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Is Recent Trainer Form Important?

20 March 2024/in Dave Renham/by Dave Renham

Spring is upon us, and the turf flat kicks off this weekend, writes Dave Renham. It is my favourite time of the year as all of my winter research can be unleashed in an attempt to hammer the bookies! Of course, despite all the hard work put in it, it does not guarantee profits for the year ahead. No doubt it will be the usual rollercoaster of good weeks, bad weeks, and indifferent ones. Hopefully, though, there will be more good than bad!

In this article I am going to investigate recent trainer form to see what I can unearth. Newspapers, betting sites and some pundits seem to place a lot of stock in trainer form; I must admit that I tend not to, but I am prepared to change my mind depending on what I discover: have I been missing a trick all these years? Let’s see.

I have taken flat and all-weather data from 2021 to 2023 for UK racing and profits/losses have been calculated to Betfair Starting Price less 5% commission (readers can do better than those results by selecting the 2% commission option in your Betfair account).

My focus is going to be on 14-day trainer form, but with a caveat. The caveat is that a trainer must have had at least 20 runners during that time frame. I’m adding this to make sure we eliminate small samples which are unreliable.

To try and explain how small samples can be unreliable, a trainer could theoretically have had five runners in a 14-day period with one win and four losers giving them a recent win strike rate of 20%. Generally, a strike rate of 20% for trainers at any time is considered very good. However, firstly that 20% strike rate is based on very limited data. Secondly, let us imagine all five runners had been odds-on favourite – that would not be crying out good trainer form. To be clear, I’m not suggesting that 20 runners in a 14-day period is the perfect number of runs, but it seems as sensible an arbitrary figure as any.

General 'Recent Form' Trainer Statistics

Time to review the first set of data. Here, I am looking at trainer strike rates – both win and each way linking with the win percentage individual trainers had achieved in the previous 14 days.

This initial piece of evidence suggests, at least from a strike rate angle, that trainers who had been in better form over the past 14 days outperform those whose recent form had been less good. Both the orange line (Win SR%) and the blue one (EW SR%) show solid correlation with the graph, on an upward trajectory.

However, as a recent article of mine suggested, strike rates are not the be all and end all; we need to look at value and profit / loss. The table below gives us a breakdown of this:

This presents a less clear picture but, looking at the returns, the trainers who have scored 5% or less with their last 20+ runners over the most recent two-week period have provided the worst returns. Looking at the trainers with the highest recent strike rate (31% or more), it appears that the betting market has compensated for this to a great extent given losses of more than 13p in the £.

Of course, the data shared so far looks at all trainers combined. This gives us a general starting point, but to get a better overall perspective we need to split the trainers into groups. This is because comparing the 14-day win strike rate of Charlie Appleby, say, with Liam Bailey makes little sense. Appleby has a 29.6% strike rate during the time frame compared to Bailey’s 4.3%. In addition, Appleby’s A/E index of 0.94 is nearly double that of Bailey whose figure stands at 0.48. Hence in a scenario when Appleby and Bailey have secured a 15%-win strike rate in the past 14 days, we should be aware that Bailey is performing well above his norm and Appleby well below. Looking at all trainer data therefore gives us a flavour but cannot paint the full picture.

To mitigate somewhat for this, I am going to consider split trainers into groups based on their annual win rate while analysing recent form (14-day results).

I have split them into five groups: those with an annual strike rate of 8% or less, those between 9% and 12%, 13% to 16%, 17% to 20%, and finally trainers winning at a rate of 21% or more.

Trainers with a yearly win strike rate of 8% or less

Looking at all trainers who had run at least 200 runners from 2021 to 2023, around a fifth of them had an overall win strike rate of 8% or less. With this group I would not expect to see many qualifiers in the higher 14-day strike rate groupings.

The biggest group of qualifiers has occurred in the 6-10% 14-day strike rate (SR%) bracket and they have made a BSP profit. However, this is down to two unusually big-priced winners of 451.93 and 350.0 which skew the figures considerably. What is clear is that once trainers in this group hit 16% or more with 20+ runners in a 14-day period they do start to have better results. Combining the results of the 16%+ group they have returned 10p in the £ with a solid A/E index of 0.93 from a sample of around 400 runners.

Trainers with a yearly win strike rate of between 9% and 12%

This group of trainers is the biggest and includes runners from the stables of Richard Hannon, Richard Fahey, David O’Meara, Kevin Ryan, and Jim Goldie to name but five. Let us look at the overall win and each way strike rate first:

The graph shows that this group of trainers have performed quite poorly in terms of win strike rate if their 14-day Win SR% had been between 21 and 30%, which is surprising. I expected the orange and blue lines to rise gradually and relatively smoothly from left to right.

When we compare the A/E indices we see a similar pattern:

Combining the runners from the 21-25% group and the 26-30% group would have lost over 16p in the £ to BSP. Even the 31%+ group lost 15p in the £ despite a decent A/E index. It seems that the market is aware when these types of trainers are showing good recent form and prices have been more than adjusted to account for it. Here is a tabular view of this group:

The 0% group has performed better than expected. However, as we will see, this turns out to be an outlier when considering the rest of the research I share.

Trainers with a yearly win strike rate of between 13% and 16%

This group of trainers includes Charlie Johnston, Archie Watson, and Clive Cox. Here are their stats:

There are better strike rates across each grouping as we would expect from higher general strike rate trainers, but these handlers look worth avoiding if they have had no winners from 20+ runners in the past 14 days. Losses of over 26p in the £ is steep albeir on a smaller sample size.

The picture is not much brighter at the other end of the scale – trainers that seem to be in flying form with a 14-day SR% of 31% or more have made losses of over 14p in the £. Their strike rate is relatively poor, too, at 15.09% and their A/E index a modest 0.86. These are the two key discoveries from what is essentially another mixed bag of findings.

Trainers with a yearly win strike rate of between 17% and 20%

Let’s see if this smaller group of trainers can give us some stronger patterns. Ralph Beckett and Sir Michael Stoute are two trainers who are included here in the following results:

When these trainers are out of form (14-day SR% of 5% or less) they look worth avoiding. Combining the top two rows of data we see significant losses of 27p in the £. Conversely, when they hit the dizzy heights of 31% winners or better in the past 14 days this cohort has edged into profit. I would guess that it will come as less of a surprise for such trainers to hit these levels from time to time and perhaps the market has failed to properly adjust.

Overall, these stats are strong with a decent strike rate of close to one in four, returns of over 7p in the £ and an excellent A/E index of 1.04. In general, these stats correlate better with what I would have expected to see.

Trainers with a yearly win strike rate of 21% or more

We are now looking at a very select band of trainers including Charlie Appleby and Willie Haggas. Here are their win strike rates based on recent form:

I want to focus on win percentages (hence no EW ones on this graph) to help illustrate how little difference there is in some of the numbers. For example, when this group of trainers had previously had a 6-10% win SR% over the past 14 days their win rate was 19.8%. When it was 21-25% in the previous 14 days their win rate was virtually the same at 19.9%. Let me share the fuller picture:

The first thing to point out is that a 14-day SR% of 5% or less is extremely rare in this collective, as one would expect. Secondly, I want to highlight the poor performance of the 31%+ group which incurred losses of over 18p in the £ and produced a disappointing A/E index of just 0.83.

There is no easy explanation as to why the 26-30% group have fared so well in comparison. My reading of the data is that when these yards seem a little under par (previous 14-day SR% of 11 to 20%) their runners may offer a little bit of value. I guess punters could be put off by the relatively modest recent strike rate, but essentially these runners are still scoring close to each trainer’s norm.

