class have an A/E index of 0.90, while those racing in the same class are at 0.80.

Horses upped in class have also made a decent profit to BSP of £122.76 which equates to a return of over 28 pence in the £. If we restrict these 'up in class' runners to those priced 12/1 or shorter to avoid potentially skewed results, they have still returned over 25p in the £. The evidence has a clear winner here.

 

Distance change from last race

Does the distance raced LTO have a bearing on results when running in a handicap over 1m2f at Lingfield? Let’s take a look:

 

 

Horses keeping to the same distance as last time out looks to be a positive. In fact, if we again use the same odds restriction (SP 12/1 or less) the LTO same distance subset have provided 149 winners from 812 runners (SR 18.3%) for a profit at Betfair SP of £83.49 (ROI +10.3%).

One very strong negative stat to share is that horses dropped in trip by more than two furlongs have won just 4.1% of the time (6 wins from 145) for huge losses of £110.16 (ROI -76%).

 

Course form

Does past course form count for anything? Well, if we compare previous course winners versus non-course winners there does seem to be a difference. In terms of win strike rate course winners have won 13.6% of the time compared to 9.8% for horses that have yet to win at the course. The A/E indices correlate with these figures as the bar chart below shows:

 

 

Now the ‘non-course winners’ group does involve a proportion of horses that have yet to run at Lingfield before. However, the A/E index for non-course winners that have raced at the track before is actually lower than the overall figure standing at just 0.79. Therefore, previous course winners have a definite edge over those that have yet to win at the Surrey venue.

 

Draw bias

Over longer distances the draw often becomes irrelevant, but it is always best to check some data rather than assume that is the case. The optimum draw position here seems to be from stall 5 to 7. This group of stalls has provided a strike rate of 13.4% with an A/E index standing at a very decent 1.03. Compare this to horses drawn 8 or higher whose strike rate is only 7.3% and the A/E is 0.71. The lowest draws meanwhile (1 to 4) have secured a strike rate of 11% with an A/E index of 0.82.

The chart below shows PRB3 (the average percentage of rivals beaten of a stall and its immediate neighbouring stalls), which corroborates the A/E narrative around stalls 5-7 (and indeed 8) being favoured.

 

 

As can be seen from the course map below, the mile and a quarter start is close to the winning line and thus presents only a short run to the first turn. This may explain why high draws are significantly unfavoured, with middle drawn horses perhaps able to find and hold a position close to the lead without using up too much energy so to do.

 

 

Although the draw is not perceived by many to be that important over this C&D, the numbers seem to suggest that higher draws (8+) are somewhat of a negative, with an ideal berth being five to seven stalls off the inside rail.

 

Run Style bias

In many previous articles I have shown the importance of run style. Run style can have a big say in shorter distance races on the flat/AW where front runners/early leaders often have an edge. Let's see whether there is any run style bias over 1m2f at Lingfield? Firstly, let us look at the win percentages for each group. Because each run style group has a different number of runners, we essentially use a wins to runs ratio to calculate the win% rate:

 

 

Front runners do not enjoy an edge here and are in fact only the third best group in terms of win ratio. It seems that a position close to the pace or in midfield is best. The percentages for win and placed runners also suggest prominent runners are the best group, and by a more significant margin.

 

 

These two sets of percentages are suggesting that a prominent sit is best over this C&D with a spot in mid-division more preferable than taking the early lead or being near or at the back early. It should be noted that combining the run style with the positive draw section of stalls 5 to 7 we get the following splits:

 

 

Hence if drawn in one of the favoured stalls - five, six or seven - it is definitely advantageous to race prominently or mid-division. This is further demonstrated in the PRB (percentage of rivals beaten) draw / run style heat map below:

 

 

Key takeaways

Below is a summary of the main findings from this delve into Lingfield 1m2f handicaps:

1. SP price range of 13/2 to 12/1 has been positive. Favourites have offered bad value. Horses 14/1 or higher have performed very poorly

2. LTO winners / runners-up have a very good record

3. Male runners priced 12/1 or shorter outperform their female counterparts

4. Horses upped in class have done best

5. Horses racing over the same distance to LTO are the best LTO distance group to concentrate on, especially if priced 12/1 or less

6. Past course winners have a definite edge over horses that have yet to win at the track

7. Horses drawn 5 to 7 have outperformed those drawn lower or higher

8. Prominent racers/mid division have a better record than holdups / front runners.

 

**

Undertaking this type of specific course and distance research can throw up some excellent insights to potentially aid the selection and betting process. If you have a specific C&D you'd like to see some key stats for, please drop a note in the comment section. I will do my best to do some initial digging.

- DR

More on Price Movement in NH Markets, Part 2

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Last week I wrote the first of two articles looking at price movements from Opening Show odds to SP in National Hunt racing, writes Dave Renham. This is the follow-up piece expanding on that initial research. As before, the data has been taken from the last five full years, covering 2020 to 2024. I have used William Hill bookmaker prices, and I will use ‘OS’ to denote the Opening Show odds.

To begin, I would like to look at differing race types. Specifically, I want to compare chases with hurdles to see what percentage of these runners shortened in price, lengthened in price (drifted), or stayed the same price, when comparing their OS to their SP.

 

 

As the graph indicates, there was a bigger percentage of drifters in hurdle races compared to chases, and hence fewer hurdlers shortened in price compared to chasers. If we look at non-handicap hurdle races versus handicap hurdle races it can be seen that in non-handicaps 49.4% of all runners drifted, whereas in handicaps the figure stands at 46.2%. Interestingly, this percentage ‘swing’ is reversed when we look at non-handicap chases versus handicap chases. The splits this time see more drifters in handicap chases (44.7%) compared to 41.1% for non-handicap chases. This is a good example of where we can see the importance of digging down into the long grass. We saw this in the first article when noting the differences between certain courses, in the splits for class of Race, and in how the OS odds affect the likely direction of any potential price movement.

I also looked at bumper (NH Flat) races where 47.9% of runners drifted from OS to SP compared with 38% that shortened (just 14.1% remained the same price).

Next, I would like to see there is anything material in terms of day of the week. I am going to concentrate solely on the percentage of drifters on each of the seven days my suspicion being that Saturday will have the lowest percentage, due to having stronger markets. Let’s see:

 

 

Saturday does indeed have the lowest figure which correlates with the race class and course data shared in part one last week. Saturdays tend to have better races when the day is viewed as a whole, and more of the top tier courses are in action on this day of the week, too.

In that prior piece it was noted that Cheltenham was the racecourse that had the smallest percentage of drifters out of all the courses. With the Cheltenham Festival roughly three weeks away, I thought it might be helpful to see what the splits are in terms of runners that shortened in price, lengthened in price or stayed the same price, when comparing their OS to their final Starting Price Odds at the Festival. Here they are:

 

 

This is quite a change from what we have seen so far. Horses remaining the same price from OS to SP have occurred more than either of the other groups. Horses that lengthened in price have a figure 16% lower than when looking at NH races as a whole. I had expected the percentage figure for drifters to be somewhat lower than the norm due to the strength of the Festival markets, but I had not anticipated as much as 16%. I also did not expect the 'stayed same price' group to come out clearly ahead of the others. It has made me think that maybe I write an article where I do a deeper dive into the Cheltenham Festival in terms of price movements, incorporating early morning odds moves too. More of that to come perhaps.

Time to switch attention now to some trainer data. To begin with here are the trainers with the highest percentage of runners that have shortened in price between OS and the ‘off’. To qualify a trainer must have had at least 200 runners during the period of study:

 

 

13 of the 20 trainers have higher percentages for shorteners than for drifters. When I looked at flat trainer data back in the Autumn only two trainers managed that feat. Four of the ‘big guns’ - Nicky Henderson, Paul Nicholls, Willie Mullins and Dan Skelton - are absent from the list, so what about them? Here are their splits coupled with a selection of some other familiar names not seen as yet (again the table is ordered by % of shorteners):

 

 

It is quite interesting to see Skelton, Nicholls and Henderson with the smallest percentages for horses that have shortened in price from OS to SP. It is also interesting when we compare their shorteners with their drifters in terms of value by using the A/E index. The graph below shows the splits:

 

 

For all three there has been far better value in their runners that were backed in between OS and SP compared to those that drifted. Indeed, you would have made a tiny profit to BSP on all Paul Nicholls runners that shortened in price from OS to SP.

In terms of negatives beware Henderson drifters in chases: of the 283 chasers that drifted 43 won (SR 15.2%) but they accrued losses of £58.26 (ROI -20.6%) to BSP. In addition, Henderson non-handicappers (any NH race type) that drifted have also proved to be poor value losing over 18p in the £.

As far as Paul Nicholls is concerned a drifter is a bad sign if ridden by stable jockey Harry Cobden. Although just over 20% of them have still won, backing all 834 qualifiers would have seen a loss to BSP of £184.51 (ROI -22.1%). Conversely, drifters from the Nicholls yard not ridden by Cobden have won more often (21.5%) and proved profitable to BSP to the tune of £108.80 (ROI +19.3%). These runners would secured a blind profit to Industry SP of around 6p in the £ as well. Meanwhile, if a Dan Skelton runner drifts at Cheltenham, beware, as only four of the 87 have won for losses of over 66p in the £.

My final piece of ‘drifting’ data for these three trainers comes in the form of their record in Class 1 races when this occurs. Their results are shown below:

 

 

Henderson’s record is modest but not terrible, but for the other two the figures are very poor. I would not be keen in the near future to back a Skelton or Nicholls drifter in a Class 1 event.

Sticking with these trainers and Class 1 events, let us see their performance when their runners shorten in price before the ‘off’. Unsurprisingly, we see a contrasting picture to the earlier one:

 

 

All three have edged into profit with solid figures across the board. Clearly, for these three trainers in top level races the strength of their runners in the market just prior to the off is very important.

Olly Murphy is another trainer who has a couple of stats worth mentioning. Interestingly, his drifters have won almost as often as those that have shortened in price – 18.2% versus 20.6%. Given those numbers, it won't shock to learn that his drifters made a positive return of 5p in the £ whereas his shorteners lost 20p in the £ (to BSP). Sticking with those runners that have shortened in price, when they started favourite they broke even. When they were not favourite losses have been 27p in the £.

Lastly in this piece, I want to focus on Irish maestro Willie Mullins as there are a few useful titbits when it comes to his stats. There are three powerful stats of which we ought to be aware:

1. Any Mullins drifter at the Cheltenham Festival is not a good sign. 100 horses have drifted from OS to SP at the March showpiece of which only 11 won (SR 11%) for a BSP loss of £43.36 (ROI -43.4%).

2. Don’t be lured in by bigger-priced runners from Mullins ‘being backed’. Horses that shortened in price from an OS of 18/1 or bigger are 0 from 54.

3. When one of Mullins' horses shortens in price from OS to SP take note of the jockey. The table below shows why we want Paul Townend on board:

 

**

This article has highlighted some interesting patterns in terms of how the market moves during that brief period between the opening show and the start of the race. I think some of the trainer data for Messrs Henderson, Nicholls, Skelton, Murphy and Mullins could prove really useful and help to point us in the right direction when contemplating the timing / placing of our bets.

- DR

 

More on Price Movement in NH Markets, Part 1

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Back in October I wrote an article that examined some betting market data whereby I investigated patterns of price movement from early morning odds to SP in UK NH racing. I felt now was good time to revisit the idea but switch attention to movement between opening show and SP.

This is first of a two-parter with data taken from the last five full years covering 2020 to 2024. I have used William Hill bookmaker prices and, for the remainder of this article, I will use ‘OS’ to stand for the Opening Show Odds.

As I mentioned in earlier work, the OS for most races occurs around 10-15 minutes before the race is due to start. Each horse will have its opening price and then, as money is wagered in the period before the race starts, the prices will begin to fluctuate. Some will go up, some down, some will end up the same price as they started. Price changes are also driven by what happens on the betting exchanges.

As I did for the previous research let me start by sharing the figures for all runners over this time frame to see what percentage shortened in price, lengthened in price (often known as drifting), or stayed the same when comparing their OS to their final Starting Price Odds (SP).

 

 

 

These percentage splits are very close to those I found for flat racing with far more horses lengthening / drifting in price than shortening in price. Once again, the smallest percentage figure occurred with horses staying the same price.

Market movement during this short period before the start of the race is a good indicator of a horse's chance of winning as the graph below shows when we examine the win strike rates of the three groups:

 

 

 

Horses that shorten in price have won more frequently, edging towards twice as often as those that drift. In terms of returns, to Industry SP horses that have lengthened in price (drifters) would have lost you a hefty 30p in the £, while those that have shortened in price would have lost you around 15p in the £. To BSP the gap is much reduced with an 8.6% loss for drifters and a 5.6% loss for ‘shorteners’.

Let me now share the yearly percentage of runners splits for the three groups in terms of comparing their OS odds to their SP odds:

 

 

As we might have hoped the splits have been similar year on year. Readers may notice that 2020 is slightly out of kilter, but my guess is that Covid was a key reason behind this. No spectators at racecourses for around eight months in 2020 meant we had an unusual situation come Opening Show with no oncourse bookmakers taking money. It is also the case that, since Covid and 2020, the starting price is framed more significantly around off-course liabilities than on-course, reflecting where the majority of betting action happens nowadays.

For the next part of this piece, I would like to focus on the percentage of horses that lengthened / drifted in price showing a course-by-course comparison. The courses are ordered highest percentage to lowest. As a reminder, the overall figure for all courses was 46.5%:

 

 

I have highlighted in red those courses that had the smallest percentage of drifters and what immediately stands out is that these tracks are universally considered to be top tracks. In fact, if we look at the list of courses that have held the most Graded races over the past five seasons we see the following:

 

 

These same seven courses showed the lowest percentages for drifters. I suspect there are two main reasons for this. Firstly, stronger markets exist at these courses – more money is wagered (off course, on the exchanges, and on course); and, secondly, there tends to be better overall knowledge of the horses that race at these tracks due to the average class level, making early markets more efficient / accurate.

Thinking about class of race, based on my second theory noted above, we might hope that if we look at the percentage of runner splits within each class, the higher classes of race would see a smaller gap between horses that shorten in price from OS to SP compared with those that lengthen/drift.

I have lumped Class 6 races in with Class 5 purely because there are very few Class 6 races in National Hunt racing. In addition, I have added an extra column which shows the percentage difference between horses that have shortened compared with those that have drifted. Here are my findings:

 

 

As hoped, the theory has held, with the highest class of race (Class 1) seeing by far the smallest gap between shorteners and drifters of 5.3%. As can be seen, once we get to Class 4, the gap extends to 16.7% for Class 4 races and 14.9% for Class 5/6 races. Hence, for those of us who may still take a bookmaker’s price between OS and the start of the race, the stats for Race Class and the previous course ones should help inform us more accurately about the chance of our selection drifting or shortening in the ten minutes or so before the race. For punters, having the overall stats gives us a good 'feel', but breaking things down into subcategories can offer more knowledge and understanding of how prices may move.

My focus now is to look at price movement from Opening Show to SP within different price bands. The figures are split by percentage of qualifying runners:

 

 

These price bands are based on huge sample sizes so we can be confident that these types of figures are likely to be replicated in the future. Possibly the most eye-catching percentages are those for bigger priced runners. Once we get to an Opening Show of 18/1 or more, over 50% of such runners have drifted in price. There also seems to be no difference to the overall norm when it comes to those priced up between 9/2 and 6/1. The percentages between shorteners and drifters are close to parity with a slight edge to shorteners. To see this more clearly let me graph the comparison:

 

 

The graph clearly shows this ‘close to parity’ situation with the 9/2 and 6/1 Opening Odds price band. Expanding this slightly, it also shows that the percentages are closest from 100/30 to 8/1 compared with everything else. We knew already that drifters occur more often than shorteners but seeing these price splits offers further appreciation of how likely a horse may be to shorten or drift. Looking back at the flat article I wrote we witnessed a similar pattern in terms of how the overall graph looks.

To conclude, understanding how a betting market may evolve from Opening Show to SP is an area that is rarely analysed. There are some parallel patterns with the flat findings I previously shared, as you might expect. In many ways this is a positive as it provides greater confidence that OS to SP prices will continue to move in similar ways in the next few years.

My next article will be a follow up to this one, and will look at some additional areas such as race type and trainers. Until then...

- DR

‘SR’ Ratings on the All-Weather

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There are numerous reasons why the only racecards I use are the Geegeez Gold ones, writes Dave Renham. There are several useful tabs on the racecard, three of which I always look at first: Pace, Instant Expert and Profiler. For flat and all-weather racing I will also look at the Draw tab.