At this juncture the picture is quite muddy when it comes to 14-day trainer form. The strongest and most important finding is that we can say that a 14-day win SR% percentage of 5% or less is a negative.

Individual 'Recent Form' Trainer Statistics

It is time now to look at individual trainers. With each trainer plying their trade in a different way, one would hope there might be more insights to glean here. Fifty of the leading trainers are shown in the table below in terms of their win strike rate (missing cells are due to limited data):

Before going into more detail let me share their A/E indices with you as well. I have colour coded the A/E indices with positive figures of 1.00 or more in green and negative ones of 0.70 or less in red.

Individual Trainer Angles to Note

These are what I think are the most significant findings:

Andrew Balding does unexpectedly well when his recent 14-day SR% is less than 5% returning 37p in the £ on all runners. He also made a BSP profit with his 6-10% group.

Ralph Beckett looks a stable to follow when he hits the 14-day win SR% of 26% or more. An A/E index of 1.05 and a small profit to boot.

The Crisford stable has a bizarre set of strike rates and A/E indices:

Both metrics correlate with each other which gives us confidence in the findings, but the data is suggesting that the poorer the recent form of the stable the better.

Don’t be put off by low recent 14-day win strike rates for Eve Johnson Houghton. When her strike rate was 5% or less in the previous two weeks her runners have offered good value. Backing all runners blind in this context would have secured a small profit.

When Alan King’s 14-day SR% has been between 21% and 25% he has managed just one winner from 62 runners. Losses of 90p in the £ would have been recorded backing horses from a so called ‘hot’ stable.

Daniel Mark Loughnane has the type of profile I was expecting more of. When his 14-day SR% is 5% or less his record is very poor. When it hits 26% or more his record has been excellent. He does a look a clear case of “avoid when his stable is cold, take advantage when the stable is hot”.

When the Kevin Ryan stable is out of form, his runners are probably worth swerving, especially if he has failed to record a winner from 20+ runners in the previous 14 days.

Saeed Bin Suroor’s A/E indices for the four groupings in which he has enough data are all above 0.90 suggesting his stable perform in a similar vein regardless of very recent form.

Grant Tuer shows a similar pattern to Crisford implying that the poorer the recent form of the stable the better from a betting perspective.

Summary

So, what are the main takeaways from this research? When looking at the general picture, I think the data indicate that poor 14-day form has more of an effect on performance than good 14-day form. ‘Cold’ stables with 14-day win rates of 5% or less from 20+ runners are best avoided (with a few individual exceptions).

In terms of when a stable has been ‘hot’ over the past 14 days we see an uptick in win rate, but this does not guarantee value or profitability due to such form being fully exposed in the market.

Regarding when a ‘hot’ trainer should potentially be followed I would use the individual trainer table of A/E indices looking for figures close to, or greater than, 1.00.

I plan to revisit this idea in the future, looking at a slightly longer prior time frame to see what difference, if any, that makes. I could also delve into NH trainer stats as well. But that’s for another day. I hope you have enjoyed this piece, and good luck with your early flat season betting.

Dave Renham: NH Q&A

14 November 2023/in Dave Renham/by Dave Renham

This article is slightly different from my usual pieces in that I am going to address some of the questions you have asked in the comments over the past couple of years, writes Dave Renham.

As the turf flat season has come to an end, I will concentrate on some of the National Hunt questions that have been posed. Any profit and loss figures quoted have been calculated to Betfair Starting Price less 5% commission. Data have been taken from UK NH racing going back to 1^st Jan 2017. Here we go...

Does the market position of the horse on debut make any difference in their next few runs?

For this answer I am going to combine the stats for all horses having their second, third, fourth and fifth careers starts. Horses that were favourite on their debut have gone on to win just under 20% of the time when grouping together all the results of their next four races. The graph below shows the second to fifth run combined strike rate for different market positions on debut:

The graph shows that the position a horse appears in the betting market on debut has an influence on their success early in their careers. In terms of returns, favourites on debut have got close to breaking even if you had backed them in all of their next four starts. Compare this to horses that that were 5^th or higher in the betting market on debut – they would have combined to lose you over 20 pence in the £.

How successful are beaten favourites on their next start?

Horses that were beaten favourites last time out scored in 18.6% of their next starts; but backing all qualifiers would have produced a loss of 6p for every £1 staked. Looking at horses that were beaten favourite two starts back, they have produced a strike rate of 17.3% with slightly higher losses of 7p in the £.

Horses that have been beaten favourites on both of their last two starts have won just under 20% of the time, but losses have been steeper at 9p in the £. These are generally worth swerving!

Is wearing blinkers for the first time a positive or a negative?

Trainers turn to headgear in an attempt to make it easier for the horse to focus on what is in front of them rather than being distracted by other horses or the crowd etc in their peripheral vision. Hence, trainers hope that the application of blinkers will help the horse concentrate better and thus perform better. However, the stats point to the fact that horses in first time blinkers are a negative.

First time blinker wearers have won 8.5% of their races (205 wins from 2402 runs) producing losses of £367.95 (ROI -15.3%). One positive stat worth sharing is that if the horse was prominent in the betting (SP of 9/4 or less), this subset of first time wearers made a profit, albeit from a small sample. There were 104 qualifying horses of which 49 won (SR 47.1%) for a profit of £28.75 (ROI +27.6%).

Trainer Gary Moore has a good record with horses wearing blinkers for the first time scoring 7 times from 28 Runners (SR 25%) for a profit of £30.27 (ROI +108.1%). Yes, it is a very small sample but there are two other positives I can share. Firstly, seven other runners were placed, giving Moore a win and placed strike rate of 50%; and secondly, I checked his 2013 to 2016 results also and he won 5 from 18 (SR 27.8%) for a profit of £30.42 (ROI +169.03).

Of course, there are other headgear options and the application of first time cheekpieces has produced much better overall results than first time blinkers. The stats show that 10.7% of these runners won and losses stood at only 1.2% - or just over 1 p in the £ lost for every £1 staked.

How does the weight a horse carries in a handicap chase affect the result?

Horses are assigned different handicap marks in handicap races which affects how much weight a horse will carry. Better horses with higher handicap marks (Official Ratings) carry more weight. The idea is that the weight will balance out the differences in ability with the theory that any handicap race will end with all runners finishing at the same time. The handicapper does an excellent job, but higher weighted horses still win more often than lower weighted runners. The graph below shows this:

Top weights in handicap chases are more than twice as likely to win as horses weighted 7^th or lower. However, the market does adjust for this. Top weights, despite their decent win rate, would have lost you around 7 pence in the £ if backing all of them ‘blind’. Horses that were 7^th or lower in the weights actually turned a small BSP profit. Of course, a few big-priced winners did skew these results somewhat, but even without those you could legitimately argue that lower weighted horses offer slightly better value in these races.

What percentage of races are won by a horse from the top three in the betting?

When combining the results of all National Hunt races, the winner comes from the top three in the betting in 73% of races. However, there is a big variance depending on type of race. Here is a table showing the performance of the top three in the betting in different race types. I have ordered the table row from highest percentage to lowest:

Handicap races are generally more competitive than non-handicaps which is one of the reasons why the lowest figures are for the handicap groups. Having said that, field size plays a part and handicaps tend to have bigger fields which naturally impacts the percentages. In terms of returns, horses from the top three in the betting have performed best in non-handicap novice chases – these runners would have lost you just 1p for every £10 bet (ROI -0.1%).

Have you any breeding stats that will help with my National Hunt betting?

Here are my favourite stats connected with breeding.

When looking at French-bred runners, did you know that female horses have outperformed male horses in terms of strike rate? This is unusual as male horses have a general strike rate edge over female runners in all types of racing be it flat, all weather or National Hunt. French-bred runners that are female have won 13.72% of their races; males have won 13.57%. Females have provided by far the best value of the two also – males would have lost you 9p in the £; females would have won you 14p in the £. I should also say that French-bred females have a strike rate edge in both hurdle races and chases. Male French-bred runners enjoy a small edge in bumpers.
There are a handful of sires whose chase record is considerably better than their hurdles one. Muhtathir is one such sire. His chase SR% stands at 18% while his hurdle one is just 7.9%. In terms of A/E indices, his chase index is 1.04, his hurdle one is just 0.61. Another sire with a similar bias is Schiaparelli. His hurdle SR% has been 9.3% (A/E 0.79); his chase SR% more than double that at 18.9% (A/E 1.02). Fuisse has similar stats to Schiaparelli – he has a 21.4% strike rate in chases (A/E 1.14), in hurdles this drops to 11.9% (A/E 0.81). Both Fuisse and Schiaparelli have made blind profits in chases to BSP.
Sire Trans Island performs much better in hurdle races compared to chases. Strike rates are 13% (hurdle races) versus 8% (chases) with the A/E indices standing at 1.10 and 0.70 respectively. Coastal Path is another sire who seems to have a clear edge when comparing hurdle results to chase ones. In chases he has a 12.1% SR% with his runners showing hefty losses of 44p in the £; in hurdle races the strike rate is 17.7% and his runners have made a blind profit of £322.48 (ROI +107.9%).
Poliglote is a sire that only has a handful of hurdlers these days, but he is the only sire to secure a strike rate of over 20% in these races over the lesser obstacles (44 wins from 215 runners). Returns of 73 pence in the £ is noteworthy and hence any hurdler sired by Poliglote is worth close scrutiny.

Are there any trainers who do particularly well in bumpers?

Let’s start by looking at the trainers with the highest strike rates in bumpers. In order for them to qualify they must have had at least 75 runners and achieved a 20% win rate or higher:

It will probably come as no surprise to see Paul Nicholls and Nicky Henderson at the top. However, neither have made an overall profit, losing 4p and 5p in the £ respectively. There is a profitable angle for both Nicholls and Henderson though when we dig a bit deeper into the numbers – and it is the same angle. For both trainers you would have made a profit if ignoring horses on debut and those with just one run under their belt. For Henderson, horses having their second or more career start have won 20 races from 79 (SR 25.3%) for a profit of £23.13 (ROI +29.3%); for Nicholls he has had 21 winners from 69 (SR 30.4%) showing a profit of £18.79 (ROI +27.2%).

There is one more trainer I would like to mention who does not appear on the above graph and that is Hughie Morrison. Morrison is probably better known as a trainer on the level, but he has an excellent record albeit from a smaller sample. He has had 58 bumper runners since 2017 of which 14 have won (SR 24.1%) recording a profit of £24.87 (ROI +42.9%). In fact, 7 of his last 19 runners (SR 36.8%) have won.

Sticking a little bit longer with bumpers, there are two trainers who have done particularly well with bumper debutants. Harry Fry and Anthony Honeyball are the trainers in question. Their figures are impressive:

Both trainers have been consistent, each making a profit in five of the seven seasons.

Which trainers do best with horses that make their career debut in a hurdle race?

Just under 70% of all National Hunt horses have their first ever run in a bumper. However, a good proportion start off their careers by ignoring the bumper route and going straight over hurdles. One trainer excels with these runners, namely Nicky Henderson. His record is outstanding:

The win strike rate is on another stratosphere with only two other trainers hitting over 20% (20% and 26% for Donald McCain and Paul Nicholls respectively). His biggest priced winner has been at 11/1 (BSP 17) so his results are not skewed in any way. Henderson also seems to target hurdle races at Newbury as 11 of his 18 runners (SR 61.1%) have won there on debut.

There are two stables to avoid, however, when they send an unraced horse over hurdles for their debut. Firstly, Venetia Williams has saddled just three winners from 52 (SR 5.8%) for a loss of £35.65 (ROI -68.6%). In fact, 31 of these runners started at single figure odds so this is not a case of lots of outsiders losing. The other stable to avoid is the Oliver Greenall and Josh Guerriero yard. They have managed just two winners from 64 runners (SR 3.1%) for a hefty loss of £52.38 (ROI -81.8%). In truth, a fair proportion of their runners have been at the higher end of the price spectrum, but regardless of price I think a wide berth is the prudent call.

At the Cheltenham Festival Irish trainers seem to excel. What is the record of Irish trainers in all UK National Hunt Races?

Here are the stats for all Irish trained runners in the UK going back to 2017:

This is an impressive set of figures. Having said that, 80% of the profits occurred at the Cheltenham Festival from around 28% of the total runners.

The Irish seem to target the better meetings and the bigger prizes. There are four courses where they have had at least 200 runners – all four have seen a blind profit as the table below shows:

It is no surprise that Cheltenham has seen the best returns, but the Perth stats are strong, too. It makes sense to me that when you see an Irish runner declared at any of these four tracks you should look carefully into their chances. If the race is a class 1 or 2 contest, then that has also been a positive.

Trainers with sole runners on the day – are any worth following?

The penultimate question for this piece concerns trainers who have had just one runner racing on a particular day. Firstly, let us see the trainers with the best strike rates with these sole runners.

The usual suspects of Nicholls and Henderson head the list, but it is interesting to see Ann Hamilton in fourth place. Six of the ten earned a blind profit – Henderson, Skelton, Hamilton, Richards, Lacey and Bailey. As far as Henderson is concerned, if you ignored his runners that started favourite, his record is mightily impressive with 53 wins from 249 runners (SR 21.3%) for a profit of £117.99 (ROI +47.4%). This subset of runners would have yielded a profit in six of the seven years.

What is the comparison of novice chase debutants with horses having their second chase start in a novice chase?

This is a very recent question which was asked after I wrote a piece on chase debutants. I was asked about trainer improvement between chase debut in a novice chase and the second chase start in a novice chase. Horses that are racing for the first or second time often contest novice chase events so there is a reasonable data set for some trainers.

Firstly, let me compare the overall strike rates in novice chases between horses having their first ever chase run compared with those contesting a novice chase having only their second run over fences:

As you can see, and might expect, horses improve for the experience. Remarkably, horses having their second chase run have made a blind profit when they raced in a novice chase on this second start. That 18% strike rate has helped turn a 7p in the £ profit.

Now to compare trainer performance. Below is a table displaying individual trainer strike rates on chase debut and 2^nd chase run. Once again, these figures apply only when the race in question was a novice chase. To qualify each trainer has had at least 30 runs for each group. I have also created an extra column where I have divided the 2^nd run SR% by the debut SR%. To show an improvement this figure needs to be higher than 1.00. I have ordered the table by ‘improvement’:

Tim Vaughan has shown a remarkable improvement going from 4 wins from 72 on debut to 9 wins from 33 on second start. There is also a significant differential when comparing the Evan Williams stats. There are very few trainers whose chase debutants out-perform their second chase starters but there are a handful (at the bottom of the table). I hope this table will prove useful to assess how likely a horse is to improve from chase debut to second chase run.

As stated, this final question has been geared to novice chase data only. Not all first- and second-time chasers race in a novice chase. Hence you would get bigger data sets if you allowed ‘all chases’ to be analysed for these two groups of runners. Having said that, I have looked briefly at that data, too, and the results for most of the above trainers are similar.