Each of these tabs offers me useful and diverse information, all at simply the click of a button. In under two minutes I can decide about whether the race in question is one that merits more of my time. If it does, then I will delve into the Full Form tab to build up a bigger overall picture for myself. If I get to the stage where there looks to be a horse or horses that I may be interested in betting on, the next thing I will look at is the SR column in the main Racecard.

The number in that column is a ratings figure derived from Dr Peter May’s research. I have always had huge respect for Peter, and I will always consider his ratings when analysing a race. Having Peter’s ratings is another bonus when it comes to using the Geegeez Gold cards. And for today’s article it is Peter’s SR ratings that I am going to take a deep dive into.

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.

My focus for this article is all-weather racing. I have looked at a five-year time frame from January 1st 2020 to December 31st 2024. When I refer to the ratings from now on, I will call them SR Ratings as that is how they appear on the geegeez racecards.

I have spoken to many people who have compiled ratings in the past, be they speed or ability ratings, and in every case the win rate was the key to judging the effectiveness of their ratings. 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. Obviously, it is hoped the top-rated runner is the best performer in terms of betting returns, too; however, it is important to point out that regardless of how good a set of ratings is, we cannot generally expect the top-rated runner to secure a blind profit over thousands of races. That's not the case with Racing Post Ratings, Timeform Ratings or any other public rating. Despite that, such figures are an excellent guide to which subset of horses can normally be considered contenders.

Let’s start with looking at the win percentages (strike rates) for different SR-rated runners. This covers all races on the all-weather over the five year period of study. The horizontal axis is labelled from 1 and represents the top-rated runner, 2 the second-top rated, and so on:

 

 

The win strike rate for top-rated runners is close to one win in five which is thoroughly decent, and the top three rated horses win almost half (48%) of races. The percentages correlate positively with the rated positions showing a sliding scale that we would hope for. If we look at the Each Way (win & placed) strike rates, we see a similar pattern:

 

 

The top-rated runner is comfortably clear once more, and the sliding scale is replicated showing positive correlation with the win only figures.

In terms of returns to Industry SP, the top-rated runner has performed the best although overall losses stand at 15 pence in the £. However, to Betfair SP losses stand at under 2p in the £. This is impressive considering there are around 13,000 top-rated runners in this sample.

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

 

 

As we can see, in non-handicaps the top-rated runner is well clear of the second rated, while in handicaps the gap is much smaller. This was to be expected, given the relatively competitive nature of handicaps compared with non-handicaps, but again it is good to see it in black and white - or should I say orange and blue!

I would like to now analyse the BSP returns of the top-rated horse in different race types. These have been split into 2yo non-handicaps, 2yo handicaps, 3yo non-handicaps, 3yo handicaps, all age non-handicaps, and all age handicaps. The graph below shows the Betfair SP return on investment percentages (BSP ROI%) for each race grouping:

 

 

Three of the six groupings (2yo non-handicaps, 2yo handicaps, 3yo handicaps) saw the top-rated secure a blind profit which is impressive stuff. All age non-handicaps showed the worst returns, still only losing 6p in the £.

Using the Query Tool on Geegeez I decided to compare the performance of AW favourites, split into those that were also top-rated on the SR Ratings versus those that were not top-rated. Here are the findings:

 

 

The Win PL (profit/loss) and ROI (return on investment) columns have been calculated to Industry SP, and we have a clear winner. In addition, the strike rate is more than six percentage points higher.

When calculating to BSP there is a similar difference between the two:

 

 

Thus, if we back favourites on the all-weather, having them top-rated on SR Ratings would have improved our bottom line. Yes, SR top-rated runners when favourite still made a loss to BSP, but it was limited to only 2p in the £ over five years. A pretty good starting point for further research.

We see a similar pattern when we look at horses second in the betting comparing their record when SR top-rated or not. Here are those splits:

 

 

Again, these are calculated to Industry SP but a clear difference, equating to around 8p in the £, can be seen. To BSP, SR top-rated horses that started second favourite secured a profit of around 4p in the £.

I would now like to look at top-rated runners in all age handicaps in more detail. The reason is that all age handicaps make up around 70% of UK all-weather races, a striking statistic. Also, from a personal perspective, these are my favourite races to bet in. I am hoping that getting a better feel for the top-rated runner has the potential to inform some of our future betting decisions.

Below is a table showing the most positive results from a BSP returns perspective in all age handicaps:

 

 

As a fan of sprint handicaps this makes very pleasing reading. The minimum distance has been a strong positive for top-rated runners in these all age handicaps. The lower weighted top-rated runners have also performed well. It should be noted that this is based on the card weight of the horse and does not consider jockey claims. A quick return is often seen as a positive and, although they tend to be overbet these days, that has not seemingly been an issue when they have been SR top-rated runners. Horses that have yet to win at the course have also snuck into profit possibly due to course winners being overbet meaning the non-winners have been slightly underbet.

I would like to finish by combining top-rated runners with Run Style/Pace. Of course, the run style figures are only known after the race is in progress but the figures follow a familiar pattern we have seen before:

 

The Win PL and the ROI can be considered to be ‘projected’ returns to Industry SP, because as we know we cannot predict 100% how the run style for each horse within each race will unfold. But if we can find a top-rated runner that is a strong candidate for leading early, then this would potentially be a decent betting opportunity. For the record, front running top-rated runners offer slightly better returns in handicaps compared to non-handicaps.

**

At the beginning of this article, I was praising the virtues of the Geegeez Gold racecards. At the end of that opening paragraph I mentioned that having Peter May’s ratings (SR) was a bonus; I hope after reading this article you will agree with me and feel better equipped to tackle the all-weather, particularly under certain highlighted circumstances, going forward.

- DR

When NH Trainers run two in the same race

/in /by

Back in July 2021 I shared some research connected with UK flat trainers when they saddled two runners in the same race (which you can read here), writes Dave Renham. In this article I will do likewise with UK National Hunt trainers. Clearly, there are occasions when trainers saddle three or more runners in a race but, to make the research and writing process easier, for this offering I will once more focus on exactly two runners saddled.

It is likely that in the past some punters have been lured by the prices on two runners from the same stable: if one is 3/1 and the other 14/1 the chances are the focus will be on the more fancied runner of the pair. I, for one, have been guilty of this before.

The data in this analysis has been taken from UK National Hunt races between January 1st 2016 and December 31st 2024. All profit and loss figures have been calculated to Betfair Starting Price less commission. For the shorter priced horse of the pair, I will call this the “first string”, the bigger priced runner will be known as the “second string”.

Overall trainer performance when running two in the same race

Let me first look at trainers who have had two or more runners in the same race on at least 100 occasions (hence at least 200 runners overall). There have been 28 trainers that qualify in the study period using that stipulation:

 

Below are the combined results of all runners for each trainer (i.e. both first and second string horses). The trainers are listed in alphabetical order:

 

 

Not surprisingly, just four of the 28 trainers show a profit when looking at both runners combined. It is unlikely that backing both runners for every trainer in every race is going to make a profit long term as the overall stats clearly show. Indeed, the four in profit owe that accolade to some huge prices going in.

Let us see what happens when we break the data down and compare trainer win strike rates between first and second string runners. The plan is not to compare the raw win percentages with each other, but to add up the winners for each of the two market ranks and work out what percentage of all the winners came from the trainer’s first string (shorter priced runners) and what percentage came from the second string (longer priced runners).

In other words, if we use Donald McCain as an example, he has had 60 winners when running two horses in the same race, of which 45 were his first string runners (75%); 15 winners came from his second string runners (25%).

To show this comparison for each trainer I have split their data into four separate graphs, so as not to overcrowd the pictorial evidence. The orange bar represents first string runners, the blue bar is for second string.

 

 

As the graphs show, the stats vary greatly from trainer to trainer. For example, Nigel Twiston-Davies has two percentages that are close together (57.1% and 42.9%) having done particularly well with second strings, whereas Phil Kirby’s figures are poles apart (95.8% and 4.2%). Overall, when combining all 28 trainers, 75.7% of the winners have come from their first string entries, 24.3% from their second string. These figures are almost a carbon copy of those calculated in the flat trainer article back in 2021.

 

Trainer performance with first string runners

Eight trainers have made a profit with their first string runners and their figures, ordered by BSP profit, are shown in the table below:

 

 

Caution is advised regarding the profit figure for Christian Williams as he had BSP winners equating to 165/1 and 179/1, and yes, they were his first string runners despite the high prices! Chris Gordon in contrast has not had any big-priced winners and overall, his record with first string runners is excellent. If you restrict Gordon’s first string runners to those priced in single figures (at BSP) his record reads a highly impressive 29 wins from 82 (SR 35.4%) for a profit of £33.90 (ROI +41.3%).

Paul Nicholls has had over 400 first choice runners in this double-handed context, and his biggest priced first string winner was BSP 13.0 (12/1). Hence his bottom line has not been skewed by numerous scorers at very big odds. If we look at all his first string runners priced BSP 13.0 or less he has secured a healthy profit of £90.23 (ROI +27.2%) from 332 qualifiers. If we look at the Nicholls profit year on year with this subset of runners we see the following:

 

 

2021 was the year that produced over half of the profit but even taking that out of the equation the performance and consistency has been excellent. Over the nine years of study, seven have shown a profit.

Phil Kirby’s figures are also not badly skewed by horses winning at big prices. Sticking to a price cap of BSP 13.0 or shorter, Kirby has secured 20 winners from 68 qualifiers (SR 29.4%) for a profit of £24.02 (ROI +35.3%).

Nicky Henderson did not secure an overall profit with his first-string runners but the jockey booking seems to have made a difference. When Nico de Boinville has been riding the Henderson first string, the results read 49 wins from 224 (SR 21.9%) for a profit of £21.67 (ROI +9.7%). When any other jockey has been on board the Henderson figures read 46 from 241 (SR 19.1%) for a loss of £74.80 (ROI -31%).

Dan Skelton is a trainer who has performed extremely well over the past few seasons across the entire National Hunt sphere, but when we focus on his first string runners (of two) in chases his stats make very poor reading. From 95 qualifiers only 11 won (SR 11.6%) for hefty losses of £46.44 (ROI -48.9%).

Trainer performance with second string runners

Five trainers have produced a BSP profit with their second-string runners. Clearly big prices have made the difference here with all strike rates under 8%:

 

 

As profits go these should largely be taken with a pinch of salt, but I wanted to share them all the same.

It may be more useful to share a list of trainers with a very poor record with their second string runners, so below are those trainers with the worst returns across the nine year review period:

 

 

Based on these figures it seems sensible to all but rule out second string runners from trainers in the above table.

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One trainer whose data has not been shared as yet is Irish maestro Willie Mullins, simply due to him not quite saddling enough UK NH runners to make the cut. For the record his figures for both first and second strings are good with blind profits to BSP for both. His first string runners have secured returns of 26p in the £, his second string runners 28p in the £.

Harry Fry is another trainer who had less than 200 runners of this type overall, but his first string made a blind profit. Indeed, when focusing on these first string runners using the earlier price stipulation of BSP 13.0 or less, Fry has secured 14 wins from 48 (SR 29.2%) for a profit of £26.31 (ROI +54.8%).

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Trainer statistics are used by many punters when contemplating a bet. These stats come in different forms such as course stats, recent form stats (e.g. last 14 days), favourite stats, horses on debut, etc. The ones I have shared in this article generally fly under the radar but, hopefully, you have found them useful for either pinpointing possible value bets or, just as importantly, helping to avoid poor value ones. Unsurprisingly, given the overall stats uncovered in this article, the evidence points firmly towards focusing most attention on the shorter priced first string runners.

- DR

The Maths of Multiples, Part 2

/in /by

In my previous article, the discussion moved to each-way doubles and how the makeup of certain races / markets has the potential to give punters an edge over bookmakers, certainly in terms of the place part of such a bet, writes Dave Renham. You can read that article here. In this follow up, we are going to dive deeper into the world of the ‘each-way double’.

For these bets to be profitable in the long run, we ideally need to have achieved a value price on both of the two selections, in terms of the win part as well as the place part, for every bet that has been struck. In other words, the actual chance for both parts of the bet for both selections are higher than the percentage chances on offer from the bookmaker. Technically we could also make a long-term profit if one of the two parts of the bet always offers enough value to compensate for the part that does not. It goes without saying that achieving any sort of edge is far from easy.

To try and illustrate this in numbers let us imagine an each-way double where we have place terms of one quarter the odds, and the price on both selections is 5.0 (4/1). The true percentage odds for a horse priced 5.0 to win is 20%; the true percentage chance for a place with quarter the odds stands at 50%. (N.B. a ‘win’ constitutes a ‘place’, so effectively ‘place’ means ‘win or place’). Therefore, if both horses are priced over 5.0 to win, we have a value bet.

To help crunch the numbers, I have created an excel spreadsheet to simulate a series of each-way doubles with a specific price / percentage chance for each selection. The number of simulated each-way selections for each series of bets has been set to 1000. This is a huge number of races but due to each-way doubles rarely achieving two wins, it makes sense to use such a large number. Ultimately it is easy to tweak the number of bets/races for each simulated series, so I could adjust the number of races up or down. Within each simulation I can adjust the win/place percentage chance of these ‘runners’ (above and below the ‘true’ percentage chance) to examine the long-term outcome from a profit/loss/returns perspective.

So, to kick off I'll return to the example of the two 5.0 priced runners given in the third paragraph, where we have place terms of one quarter the odds. If we assume each 5.0 price is always the ‘true’ price, then over 1000 bets we would break even. The maths look like this based on a £1 each-way stake (£2 in total) on these 1000 each-way doubles:

Races with two wins – 40
Races with ‘place’ wins (e.g. Win/Place or Place/Win or Place/Place) – 210
Races where the bet was a loser (e.g. at least one horse unplaced) - 750

Thus...

The 40 successful win bets would have paid £960 profit and £120 profit on the place part of the bet;
The 210 winning place bets would have paid £630 profit for the place part but would have lost the £210 placed on the win part of the bet, leaving a profit of £420.
The 750 losing bets would have seen a loss of both the win stake and the place stakes equating to £1500.

Adding the profits of £960, £120 and £420 we end up in credit to the tune of £1500, but subtracting the losing bet total of £1500 we arrive at that break-even situation as mentioned above.

This 5.0 / 5.0 example shows what happens when the horses win and place as often as they theoretically should do based on their odds / percentage chance. In this case we know already that a true 5.0 shot should win 20% of their races and win or be placed in 50% of them. So, what happens when these percentage chances differ from the ‘true’ percentage chances? This is where my spreadsheet comes in to save time.

The first graph will look at the effect that different win and placed percentages have on the long-term Return on Investment figure (ROI%). Remember we will be theoretically placing 1000 each-way doubles on two horses priced 5.0 with quarter the odds a place. In order to help explain the graph, the table below shows how I have adjusted the win and place percentages:

 

 

 

 

There is a neat symmetry to these results. As is shown, if we could increase the average win chance by 2% (from 20% to 22%) and the placed percentage also by 2 (from 50% to 52%) the long-term return would be a pleasing 14% or 14p in the £.

Let’s look at another example. This time we will assume both horses are priced 6.0 (5/1) but the place terms are 1/5 of the odds. I have tweaked/changed the percentages in exactly the same way as I did in the first example. For the record the true win percentage chance here is 16.7% (to 1 decimal place), with the place chance being 50%. Here is what I found:

 

 

We get a similar pattern as one would expect although not quite the exact symmetry of the previous example. It should be noted at this juncture that the 1000 bet simulation using this particular price point could show that a horse has won 39.89 times in the 1000 races! Clearly this is not possible, so I have simply rounded the ‘expected’ win or placed results to the nearest whole number. Therefore, one could argue that the 7.8% ROI for let’s say the W17.7 P51 group is not 100% accurate, but it is as near as doesn't matter in the context of these simulations.

Time now to look at two horses with different prices; I am going to consider horses priced 3.0 (2/1) and 5.0 (4/1), using one quarter the odds a place. This is more difficult to show on one graph because we now have effectively two win percentages and two place percentages being used for each ROI% calculation. Hence, I am going to share two separate graphs.

In the first of the two graphs the ROI%s shown are based solely on the win percentages for each horse changing compared to their true win percentage chances. In this case I have assumed that the place percentage chance has remained the same for both horses for this simulation. The bottom of the graph has a key which I will now explain:

TW stands for the true win percentage chance for each horse based on their prices of 3.0 and 5.0 (which 33.3% and 20%)

TW+1 stands for the true percentage win chance +1% (34.3% and 21%)

TW+2 stands for the true percentage win chance +2% (35.3% and 22%)

TW+3 stands for the true percentage win chance +3% (36.3% and 23%)

TW-1 stands for the true percentage win chance -1% (32.3% and 19%)

TW-2 stands for the true percentage win chance -2% (31.3% and 18%)

TW-3 stands for the true percentage win chance -3% (30.3% and 17%)

 

To be clear, the graph below shows the effect on the ROI% of only theoretical changes in the long-term win percentages. All place calculations are based on their true percentage place chances which for the 3.0 priced horse is 66.7% (to 1 decimal place) and for the 5.0 priced horse it is 25%.