So, there you have it – a selection of answers to the many questions I have been asked about National Hunt racing in recent times. If you have any specific questions, please post them in the comments. It might inspire a new article!

- DR

Jockey Profiles: Ryan Moore

7 June 2023/in Dave Renham/by Dave Renham

The second in my series of articles on jockeys and, this time, Ryan Moore comes under the microscope.

Ryan Moore Introduction

Ryan Moore was born in Brighton in 1983 and he rode his first winner in the year 2000. Three years later, he broke through the 50 winners in a year barrier and, in 2004, he notched up his first century (132). In his early career he rode primarily for Richard Hannon but, by the mid-2000s, Moore was getting an increasing number of rides for Sir Michael Stoute. It was for Sir Michael that he recorded his first Group 1 success with Notnowcato in the Juddmonte Stakes at York in August 2006. In 2011 he started being noticed by Aidan O’Brien and, by 2016, he had ridden over 100 times in a season for the Irish maestro in the UK and Ireland combined. The Coolmore Stud provided the vast majority of these rides from the Ballydoyle handler, giving Moore the opportunity to ride some of the very top horses in training. In 2017 he secured his 2000^th British winner and Moore is a definitely a jockey who justifies a deep dive into his statistical performance.

As with the Hollie Doyle piece I have analysed the last eight full years of flat racing in the UK and Ireland (2015-2023). I have used the Profiler Tool along with the Query Tool as the main vehicles for my data gathering. In all the tables profit/loss quoted is to Industry SP, but I will quote Betfair SP where appropriate.

Ryan Moore: Overall Record

Let's first look at Moore’s overall stats by reviewing his performance on every single runner during this eight-year period:

An excellent strike rate for Moore, in excess of one win in every five, primarily due to the fact that a sizable percentage of his rides are on fancied runners at shorter prices. This market detail also partly accounts for the fact that the PRB figure is very high at 0.63. His A/E index, a ratio that essentially determines value, is around the average for all jockeys.

We can also see that backing all his rides blind would have secured losses of nearly 21p in the £ to SP; to BSP the returns improve, but we still would have lost around 12p for every £1 staked.

Ryan Moore: UK v Ireland

It is relevant to distinguish performance in the UK versus Ireland for Moore because there is a quite a difference:

As can be seen, Moore's record in Ireland is far superior in terms of win percentage. This is mainly due to the fact that, in Ireland, 93% of his rides have been for Aidan O’Brien, whereas in the UK this combo stands at just 17% of total rides. O’Brien runners are rarely big prices so as a result of this one would expect to see that high strike rate for Moore in Ireland. However, perhaps what is more significant is if we look at the data for horses from the top three in the betting, comparing Ryan's record in the UK with his record in Ireland.

We are now comparing like for like from a betting market perspective. And yet still we see a stronger performance in Ireland and a much higher strike rate, as well as significantly better returns and a stronger A/E index. It should be noted we get a similar set of results if using a price bracket of say 5/1 or less. Already I am thinking Moore riding in Ireland is something to keep an eye on.

Ryan Moore: Record by Year

Annual data are the next port of call. Here is a breakdown by win percentage / Strike Rate (SR%):

Six of the eight years have seen a strike rate of over 20%; 2019 and 2020 were the years to dip below that figure. One obvious reason that may help explain this lower level was that Aidan O’Brien slightly under-performed at the same time. Obviously that would have affected Moore’s record as he rides so regularly for the stable. Moreover, 2020 was Covid-affected with Moore largely unable to ride in Ireland: he had just 15 rides, across Irish Champions Weekend, with two wins and another five placed horses.

If we track the yearly strike rates of both trainer and jockey we can see there is a clear correlation:

As punters we need to appreciate that in most cases jockeys are only as good as the horses they are riding, and those primarily riding for top stables will win more often than jockeys who ride regularly for ‘lesser’ stables. This is why when researchers drill into data they often use price bands to compare in order to offer a fairer comparison (like I did earlier in the UK v Ireland – top three in the betting stats). Talking of price, let's look at this area next:

Ryan Moore: Record by Betting Odds / Price (SP)

The Profiler offers a breakdown of performance by Starting Price splitting the market into seven price brackets. I have taken Moore’s record straight from that table:

As can be seen, Moore does not ride many genuine outsiders – less than 50 rides on horses priced 28/1 or bigger in the last eight years. From the table, then, it looks sensible to concentrate on horses priced 17/2 or shorter. When using BSP with these shorter priced runners one would have lost only around 6p in the £ across 3549 qualifiers. That's not too bad given the huge sample. In fact we would have made a small profit to BSP last year (2022) on horses with an industry SP of 17/2 or shorter. Hindsight, eh?

One clear problem with jockeys as well renowned as Moore is securing value. How easy is it to obtain value on a Moore mount? Clearly it is not easy, so we need to keep digging!

Ryan Moore: Record by Distance

A look at Ryan's record at different distances now. I have grouped them into five distance bands. Again I am comparing strike rates:

The one distance bracket that stands out from a strike rate perspective is 1m1f to 1m3f. The data sample is considerable so one would guess there is something going on here. But what could be happening? The first point to clarify is there is not a field size-related bias, even if 7f-1m races have a slightly bigger average field size than other distances.

One factor could be that Moore rarely blasts his runners out of the gates and hence tends to front run in races less than the average jockey. With that in mind, this might be what is hindering his strike rate figures at shorter distances (less than a mile). Over longer distances the front running bias declines considerably and hence in 1m1f to 1m3f this is not such an issue. That is one plausible idea.

Another theory is linked to the fact he rides many of the best bred middle distance horses in the world, usually for O'Brien / Coolmore Stud. Indeed if you look at the distance stats for Moore when riding for O’Brien, the best distance range for the pair is also 1m1f to 1m3f – hitting close to a 31% success rate. Backing this combo over these distances would have yielded a BSP profit of over 15p in the £. This theory, which initially had plenty of logic to it, now has some evidence to give it 'real world' credibility.

My final word on this distance section is simply that Moore may just judge the pace of these 1m1f-1m3f races better than any other distance. That may also have some validity.

Ryan Moore: Record by Course

I am now going to look at all courses where Moore has had at least 75 rides in the eight year sample period. The courses are listed alphabetically:

As one might expect, achieving blind profits at individual courses is unlikely, but Moore has snuck into SP profit at Chelmsford and Sandown. Using BSP actually does not change things too much with only Naas additionally edging into profit and Lingfield hitting break even.

Moore's record at Goodwood offers up some interesting stats when we compare his data on favourites with other market ranks:

The ‘not favourite’ stats include plenty of runners that were near the head of the market – combining second and third favourites produced just 6 winners from 73! Goodwood obviously hosts highly competitive racing so we do have to factor that in when noting poor or modest looking results. But perhaps a crucial note is that Aidan O'Brien doesn't really target the Glorious Goodwood festival like he does other meetings. Indeed, of the 16 tracks where O'Brien has saddled 20+ runners in the months of July and August, Goodwood has the lowest each way strike rate of all. Moore rode 55 of APOB's 80 such runners during the study period.

Considering Grade 1 UK courses more broadly, punters need to be cautious when focusing strongly on one particular jockey. For example, I think the following table is quite an eye opener. It compares Moore riding favourites at Grade 1 UK tracks with favourites at non-Grade 1 UK tracks. The Grade 1 UK tracks are Ascot, Doncaster, Epsom, Goodwood, Newbury, Newmarket, Sandown and York:

It should be noted that the average price of the favourites at the UK Grade 1 tracks was higher, which will have a bearing on the strike rate, but even taking that into account the numbers are still poles apart. I did check horses priced 2/1 or shorter across both types of track and the non-Grade 1 UK courses secured an 11% better strike rate then as well and much better returns of an extra 19p in the £. I rarely back favourites myself, but if there are favourite backers out there, bear those stats in mind if looking to back a Moore 'jolly'.

Before moving away from courses, the stats from these five courses where Moore did not ride at least 75 runners are actually worth sharing:

The sample sizes are not that small and the two stand out stats are the PRB figures for Wolves (0.84) and Navan (0.80) – these are exceptionally high.

Ryan Moore: Record by Trainer

Here are the trainers that Moore has ridden for at least 50 times (ordered by strike rate) – there are 11 in total:

* includes prior trainer entities at the same establishment

Moore has a very good record when riding for the Charlton stable, especially with horses from the top three in the betting – with these runners his figures read 21 wins from 54 (SR 38.9%) for an SP profit of £34.03 (ROI +63.0%). William Haggas and Charlie Hills are also trainers that Moore has done well for and, as a general rule, when the jockey teams up with either of these trainers I would look at it as a positive.

As expected Aidan O'Brien and Sir Michael Stoute provide Moore with the vast majority of his rides, with O'Brien offering better stats in that particular battle.

We saw earlier that the overall Ireland versus UK stats differed markedly for Moore. It makes sense therefore to compare Moore’s record with O'Brien when riding in the UK compared with Ireland. The graph below plots the relative win and win/placed (each way) strike rates:

We can see a much stronger set of results for Irish races in terms of wins and places. This was to be expected, with there being a heavy selection bias when Moore catches a plane to ride, but it is still nice to see that confirmed. Losses to level stakes correlated with the strike rates meaning they were much steeper in the UK than in Ireland for this jockey trainer combination - 16.5% in the UK, 5.8% in Ireland. This equates to a difference of nearly 11 pence in the £.

Ryan Moore: Record by Run Style

Onto run style now. Here is a breakdown of Moore’s run style in terms of percentage of runners that match each of the four styles measured on geegeez.co.uk:

These figures are very similar to those you would find if you averaged out all the jockeys in the weighing room. Ryan has raced from the front on 14% of his rides which equates to roughly one in every seven. However, there is a big difference if we compare the percentage of Moore front runners in handicaps to non-handicaps. In handicaps he has taken the early lead in just 9.7% of races, in non-handicaps the figure is 16.7%.

In sprint handicaps (5-6f) Moore has led early just 20 times in 264 races, which equates to just 7.6% of the time. This stat does baffle me. As regular readers will know, front runners in sprint handicaps generally have a huge edge. Moore clearly does not think like this – if he did that figure would be much much higher.

Moore follows the usual trend of jockeys where his front runners win more often than his prominent racers who in turn out-perform mid div and those held up early. I always look at favourite run style data, too, as this eliminates any potential selection bias regarding 'good horses at the front, bad ones at the back'. Here are the relative win strike rates for Moore-ridden favourites in terms of the four main run styles:

Over half of his front-running favourites went onto win. It should come as no surprise therefore that one would have made a healthy profit on Moore-ridden front-running favourites, while significant losses were incurred on favourites that were held up or raced midfield early. Moore on Aidan O'Brien-trained front-running favourites have an astonishing record: 60 wins from 94 runners (SR 63.8%). If your crystal ball had predicted these runners pre-race, you would been able to secure a huge profit of £52.36 (ROI +55.7%).

Ryan "More": Extra stats and nuggets

With the main body of the article complete allow me to share a few extra statistics that may be of interest:

When riding a horse making its debut in the UK, Moore has won 44 times from 333 runs (SR 13.2%) for significant losses of £143.36 (ROI -43.1%). Even when these debutants have started favourite such runners made losses of around 29p in the £. Compare this to Irish debutants who have won over 25% of the time (23 wins from 90). This is another example of the O'Brien factor.
Keep an eye on horses that are having their second career start where Moore was also on board for their debut. This cohort has produced 39 winners from 111 (SR 35.1%) for a small SP profit of £3.27 (ROI +3.0%). To BSP this improves to +£18.73 (ROI +16.9%).
Moore has a better strike rate at Royal Ascot compared with all other Ascot meetings combined. At Royal Ascot his strike rate is 18.6%; all other Ascot meetings combined this figure is just 12.7%. At Royal Ascot (2015-2022) backing Moore blind would have yielded a BSP profit of £44.91 (ROI +18.2%).

Ryan Moore Main Takeaways

Moore has a much higher strike rate in Ireland than in the UK (the O'Brien factor).
Moore's form is heavily influenced by the form of the Aidan O'Brien stable, especially when racing over the Irish Sea.
Moore has excelled at middle distances of 1m1f to 1m3f for all trainers, but especially so for O'Brien.
At Grade 1 UK tracks it is difficult to find value when Moore is riding.
Away from Grade 1 UK tracks Moore has made a small profit on all rides sent off favourite.
He has an excellent record at both Navan and Wolverhampton (samples are modest but the PRB figures are insane).
He has a very good record when riding for the Charlton stable, especially if they are in the top three of the betting. Charles Hills and William Haggas are trainers for whom he has solid records also.
Moore has an outstanding record on front runners that start favourite. This is especially true if trained by O'Brien.
The three extra nuggets shared immediately above.

So that wraps up my Ryan Moore profile. There is clearly no doubting Moore's qualities as a jockey – from a personal point of view, I just wish he would race close to or up with pace more often, especially in races of a mile or less. Given his superstar profile it is difficult but, as I hope you've discovered, not impossible to squeeze some juice out of Ryan Moore's value lemon.

Until next time...

- DR

Draw Bias 2022: Part 4, Negative Bias

17 May 2022/in Dave Renham/by Dave Renham

In this article I will discuss another angle that can be deployed in our betting, and that is negative draw bias, writes Dave Renham. I think the phrase was coined in the late '90s by Russell Clarke when he used to write regularly in betting magazines. [He has since contributed an excellent eight part series on the betting markets here on geegeez, which can be read here].

What is negative draw bias?

Negative draw bias highlights a horse or horses that have run well from a poor draw and, hence, in theory have run much better than their finishing position may have initially indicated. From there, one would potentially have a ‘horse to follow’ and worth backing soon afterwards when granted a more favourable position in the starting gates.

As with many things in racing, negative draw bias is not quite as simple as it sounds. There are potential issues with this idea – for example, once we have a ‘horse to follow’ we have the tricky decision of how long to continue supporting the horse in the future? One run? Two? Until it wins? What if it loses four or five races? There clearly is no ‘correct’ answer’ to this question.

We also need to think about under what circumstances we back the horse. Should we back it blindly? Or only under similar conditions? What if it is drawn poorly again the next few times it races?

A third question to consider is, "can we be completely sure the horse has actually run well against a draw bias?" If the horse has been beaten a neck over 5f at Chester from stall 14 then we can be as good as 100% certain. However, generally, races - especially big field affairs on a straight course - where one side of the draw seems to be strongly advantaged over the other. There is a case to say that biases that occur like this can be down to a pace bias (i.e. the fast horses were all congregated on one side of the track and therefore made that 'mini race' quicker) than a draw bias but, regardless of which, it is likely some form of ‘bias’ is in play.