 

 

Assuming we can improve our percentage chance of each horse winning by 3% compared to their true chance we would make close to 13p in the £ over the long term. Conversely, if the percentages for both horses dropped by 3% we would be losing just over 11p in the £.

The second graph will show theoretical changes in the place percentage while keeping the win percentages at their true figures. I will again use +1, +2 idea but this time I will use TP meaning true place percentage:

 

 

As we can see a change of 1%, 2% or 3% in the placed percentages has less influence on the ROI%. However, if we can gain a place edge while keeping parity in terms of the win percentage then we will make money over the longer term. Clearly if we can gain both a win edge and place edge your profits should mount up nicely.

It is time to look at some ‘real life’ data now, based on actual horse racing results and prices going back to 2010. I looked at all 12-runner handicaps over this time frame which covered over 90,000 runners. I looked at the prices of different runners and extrapolated their actual long-term win and placed percentages. I then used these figures to work out the potential returns on a series of 1000 each-way doubles with said percentage chances. As I was simulating 12-runner handicaps for each of the 1000 races, the place terms were set at one quarter the odds. Here is what I found:

 

 

This does not make for pleasant reading. The reason behind such poor figures is, of course, the bookmaker edge I discussed in the first article. The average prices of the runners do not reflect their true chance of winning, or indeed placing.

Readers may note that the 5.0 / 5.0 figures see a loss of 16.6%. If we go back to the first graph in this article which examined a 5.0 price / 5.0 price simulation, we can see that when the win% was set at 18% and the place at 48%, this lost 14%. Given the real-life figures gave us an ROI% just below that at 16.6% it is no surprise to know that the actual win and placed percentages based on the 2010-2024 average figures were just below these at 17.97% for the win and 46.67% for the place.

Understanding how probability works is important when it comes to betting singles, but I would argue it is even more important when it comes to combining two or more horses in a bet. Probability can be a complex subject at a higher level but, fortunately, for betting purposes it is relatively straightforward. Just remember, for those of us betting doubles, trebles, fourfolds, and so on, we need to multiply the percentage chances together to give the overall percentage chance.

*

I hope this has been an enjoyable and informative piece, and that it has tied in neatly with the previous one. Each-way doubles are bets that are worth considering given the right conditions of price to chance and race shape. I am in two minds about whether to dig a bit deeper with the potential to research and write a third piece. I will play around with some ideas in the next few weeks so watch this space!

*

Before I go, if anyone is interested in a more complex probability challenge please read on.

I would like to share a famous problem that I used to pose to my older students when I taught in schools. It is a version of what is known as the ‘Birthday Paradox’.

Imagine 30 children in a room all aged 12. What is the probability that at least two of them will share the same birthday? 

Now for those who have not heard this paradox before, then I urge you to take an educated guess at the chance of this occurring before reading on.

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When I posed this question to my classes over the years, their thinking generally went along the lines that there are 30 children, there are 365 days in a year and hence they divided 30 into 365. Having said that, most of them ‘rounded’ 365 to 300 to make the calculation easier, where 30 divided by 300 gives an answer of 10%. So, I would say 95% of all answers I received were in the ballpark of 10%. However, 10% is way off.

The actual answer is 69.68%.

Be honest now – how many saw that coming?

I am sure there will be a high proportion of readers that will be incredulous that this is the answer. However, if you Google it, you will see that the information above is accurate, and how the answer is calculated.

Until next time...

- DR

The Maths of Multiples, Part 1

/in /by

I am sure even the most disciplined of punters will have had a more ‘exotic’ bet at least once in their life, be it an exacta, tricast, placepot, double/treble, or some type of accumulator bet involving four or more selections, writes Dave Renham.

The lure of a bigger payout has a big appeal to many punters; I certainly include myself in that category in the past. I have been very lucky to have what I consider to be one monster betting payout in my life which was thanks to a tricast / CSF combo back in 2004. At the time this one bet paid the equivalent of around ten months’ worth of my take home pay from my teaching job. I wouldn’t mind that happening again now, I have to say!

The problem of course with any exotic bet is that the margin in favour of the bookmaker is usually bigger than it is if solely betting win singles. The more selections you have in an accumulator the bigger the bookmaker’s edge generally is. I am not going to dive deeply into the maths here but to give you a basic understanding of what is going on let me look at a hypothetical fourfold win only accumulator that has been placed with a bookmaker. I am going to assume that the four selections come from races with ten runners in each race and the decimal odds obtained for each horse are:

4.0, 6.0, 3.0, 7.0

In this scenario, the unlikely event of all four winning would net a profit of £503 for a £1 stake (£504 total return, including stake).

The problem is that the true odds of each of the four horses should be bigger. This is due to the inbuilt bookmaker overround/edge. On average the bookmaker’s edge in a 10-runner race will be around 20% (using a rough guide of 2% per horse). Hence when you add up the percentage chance of all the runners this will equal around 120%, not 100% which would, of course, give punters a fair playing field due to the odds be true/correct.

To find odds for these four horses much closer to their true odds we can look on the Betfair Exchange as their betting book for each horse race is always closer to 100%. This means the odds are as near to the true odds as we can get. Of course, we cannot place a fourfold on the Exchange, but I can at least borrow their ‘true’ prices to see what the winning return on this wager should pay, rather than the payout we saw earlier. Here are prices for our four horses that will be nearer to their true odds – the type of odds you would find on the Betfair machine:

4.6, 7.2, 3.25, 8.6

As can be seen each corresponding price is bigger, not by that much, but enough to make a huge difference overall. In this case, the winning profit on the fourfold would stand at a much healthier £924.70 for your £1 stake – over £420 more than would have been returned using the odds available from the bookmaker.

To make money on betting we need to get a value price. For example, if we can get odds of 2.2 on the toss of a fair coin, which should be priced at 2.0 we have value. Hence one could argue that multiple bets or accumulators can offer the punter value as long as all the selections are value prices. One immediate downside of course is that even if we are effectively getting value on each horse, we still need all of them to win!

Staying with the tossing the coin example, we can apply this to horse racing. Let’s assume that we have found four horses priced 2.2 that we believe have true odds of 2.0. If we combine them in a fourfold accumulator, the chances of all four winning equals 1 in 16. This is based on probability theory where we multiply the individual chance of each event together with each other – in this example each horse has a 50% or 1 in 2 chance of winning their respective race so we calculate thus ½ x ½ x ½ x ½ = 1/16.

Hence, we would be expected to win this fourfold bet one time in every 16 attempts. Of course it is not going to pan out perfectly like that in real life – we will not have 15 losing bets followed by a win, then another 15 losers followed by a win and so on. However, over the long term we will win with this type of bet on average around once in every 16 races (if we are correct about our true odds estimate).

But what is the edge on this bet?

Let us imagine we place £1 on each fourfold using the probability theory scenario of one win in 16. Over the 16 bets we would lose £15 on the 15 losing bets but win £22.43 on the one winning bet plus our stake back. This gives us a profit of £7.43 from £16 staked which equates to a Return on Investment (ROI%) of 46.4%.

As I have mentioned this calculation has been based on probability theory being played out perfectly in real life over 16 fourfold bets involving 64 horses priced at 2.0 with true odds of 2.2.

Let’s now compare the winning fourfold return with 64 individual win singles on these same horses using £1 stakes. With a 50% chance of winning this means we win 32 times and lose 32 times. The 32 losses lose us £32. Each win nets us a profit of £1.20 so 32 x £1.20 equals £38.40 giving us an overall profit of £6.40.

Now the eagle-eyed mathematicians will have noted that in the second example the total outlay of the bets comes to £64 and in the fourfold example it came to £16. We were correct, so comparing simply the two profit figures here is not a fair test. We need to calculate the ROI% as before by dividing the profit of £6.40 by the total stake of £64. This gives us an ROI of 10% - a good deal lower than the fourfold return. Therefore, by doing that comparison, we can see that fourfolds where we have value on each horse, potentially gives us extra value in the long term when compared to win singles.