Examples of negative draw bias

It's time to look at some examples of negative draw bias in action. I want to look first at a race at York over the 1 mile trip. This course and distance is in 7^th position in my top 10 draw bias courses which I looked at in a previous article with low draws holding an edge over middle draws, and high draws at a big disadvantage. The race was run at the backend of 2021:

This race had a maximum field of 20 and, as can be seen, three of the five lowest draws filled the top three positions. Two middle draws in 9 and 12 came 4th and 5th and then the best of the high draws, Another Batt (drawn 20) and Ouzo (19) came 6th and 7th. This looks a solid example of Another Batt and Ouzo running well considering their negative draws. In fact, draws 19 and 20 are the worst of the lot being stuck ‘out in the car park’.

From a negative draw bias perspective, both Another Batt and Ouzo look to be horses to follow. So how did they fare after this good run? Well, next time out Another Batt went on to win at Donny:

He was joint favourite that next day, so clearly others noticed the good run at York from a poor draw. Even so, he won fairly comfortably and 9/2 are decent enough odds. Ouzo, meanwhile, has yet to run since but may be worth noting. He was bought for 62,000 guineas in the Newmarket Autumn sale and has moved to Jamie Osborne's stable.

Now, of course not all good runs from poor draws will produce next time out winners. So this goes back to the earlier question about what to do when you find one of these negative draw bias horses, and for how long do we support it, and under what conditions? I said earlier that there is no ‘correct’ answer. What we decide will simply be down to personal preference. From my perspective I tend to keep an eye on these horses for three or four more runs. That does not mean I will back them every time and, once they have won, I tend to cross them off my list. Why three or four runs?

Well, as mentioned, conditions in subsequent races will influence their chances. They may been drawn badly again; they may be in a highly competitive 20-runner race; the going may not ideal, and so on. Also, if they do not return to the track relatively quickly, as in the case of Ouzo, then that gives another potential cause for concern. So there are many factors that will make me think twice about backing the qualifying horse, even though sometimes I will miss a good winner by being more selective.

A system from the '90s

There is another reason I will keep the horses on my radar for a few subsequent runs and that is down to a system I used back in the 1990s. This system was based on negative draw bias and the optimum strategy for this particular approach was backing such runners on their next three starts, but stopping if/when the horse was a winner. It was very successful for a four or five year period, and it made me realise that these types of horses should not be immediately discarded if they ran poorly in the race following their negative draw bias run.

I mentioned at the beginning of this piece that big field races on straight courses can produce what seems to be a draw bias but may actually be a pace bias (which, I guess, is a sort of moveable draw bias). Ascot is one such course where this happens on a fairly regular basis. A good example can be seen in the Royal Hunt Cup of 2020:

High draws dominated this race as you can see in the result above. Maydanny, who finished 7th, was the only low drawn horse to finish in the first eight. Now normally your eye would not be drawn (excuse the pun) to a horse that had finished outside the top six. However, there clearly was a bias occurring here, and Maydanny was first home on the disadvantaged far side.

Maydanny did not follow the script next time when beaten into fifth as an odds on favourite. However, on his second subsequent run this happened:

From a plum draw (for a front-running type) in stall 1, he destroyed an 18-runner field at Goodwood, winning by five lengths at odds of 5/1.

Looking back to the Royal Hunt Cup, the in-running comments were insightful, too. Maydanny was the only horse to race on the far side out of the first eight finishers. Therefore, on a straight course especially, it is a good idea to look at the race comments in conjunction with the draw positions for the first few runners home in a race.

Here is another example, where I would argue the race comments are more clear-cut than the draw numbers. The first five home in the Britannia handicap at Royal Ascot in 2021 were as follows:

If we purely look at the numerical draw positions of the first five finishers, we can see that higher draws seem to have been favoured, but on first glance we may not think the draw bias was hugely significant. It may be a different matter if four of the first five home had been drawn 24 or higher and the other runner had been drawn 1; the numbers are shouting out as us in a case like that. However, if we read the ‘in running’ comments for this race we can see that fourth-placed Dubai Honour was the only one of the first five to race on the far side. The other four raced near side. This fact coupled with the draw positions make this look like a good run from a poor draw.

Dubai Honour was a horse that we could have added to our negative draw bias list and if we did, he would have rewarded our faith next time out, getting up to win by a head at 11/2. Indeed, he subsequently won a pair of Group 2's in France before running second in the Group 1 Champion Stakes back at Ascot on British Champions Day!

The next two home on the far side were Mithras (unraced afterwards in UK, renamed Turin Redsun and now racing in Hong Kong) and Qaader, who won at 8/1 two starts later.

Identifying negative draw bias horses (and a shortcut)

I have picked out three examples of negative draw bias but there are plenty more I could have shared with you. Not all will follow the winning script, but a reasonable proportion will win within three or four races.

Ultimately, to pick up on all potential negative draw bias qualifiers, we need to look at results on a daily basis and then keep a track of them, which can be done on Geegeez using the excellent Tracker tool. However, there is a possible shortcut for those of you who simply do not have the time to do that. It won’t likely be as accurate but it will be a quicker way to determine negative draw bias type selections.

What we can do is deploy a rule-based racing system. I discussed numerous racing systems in a recent set of articles so combining that approach with the draw provides some gratifying symmetry.

Here are the basic rules of the system:

Last time out (LTO) race was a handicap with 10+ runners
Horse must have been drawn 10 or higher LTO
Horse must have finished 2nd, 3rd, or 4th LTO

This system is then to be used where the LTO course and distance was one of the following:

Now, for the eagle eyed reader, you may have noticed that my top 10 draw biased courses from 2016 to 2021 are in the list. In addition there are some of the 'near misses' I published with that top 10, as well as Dundalk over 5f. It is very difficult to win from stall 10 or higher at any of these course/distance combinations which is why I chose them.

I looked at results going right back to 2009 – essentially this was to get a bigger individual sample for each course and distance. Combining all of the qualifiers from all of those courses in their next starts we get these bottom line figures:

Considering this is a very raw type of system these combined results are impressive. It should be noted that I chose the course and distances before I checked the results so there is no back fitting here. Indeed, five of the 14 made a loss, so I could easily have manipulated the stats by ignoring those courses to improve matters – but that is not my style.

For the record, those that made a loss were horses that ran last time out at Chester 7f, Kempton 6f, Goodwood 7f, Goodwood 1m and Pontefract 1m. The other nine combinations were all profitable.

I then thought it would be a good idea to compare the strike rates of the negative draw bias system horses with ALL horses that finished 2nd, 3rd, or 4th last time out in 10+ runner handicaps (2009-2021); not just the win strike rate, but the placed strike rate as well (placed SR% being win and placed runners combined). Here is the comparison:

A better absolute strike rate of nearly 2% in terms of wins, which is almost 14% better comparatively; while the placed results show a similar pattern:

Over 3% absolute difference in the placed strike rates, and an 8% comparative improvement. It's satisfying to see increased strike rates in both groups, which adds confidence to the basic system concept and the results thereof.

This system approach should not be time consuming. There will be far fewer races to check over the course of a year compared with worrying about checking the results of all 10+ runner handicaps. Indeed you will only need to check the day’s results when one of these track and trip combo's has rnu a handicap with ten or more runners. Also the system is only concerned with the very next run which means once a horse has run again you simply strike it off the list.

Of course this method is easily adapted: for example, you may want to change last time out position of 2nd to 4th to a distance beaten figure (in lengths, or lengths per furlong - perhaps using the Geegeez Px coloured dots on the left side of the Full Form result rows); you may want to change draw 10 to draw 8; you may want to keep qualifying horses for more than one run, and so on. Ultimately, there is lots of scope to change the approach to suit your style.