However, this is all well and good, but a massive downside to the multi approach is finding four horses that offer value on the same day. For some of us it hard enough to find one each day, let alone four. In theory, four value selections combined in fourfolds offer us the chance to really enhance our long-term returns, but in practice it is going to be nigh on impossible to achieve it.

Even if we did find four value selections what are the chances these value selections will all be available with the same bookmaker? Not only that, but the example I gave looked at four very short-priced runners giving us returns on average once in 16 races.

If we instead consider say four horses that all had a bookmaker price of 4.0 (3/1) where their true odds were all say 4.3 (3.3/1), based on probability theory this bet is going to be landed just once in every 256 bets (because ¼ x ¼ x ¼ x ¼ = 1/256).

So, if we assume we are able to find four 4.0 priced horses with true odds of 4.3 on the same day with the same bookie, let’s say once every week, and we place them in a win fourfold accumulator, on average we will have one successful bet every 4.92 years! Perhaps this is starting to help explain why bookmakers push their multiple and accumulator bets so much!

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There is one type of multiple that some people believe can offer us some value though and that is an each-way double. An each-way double is when we place a bet on two horses to win and/or place. If both horses win, the win part is worked out in the same way as a win double. If both horses place, or one horse wins and the other one places, we will win the place part of our each-way double. And, naturally, if one or both horses fail to at least place the bet is a losing one.

Let’s look at example with prices. We’ll assume both horses are priced at 5.0 (4/1) and the place odds are ¼ of the win odds. Here are the possible outcomes based on a £1 each-way double (£2 staked):

 

 

Advocates of this bet will say that one advantage of an each-way double compared with a straight win double is that we can get a return even if both horses fail to win, as long as they get placed. They will also say, quite rightly, that compared to the fourfold accumulators looked at earlier we only need two horses to perform well, not four. Hence the bookmaker edge / margin is less pronounced.

Personally, I do play each-way doubles from time to time. When running my tipping service back in the early 2000s I put up the odd each-way double as actual main bets/selections, and I nailed an each-way double that returned a profit of £128 for an outlay of £2. So, with the right selections in the right race, I view this bet as having potential to make money long term. However, as with anything in betting, we need lots of patience to find the right opportunities.

The ideal type of race we are looking for is when we have a race with a very short-priced favourite, with the second favourite clear in the betting of the remainder. Such a race could look like this – let us assume it is a non-handicap:

 

 

We could find that a maiden or a novice chase/hurdle race could be priced up in this way. In this example the second favourite is ideal as one of our each-way double selections, because there will be value in the place part of the bet. The chance of the place based on the bookmaker price is even money (2.0) thanks to the place paying 1/5 of the odds, but in reality, the true chance of placing is much shorter, probably somewhere around the 1.80 mark.

The maths behind proving this is complicated, so I won’t bore you with that, but after the next race I look at I hope you are able to trust me on it. Therefore, allow me to now give a real-life example from a race in October 2024 with a similar market dynamic, because you will be able to see the place value more easily:

 

The ‘shape’ of the market for this race is not quite as good as my hypothetical example purely because the second favourite is only four points clear of the third favourite in the betting. However, the top two in the betting have the same prices (30/100 and 5/1) as in the imaginary race, and if we look at the Betfair place odds we see the following:

 

 

Now I noted earlier that Betfair odds on the win market are as close to true odds as we can find. It is a similar story for the place market, especially for the top two in the betting. Hence in the Sedgefield race we can see that the ‘true’ place price for Path Of Stars was 1.72. Remember the place part of this bet, if successful, would pay 2.0 at the bookies. This gives us the edge as far as the place part of the bet is concerned because the true chance of Path Of Stars placing in percentage terms was 58.1%, a full 8.1% higher than the bookmaker percentage chance of placing which was 50%.

Hopefully that makes sense, and you can see that there can be a place edge to be found given the right race shape / market make-up.

Unfortunately, before one gets too over excited, there is an issue with a possible each-way double even if you are able to find two similar place edges on the same day with the same bookie, which is that we have not considered the bookmaker win odds versus their true odds.

Ideally, we need to find horses that not only have this place edge, but whose exchange price is as close to the bookmaker price as possible. As we know, this does not happen often, but in this real-life example Path Of Stars was only marginally above his bookmaker price of 6.0 on Betfair as the BSP was 6.16. To give you some maths here, the chance of a true 6.0 priced runner winning is 16.7%, a true 6.16 priced runner has a 16.2% chance of winning.

For the record Path Of Stars did not finish in the first two, but that is not the point. The point is that in terms of the place part of the bet, the probability/maths was in our favour and he was very much a value play.

Five-runner races offer the best value from a place perspective when two horses count for places, hence why I chose that field size to try and illustrate my point. Likewise, eight-runner races offer the best value from a place perspective in terms of three placed horses where the bookmakers pay one fifth of the odds. These races also lend themselves to getting that place edge we have seen already. Below is an eight-runner race from 10th October 2024 which was actually a handicap. The race was at Exeter:

 

 

Again, we have a short-priced favourite, and the second favourite War Lord is again priced at 5/1. With 1/5 the odds a place, the second favourite once more has a 2.0 chance of placing according to the bookmaker odds. However, when we look at the Betfair Placed Odds we see that War Lord’s ‘true’ odds are 1.76 not 2.0.

 

 

This type of race offers the same place edge as before. Unfortunately, in this example War Lord’s win price on Betfair was significantly higher at 8.55. On the upside he finished third and did land the place.

At this juncture I should mention that using five- and eight-runner races for these bets has some inherent danger. One non-runner in either would scupper plans instantly as the place terms will be altered essentially turning the bet on its head. The value place bet would suddenly become a very bad value bet. Hence, it may be better to think about six-runner or nine-runner races as an option just in case, even though these are slightly poorer value in place terms. This is assuming of course you can still gain the same type of edge within the place part of the bet.

That’s all for this article. However, my plan is to go into more detail about each-way doubles in a follow up piece. I have spent several hours creating a spreadsheet that can simulate thousands of races where theoretical each-way doubles with specific prices can be placed, and the long-term returns can be calculated based on ‘true’ win and placed percentages.

Why an article solely looking at each-way doubles? Well, as I said, bookmakers hate these types of bet: they know that there can be a place ‘flaw’ in the type of races I have discussed. Bookmakers have been known to close accounts for people they consider to be successful “each-way double thieves”. [If you value your accounts, you’ll have more success placing these bets on the high street!]

Right, I’m off to play with my spreadsheet and I looking forward to sharing some findings with you next time.

-      DR

Irish Trainers in UK National Hunt Racing

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As we start a New Year, I want to examine the performance of Irish trainers when they send runners to the UK, writes Dave Renham. The focus of what follows is National Hunt racing, and I have taken data going back ten years, to 2015. Profits/losses are calculated to both Industry SP and Betfair SP.

Now, I am sure virtually everyone reading this will be aware of the excellent record of Irish trainers versus the British trainers at the Cheltenham Festival in recent years. So let's begin by reviewing this. Subsequently, I will delve deeply into the broader picture to see if there are any angles that, as punters, we may be able to take advantage of.

Cheltenham Festival

This four-day feast of racing will be upon us sooner than we think – March may be two months away, but the time soon flies by. Below is an overall table directly comparing the Irish trainer record at the Cheltenham Festival with their British counterparts.

 

 

It's hardly breaking news, but the Irish have been so dominant in this time frame; they have a much higher strike rate - well over double - and in terms of returns they have trounced the British in at both SP and BSP. It should be noted that Irish trainers outperformed British ones in the ten years prior to that (2005 to 2014), too, but the gap was closer, certainly in terms of win percentage (Irish won 7.9% of races compared to 4.6% for the British).

 

It's time now to start a deeper dive into the overall Irish performance. To begin with here are the stats for all Irish runners in the UK since 2015:

 

 

As the table indicates, there have been blind losses to SP of around 17 pence in the £, but a small 4p return to BSP. Taking the Cheltenham Festival out of the equation produces a small loss to BSP.

Time to drill down into the Irish / UK performance across different parameters...

 

Performance by Year

From this starting point I am going to look at some yearly data. For this I have used a method based on a Nick Mordin idea that I've previously used in recent draw bias articles; this approach helps to avoid individual year fluctuations which can make possible performance changes harder to pick up. I am using rolling four-year timeframes to help spot any patterns. Here are the four-yearly data in terms of returns to BSP.

 

 

The graph shows each four-yearly time frame has produced a profit to BSP which is clearly noteworthy. However, the last couple of years (2023 and 2024) have been losers, hence the recent drop in the 2021-2024 figures. It looks as though the market has now fully 'cottoned on' to current Irish dominance.