Keep in mind (of course) that, as we know, a system is simply that – it is not a magic bullet and just because 2009 to 2021 produced a profit, it doesn’t mean results will continue to be positive in the future, or that there won't be losing runs. This system, however, does follow logical negative draw bias ideas so one would hope it has a sporting chance of repeating its past success in the near future at least.

I hope this article has sparked your interest in negative draw bias and please share your thoughts or personal experiences in the comments below. I'd love to hear from you.

- DR

p.s. The recent Victoria Cup, again at Ascot, saw the highest three (out of 27!) stalls combine for a £5208.10 trifecta dividend - keep an eye out for draw bias angles, both positive and negative!

Running Well Against a Pace Bias, Part 2

29 November 2020/in Dave Renham/by Dave Renham

In the first half of this two-parter, I started to look at something I term as ‘negative pace bias’, writes Dave Renham. The basic idea is to find races where there seems to have been a strong pace bias with a view to highlighting horses that have run well against it. I mentioned last time that one can never be 100 per cent certain whether there has actually been a pace bias in a race or not but, generally speaking, one is going to be right many more times than one is wrong.

To recap, there are two ways a pace bias could play out. Firstly, races where horses close to the pace from the start dominate: here we are looking for any hold up horse that has run well. And secondly, one where hold up horses end up fighting out the finish, in which case we look for prominent racers or race leaders that have run well.

As before, I have looked at bigger field – races of 15 or more runners – from UK turf flat and all-weather racing in 2020. In the first piece I looked in detail at five races and the subsequent form of highlighted runners; in this one I will look at another quintet of big field negative pace bias races.

Continuing in chronological order, and starting on 4th July, with the Derby.

RACE 6 - 4^th July – 4:55 Epsom

One of the most iconic races of the year, the Investec Derby showed a strong pace bias this year as the result and race comments below imply:

This was an extraordinary race where the early leader, Serpentine, just gradually increased his lead in the final mile until he was over ten lengths clear with three furlongs to go. He basically slipped the field, and it was a triumph of pace setting by jockey Emmet McNamara.

What was equally remarkable was that the first three horses home stayed in those positions for most of the race. Not only that, all three were huge prices which, for me, strengthens my belief that there was a bias that day for those who raced close to or up with the pace.

Also don’t be fooled by the words ‘held up’ in Kameko’s in running comments, because as it says he was ‘held up behind leaders’ and for virtually the whole race he was positioned in 4^th or 5^th.

English King and Mogul did best of those who ran midfield for the first part of the race and they are the horses that seemed to have run best in terms of performing against the bias.

In English King’s next run on 30^th July at Goodwood he finished 4^th, but can you guess who won that race? Yes, it was Mogul, who scored at a decent enough price of 9/2. English King has run once more since, finishing 6^th at Longchamp, while Mogul finished 3^rd at York before scoring another victory at Longchamp in September (price 6/1). All in all, another good outcome for the approach.

RACE 7 - 5^th July – 3:15 Haydock

For the next race we travel north to Haydock a day after the Derby. The Old Newton Cup is a decent Class 2 handicap, which this year strongly favoured horses coming from off the pace as you can see from the following race comments.

Seven of the first eight raced midfield or in rear early and only The Trader, who finished third, was close to the pace. Therefore, The Trader is the horse to take out of the race on the negative pace bias angle. He has run twice since, finishing 3^rd at Ripon and then 4^th at Newcastle. No future win yet but the Ripon race result with the comments are definitely worth sharing:

As we can see, the jockey on The Trader dropped his rein a furlong out. Not only that, he also got his whip tangled up. I think we could legitimately argue that he should have won that race, but for those two unfortunate incidents. Even with that happening he was only beaten by a neck and a neck.

RACE 8 - 8^th July – 8:40 Newbury

Newbury next and a long distance handicap.

In this race, six of the first seven home came from off the pace with only Tralee Hills in 4^th racing prominently. Clearly, Tralee Hills was the horse to take out of this one. He has run four times since with his results shown below:

As we can see he has not made the frame subsequently in four starts and in truth all runs have been relatively poor. Initially I thought it was interesting that Tralee Hills had been ‘held up’ in all starts since when trying to look for potential reasons or excuses. However, looking at his career record, he has actually raced close to the pace in just three of his 25 starts. The remaining 22 saw him positioned midfield or in rear early. If I had the opportunity to speak to his trainer, I might point out that racing prominently is a running style that may in fact suit his horse!

Over both articles, this is the first race of the eight I have looked at where, to date, the follow up results have shown no positivity. This highlights, of course, that no method or angle is fool proof, as I have indicated many times in the past.

RACE 9 - 17^th July – 12:35 Beverley

A class 6 5f sprint handicap is next on the agenda with the first two, and the fourth home returning big odds.

As the comments indicate, six of first eight home raced rear (four) or mid-pack (two). Pivotal Art, who raced close up and finished 3^rd, has only raced once since when well beaten into 10^th on the all-weather. The sixth horse home, Newgate Angel, who had led until the final furlong returned to the same course and distance on 12^th August. In a slightly weaker contest, he proved that the previous run had indeed been a good one, by winning relatively cosily at odds of 7/1 (result below).

It is interesting to note that Newgate Angel was drawn in stall one on both occasions, a favourable box for a front-runner at Beverley – when getting the run of the race.

RACE 10 - 17^th July – 3:40 Beverley

The final race in review is a race later on the card that same day at Beverley. This time it was a 1m2f handicap.

This was another race where the pace setters struggled with five of first seven home held up out the back early on. The two horses to buck the trend were Ideal Candy in 3^rdand Motahassen who finished 5^th. After watching a video of the race I had a slight preference for the latter even though he finished two places behind Ideal Candy. My reasoning was that Motahassen raced a little wide early but despite this soon took up a position in 3^rd. By halfway he was still close up in 5^th and then in the straight he did not take a particularly direct line, veering and changing direction a couple of times.

Since this race, Ideal Candy has run poorly on five occasions with a best finishing position of 6^th. Motahassen has fared better finishing 3^rd next time before winning at the fourth time of asking at Redcar in October.

Whether one would have stuck with him for four runs is another question. However, if you did, you would have been rewarded with excellent winning odds of 12/1.

The five races in this sample have not been as ‘successful’ as the first five but, having said that, I believe over the ten races the angle has produced an impressive set of future results.

Putting ‘Negative Pace Bias’ to work for you

If you want to check out other races for yourself, you can do this through Query Tool on Geegeez, using the following step by step method:

Select 2020, UK, flat turf, flat AW, 15+ runners
Go to Qualifiers tab and sort by position (this is in order to get the race winners)
Click on the winner to go the race result
Select 'Comments' to view the in-running comments
Note any positive efforts against a bias
Go to back to number 3 and repeat the process.

Step 1 is something that can be tinkered with – those were just the parameters I chose. I have yet to check Irish races, but the same principle should apply so you could add that if you wish. Likewise, this method can be applied to National Hunt racing, too. Furthermore, you may want to limit races to handicaps only, as I would guess they work better in general, and of course you could look at slightly smaller field sizes to include races with, say, 12 to 14 runners. I would be wary of going below ten runners, personally.

When choosing races that fit your ‘negative pace profile’, this becomes more down to the individual. I tend to look at the first six to eight finishers and look at the split between pace horses (leaders/prominent racers) versus non-pace horses (horses who raced midfield or rear). Even then, I have no hard and fast rules, but clearly there has to be an imbalance between the two.