Here are the A/E indices using the same principle:

 

The highest A/E index of 0.95 was seen in the period from 2018 to 2021 which coincides with the best period in terms of Betfair SP returns. Also, the recent BSP drop off is mirrored here.

Taking this performance as a whole, the stats are impressive. Irish raiders have consistently made punters money over the past ten years if betting on the exchanges. Of course, there are plenty of big prices that help to inflate these results but, even so, the results are highly noteworthy.

 

Performance by Course

We have seen some course data already in terms of Cheltenham, and its Festival in March. Below are the overall Cheltenham course figures along with any other course that has seen 100 or more Irish runners during this ten-year time frame.

 

 

All of the Cheltenham BSP profit was procured at the Festival. A very small loss has occurred when combining all other Cheltenham meetings together.

In terms of the other courses Aintree is one to mention: runners at the Liverpool track have done extremely well considering the BSP profit is not badly skewed by big priced winners. Indeed, focusing on Irish runners at Aintree priced at 8/1 or less (industry odds), they would have produced a profit to both SP and BSP. Specifically, 57 of them won from 246 qualifiers (SR 23.2%) for an SP profit of £21.86 (ROI +8.9%); to BSP profits were £53.19 (ROI +21.7%). As you would expect a big proportion of these runners ran at the Grand National meeting in April.

Of the lower profile courses, Perth’s positive BSP figures are entirely down to one 200/1+ BSP winner, while Cartmel’s figures are not as bad as you may initially think. When concentrating on horses priced 8/1 or less at SP, Cartmel runners have also seen a small profit to BSP to the tune of £10.05 (ROI +5.2%). The outsiders at Cartmel have been the ones to avoid with 0 wins from 75 for horses priced 14/1 or bigger.

 

Performance by Race type

I would like to compare chases, hurdle races and bumpers (NH Flat) next. Here are the splits:

 

 

 

Hurdle races have produced a healthy profit to BSP, although as one would expect this has included a few big odds successes. There have been five wins at 100/1+ BSP to be precise and all hurdlers priced in three figures have combined to produce around 75% of the hurdling profit. Having said all that, six of the ten years has seen a blind hurdling profit to BSP with two of the four losing years showing very small losses. Focusing on shorter priced runners of 12/1 or shorter would have seen a break-even scenario. Hence, it is fair to say Irish hurdlers have performed well as an overall group. Before moving away from this section, both non-handicaps and handicaps have offered positive hurdling returns. Non-handicappers have returned 16p in the £, handicappers 9p.

 

Performance by Industry SP

A look at the results in terms of SP prices now.

 

 

There have been only small losses for shorter priced runners (5/2 or shorter). One can surmise that with a little bit of additional form study one could probably have narrowed down this group of runners in terms of which ones to back, with the potential to edge into profit as a result.

At the other end of the spectrum, horses priced 28/1 or bigger would have secured a very big profit if backing them all to Betfair SP. This will come as no surprise based on the information shared to date in this article about some big prices having gone in. While I am sure many of you are writing off the idea of backing such big-priced runners due to the fact that for such a method to work you probably need let’s say those monster 100/1+ winners hitting the mark more than they statistically should; or at least the prices of most of the winners offering value. However, the point is that one or both of the above has happened.

If we compare the results of horses priced 28/1+ in terms of British runners versus Irish runners, we see that British horses have won less than 1% of the time (0.97%) and produced losses of 56p in the £ to SP, and losses of 20p in the £ to BSP. Irish-trained runners priced 28/1+, as the figures in the table show, have won over 1.7 times more often than their British counterparts and the returns have been better by 39p and 63p in the £ respectively.

Of course, it takes a brave person with a large betting bank playing to small stakes to back very big odds runners regularly. Huge losing runs undermine confidence and if the tank is not set up appropriately, it could easily run dry. However, I found that this has not been a one-off after checking the record of Irish runners priced 28/1 or bigger from an earlier time frame (2008 to 2014). I haven’t gone back further in time because 2008 was the first full year that the Betfair Starting Price was used. Overall, during these seven years the bigger priced Irish raiders won 1.51% of the time (17 wins from 1127) for a profit to BSP of £725.31 (ROI +64.4%). Excellent overall returns once again – hence I am wondering whether anyone might be tempted to back such runners in the future. I, for one, will be keeping tabs on it.

 

Performance by Race Class

I want now to assess the class of race and whether it makes any difference either positively or negatively with regards to Irish performance in UK NH racing. Let me share the Betfair SP Return on Investment percentages (ROI%):

 

 

The chart has the highest classes of race on the left, starting with Class 1 races, moving through to the lowest class of race on the right, namely Class 6. It seems the better the class of race the more profitable for backers of Irish runners. Put simply, the highest three classes have produced profits, the lowest three losses. The BSP results for the two lowest Classes (5 and 6) have produced significant losses and it looks best to avoid these races.

If we look into Class 1 races in more depth, we see that Irish runners in all three types of Graded race (1, 2 and 3) have made a profit.

 

 

Don’t be put off by the low Grade 3 win strike rate as these contests, all handicaps, have averaged 20 runners per race over the past ten years. The class / graded data suggests to me that the Irish target the better races with higher prize money. That makes sense given the travelling costs and so on.

Before moving on I want to compare these Graded results to the record of British-trained runners during this period. Firstly, let me compare the strike rates, both win and each way:

 

 

Irish runners are ahead in all six comparisons and significantly so in Grade 1 and 2 contests. Now let me compare their A/E indices:

 

Again, the Irish runners have been completely dominant over their British counterparts offering better value across the board.

 

Performance by trainer

Trainer data is always popular so I will share the results for all Irish trainers who have sent 100+ runners to contest UK National Hunt races during this time frame, as long as they had at least one runner in 2024. The table is ordered by win strike rate.

 

 

The big guns of Willie Mullins and Gordon Elliott have sent a significant number of runners across the pond with good success. However, making a profit from either is not so easy due to their reputations; rheir runners do not go unbacked very often.

A few trainers in the list have shown a profit to BSP, but Gavin Cromwell and John McConnell’s results are the most impressive as they have not had a huge BSP winner to skew their results. Here are some additional stats for these two starting with Cromwell:

1. Cromwell has sent 36 runners to the Cheltenham Festival during the study period, of which six won (SR 16.7%) for a profit to SP of £20.63 (ROI +57.3%). This increases if backing to BSP to the tune of £36.20 (ROI +100.5%)

2. Sticking with Cheltenham, Cromwell's record at all other meetings at the course stands at 10 wins from 45 (SR 22.2%). Profits to SP have been £7.60 (ROI +16.9%), to BSP £11.36 (ROI +25.2%)

3. LTO winners from the stable have fared exceptionally well thanks to a 25% strike rate (16 wins from 64). Returns to SP were nearly 66p in the £, to BSP this increases to over 90p

4. Horses that started in the top two of the betting won 33 times from 105 runners (SR 31.4%) for a profit to SP of £8.74 (ROI +8.3%); to BSP £15.34 (ROI +14.6%)

 

Now onto McConnell:

1. Horses that finished in the first three LTO have been worth following thanks to 50 wins from 167 runners (SR 29.9%) for an SP profit of £23.22 (ROI +13.9%). To BSP this improves to £46.15 (ROI +27.6%)

2. McConnell's male runners have won almost twice as often as his female runners (26.6% versus 13.7%)

3. Horses that started favourite made a small SP profit of £8.16 (ROI +10.2%) thanks to a strike rate of 52.5% (42 wins from 80). Returns to BSP have edged up to just over 14p in the £

4. Hexham has been a good course for McConnell with 11 wins from 22 (SR 50%). He is only one win from 24 at the Cheltenham Festival, but at all other Cheltenham meetings combined he has saddled 10 winners from 44 (SR 22.7%) for an SP profit to £26.88 (ROI +61.1%); to BSP +£43.06 (ROI +97.9%)

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I hope this article has offered up some potential betting angles on Irish runners. It is widely known how well Irish runners perform at the Cheltenham Festival, but they also have competed extremely well at Aintree. In fact, Irish-trained horses' performance at Aintree is arguably more impressive than it has been at Cheltenham.

Bigger priced runners sent from Ireland to UK should not be totally written off as far more have won than statistically they should. Graded events have seen the Irish enjoy a clear advantage over British-trained runners, while the lower classes of 5 and 6 are generally races to avoid from an Irish perspective. There are two trainers that are worth keeping a particular eye on, namely John McConnell and Gavin Cromwell.

We have all heard the saying ‘the luck of the Irish’ but I think in UK NH racing terms there is a good bit more to it than that.

- DR

Starting 2025 on the Front Foot

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As we approach the end of another year, which for me seems to have gone even quicker than previous years, many of us will be examining our betting ledger and working out how we can improve in the next twelve months, writes Dave Renham. We need to understand what has worked, and what hasn’t, and tweak accordingly.

As January 1st, 2025 looms, I am sure there will be an optimistic feel across the punting community, as there will be amongst much of the training ranks, too. In this article I want to see if I can find any key trainer patterns that have occurred in the first two weeks of the year going back to 2017. To assist, I have carefully harvested trainer data from Jan 1st to Jan 14th, for the past eight years. Who starts the year quickly? Who has a Christmas hangover? I wasn’t sure if I would find anything useful but if one doesn’t dig, one doesn’t find out!

Profits/losses have been calculated to Betfair Starting Price (BSP) less 5% commission.

Overall Trainer Angles

Let me first look at the trainers with the 20 best strike rates (to qualify – 60 runners minimum):

 

 

Positive Trainer Angles

It was a surprise to see Sue Smith top the list when you consider her overall 2017-2024 strike rate stands at 11.2%. She averages only 8 to 9 runners per year in these first two weeks but nevertheless in five of the eight seasons her strike rate has hit 30%+, and two of the other three were over 20%. 2024 was a poor year by her standards with just one winner from 13, but she hit the post with a BSP 12.48 shot who finished 2nd and she had a close-up 3rd at huge odds of 73.80.

These findings encouraged me to look at Sue Smith’s record by month going back to 2017. Below is a graph plotting strike rates, both win and each way, by month. I have grouped May to September together as each month within this bracket had modest to small sample sizes, as well as basically being the ‘off’/summer season.

 

 

From my perspective this graph illustrates three things – firstly, how clearly the whole of January (not just the opening two weeks) stands head and shoulders above the rest. Secondly, that the stable takes time to come to hand at the start of each season but by December there is improvement, and this is carried through to February before it starts to tail off slightly once more. Thirdly, the form of the stable from May through to November is modest at best and I would be wary of backing any runner during this period. Before moving on, it should be noted that since the end of October 2024 Sue Smith has teamed up with Joel Parkinson so when looking for runners/results on Geegeez from that stable, you now need to look for ‘J Parkinson + S Smith’.

Going back to the first table, the Geegeez-sponsored yard of Anthony Honeyball lies in second place in terms of strike rate. It should be noted though that the last couple of years has seen a dip in success; overall, however, there are excuses as he has saddled fewer fancied runners in that time frame. If we focus on horses that were in the top three of the betting, these first two weeks of the year have been excellent for the Honeyball stable. This subset of runners has won 16 times from 36 qualifiers (SR 44.4%) for a BSP profit of £23.00 (ROI +63.9%).

Nicky Henderson lies in third place and has been consistently hitting strike rates of over 23% in six of the eight years. Only 2022 saw a really below par effort when he had just two winners from 30 (SR 6.7%). The horses to focus on for Henderson in these first two weeks are, as with Honeyball, those that started in the top three of the betting. These runners have won 53 of 143 starts (SR 37.1%) for a profit of £21.33 (ROI +14.9%).

Brian Ellison is another who has performed well in terms of wins to runs during the first two weeks of the year. Any runners at Sedgefield would have required close scrutiny thanks to eight wins from 15 but, typically, there is no Sedgefield meeting scheduled for the first two weeks of 2025! However, there is another strong Ellison stat that will have relevance which focuses on horses that finished in the top five LTO. These runners have won 13 of the 48 races (SR 27.1%) in early January for a profit of £67.89 (ROI +141.4%). It should also be noted that over the rest of the year runners from his yard that finished in the first five LTO have won 17% of their races, well below this 27.1% figure.

The start of January does seem to ignite the Ellison fires because his form in November and December is traditionally poor. Below is a graph comparing the A/E indices for the Ellison stable for the whole of January (not just the first two weeks) with November and December.

 

 

For the record, his strike rate in November over the past eight seasons has been 6.6%, for December 8.5%, but for January 21.9%.

Scottish trainer Sandy Thomson is yet another trainer who has traditionally started the year well, hitting close to a 23% strike rate. He has fared particularly well at Ayr and here are all his runners catalogued. To make things stand out the winners are in red, the placed horses in orange.

 

 

His record at Ayr in the first fortnight of the year is eight wins from 21 (SR 38.1%), with a further four placed. Profits to BSP stand at £12.33 (ROI +58.7%). As can be seen there are no big wins skewing the results, indeed the biggest winning BSP was just 7.00. There are two meetings scheduled at Ayr for early January so keep your eyes peeled for any of his runners.

Thomson has also done especially well in handicap races winning 15 of the 59 contests (SR 25.4%) for a profit to the machine of £15.87 (ROI +26.9%). Again, no big winners to skew the profits. Not only that, if you focus in on stable jockey Ryan Mania only in these handicaps the record improves to 12 wins from 31 (SR 38.7%) for a profit of £29.74 (ROI +95.9%). Thomson does look a trainer to keep an eye on in these two weeks, especially handicappers ridden by Mania, or any runners at Ayr.

Olly Murphy is another trainer with a good strike rate and excellent returns. What particularly impressed me was that he has had winners at 19 different courses and drawn a blank at just seven others. He has sent a sole runner to four tracks – Fontwell, Ffos Las, Plumpton and Sedgefield - and all four won. Murphy is also three from three at Bangor. Of those seven courses without a winner he has sent single figures in terms of runners to each. For the record, he has only had two runners at Kelso, three at Southwell, four at Wincanton and five apiece at Taunton and Donny, six at Chepstow and eight at Kempton.

Negative Trainer Angles

On the flip side, there are some trainers who seem to have a hangover from Christmas as the New Year starts. Kim Bailey is in this camp having sent out just 11 winners from 115 (SR 9.6%) for hefty losses of £78.07 (ROI -67.9%). The prices of his horses have been similar to those in any other period of the year, indeed 60% of his runners were in the top four of the betting. Digging deeper, if we ignore bumper races and focus on chase and hurdle races only Bailey’s record looks even worse – just seven wins from 99 (SR 7.1%) for losses of £78.64 (ROI +79.4%).

I felt it worthwhile to look at Bailey's monthly strike rates (both win and each way) as with Sue Smith earlier, to see how January as a whole fits into his overall monthly profile.

 

 

As with Sue Smith I combined the summer months (May to September) as one. January as a whole (not just the first 14 days) has been comfortably the worst month; not only the win strike rate but the each way strike rate too. The A/E index for January is down at 0.61 and losses were 24p in the £ worse than the second worst month.

Sometimes, as we know, trainer stats can be skewed due to prices / market position etc. Below, then, is a table of Kim Bailey’s monthly performance with horses from the top three in the betting:

 

 

As might have been expected based on the previous evidence, January’s performance is the worst. Compare that with the outstanding October record where the strike rate is basically double that of January with returns of nearly 50p in the £.

Looking at monthly data for trainers can be useful, especially as some do seem to display clear patterns. Bailey is one such handler, starting the season strongly in October and keeping that going into November as well. A slight dip in December is followed by a bigger blip in January after which he recovers with solid months from February to April. It seems the months of May to September are less important to the stable.

David Pipe is another trainer who has struggled to kick start the New Year with a high level of success. He has saddled just 13 winners from 154 runners (SR 8.4%) for a BSP loss of £75.20 (ROI -48.8%). One subset of his runners that have performed particularly poorly are his runners aged 8 or older, which collectively recorded just one win from 62 (SR 1.6%) for losses of over 82 pence in the £.

Of these runners less than half of them were bigger than 10/1 Industry SP, so it’s not as though they were all outsiders – far from it. A couple more negatives for Pipe in this period relate to individual courses: at Taunton he is 0 from 27, and at Plumpton one from 20 with nine of the remaining 19 runners failing to complete the course. Plumpton has two New Year meetings scheduled, for the 5th and 14th January 2025, and I personally will not be backing any Pipe runner regardless of how strong other factors may be.

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I hope this article will contribute to you getting a head start as we tackle the first days of 2025. Beginning the year strongly from a punting perspective can offer us more confidence to tackle the year as a whole, so good luck with your betting and may I wish you a Very Happy New Year.

- DR

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