To conclude, I continually ‘bang on’ about pace bias and how useful it can be for punters. I hope these two articles may have swayed any ‘remainers’ to switch their allegiance!

Running Well Against a Pace Bias, Part 1

16 November 2020/in Dave Renham/by Dave Renham

As regular readers of Geegeez will know I have a particular interest with running styles / pace in a race, writes Dave Renham. I strongly believe it is an area that remains misunderstood by many and essentially dismissed as unimportant.

In this piece I am going to examine a way to use pace to find future betting opportunities, something I call ‘negative pace bias’. To that end, I have looked at big field races (15 or more runners) from UK flat racing in 2020. This includes all weather racing, although the vast majority have been on turf as four of the six UK all weather courses have field size limits of 14 or less. Races with larger fields were chosen simply because I thought it would be easier to spot a potential pace bias.

So how does one determine whether there has been a potential pace bias in a race or not? Before I attempt to answer that, please note the word ‘potential’: it is important to say that one can never be 100 per cent confident that there has actually been a pace bias in a race or not. However, I think it is possible to be reasonably sure in certain circumstances.

For example, if you are watching a race and the horses that dominate the race have all raced up with the pace from the start, then it can be assumed that there has been a pace bias towards more prominently ridden animals, and against hold up horses. A reverse pattern could emerge of course with the race finish fought out by hold-up horses with all those racing up with the pace fading out of contention. Even in those scenarios, this method is far from an exact science. What is when it comes to racing?

Also, naturally, I am writing this article retrospectively. However, I do use this angle with my own betting and some of the races highlighted are ones I noted at the time, certain horses from which I ended up following.

In order to be able to write this article I needed to go through all the qualifying races and see if either of the two pace bias angles occurred. The key idea from here was relatively simple and hopefully logical. Once a race had been found where there seems to have been a pace bias, I looked for any horse who seemed to have run well ‘against’ this bias. More about these horses shortly.

In terms of finding the races I used the race comments in the Geegeez results section. From there I then watched the race video online to ensure the race panned out as the comments had indicated. [You don’t necessarily have to do this, but I personally like to see the bias for real as it were].

Normally I would expect to find one horse that may stand out given the circumstances outlined above, occasionally there maybe be more, but rarely will there be more than two; after all, if there was, then there probably wasn’t a strong enough edge in the race.

To summarise, we are looking for horses that have probably run much better than their finishing position may have initially indicated. Once finding a horse in my research that fitted the criteria, I reviewed how it ran in the races that followed. The hope or even expectation of course was to a see a ‘win’ in the finishing position column soon afterwards; and the sooner the better. After all we are trying to find a method that produces future winners that we will bet on.

Back briefly to the ‘now’ as it were. If you find such an ‘eyecatcher’ horse, as punters we have the difficult decision regarding how long we go on backing it in the future. Do we back it ‘blind’ in the next race? If we do and it loses, do we back it a second time, a third, a fourth, etc until it wins? Because we need to realise that it might not win within the next three or four races, it might not even win again within the next ten or twenty. Do we instead back it any time it runs in the next 4-6 weeks? Do we look at future races on a case by case basis digging deeper before making a final decision whether this is the right time to back it?

Deciding upon the right approach is essentially impossible and is all down to individual preference. I guess the ‘results’ from this article may help shape a method – should you decide there is sufficient mileage in what follows. For the record, I personally make decisions on a race by race basis and each horse will remain on my ‘pace horses to follow list’ for three or four runs maximum. If and when a horse wins it is invariably removed from my list.

At this point it is worth mentioning that when I am testing new ideas for the first time, like this one, I am very systematic to begin with. This is because a rules-based approach is much quicker when all I want to do is to get a ‘feel’ for whether an idea shows merit. During any testing phase I check results in two ways. Firstly I focus simply on the next run to see if they would have returned a profit, and secondly I look at the next three runs but will STOP AT A WINNER (should there be one). This is a variant of the method Nick Mordin used in his iconic book ‘Winning Without Thinking’ where he used the next three runs regardless on various ‘systems’.

Now I won’t be able to examine every race in 2020 that ‘showed’ a pace bias along with its aftermath, otherwise the article would become more like a thesis! However, there is still be plenty here to get our teeth into. The following are in chronological order the first ten ‘pace biased’ races I found, in the hope that they offer a variety of future outcomes. There is a lot to look at so what follows are the first five of those ten races.

RACE 1 - 7^th February 2020 – 4:35 Chelmsford

As you can see below this was a 15 runner class 6 handicap over 1 mile. Looking closely at the race comments, you will see that the first four finishers raced up with the pace, as did the fifth despite an awkward start. Horses 6^th all the way down to 15^th raced midfield or at the back. To me this race showed a very strong bias to horses that raced near the front.

Two horses catch my eye. Bird To Love who finished 6^th and Zayriyan who finished 7^th. These were the best of the midfield/held up runners with only a head separating the pair at the line. Both were around three lengths behind the winner. The 8^th placed horse, Irish Times, was a further 2 lengths back and it makes sense to me to ignore that one.

Before discussing what happened next, this was not a race I noted at the time. I’m giving a bit away here by saying I’m wishing I had.

Both Bird To Love and Zayriyan raced again just under three weeks later. Amazingly they reappeared in the same race, again at Chelmsford, but this time over a quarter mile further. The result is shown below:

Not only did they fill 1^st and 2^nd in their very next race, but there are two other things that also stand out. Firstly, look at the distance they beat the third by, over five lengths. Secondly look at the prices: if you had backed both at SP you would have made a 24-point profit. The straight forecast paid over 293/1, while the exacta returned a mouth-watering 514/1.

Of course, amazing outcomes like this are rare, very rare; and I’m gutted I missed it at the time. I doubt I would have been brave enough to have backed the 1-2, but I am fairly certain I would have backed both horses individually.

Before getting carried away, though, this type of result occurs extremely rarely; it just happens to be the first ‘qualifying’ race I found in 2020.

RACE 2 - 16^th June – 4:40 Ascot

Royal Ascot often has big fields and this 19-runner race seemed to show a relatively strong held up pace bias. Four of the first five home and six of the first eight came from off the pace. The first eight horses with their comments are showed below:

Summer Moon did clear best of the prominent racers, hanging on for 3^rd, so from a pace perspective he was arguably the horse to take out of the race. Land Of Oz was the next best of the ‘pace’ horses, finishing over five lengths further back in 6^th. It still looks a decent enough effort considering it was a long distance slog, but Land Of Oz has not raced since. It will be interesting to see how he performs when he returns to the track.

Let’s now look at Summer Moon’s record including this race and subsequent ones:

As we can see next time out he ran a shocker at Sandown although to be fair he had gone up in class to a Group 3. Back in handicap company he came 8^th next time, beaten five lengths, before winning at York at the rewarding odds of 18/1. For the record, this horse did appear on my radar after the Ascot run, but after his Sandown flop I unwisely crossed him off my list of horses to follow: a frustrating outcome for me considering he won within three races at such good odds.

RACE 3 - 17^th June – 2:25 Ascot

The following day another Royal Ascot race again showed what seemed like a hold up bias:

Although the winner raced close to the pace, as did the 5^th, they were the only two from the first 11 runners home that did. The remaining nine came from off the pace. Horses that win despite a bias are still horses to be interested in. Now, of course, if they won a handicap they are going to go up in the weights, which potentially makes winning more difficult in the near future. However, they still should be of interest as we know horses in form can run up winning sequences, and we also know – or believe – that the horse overcame a pace bias to win. In this case, the winner Hukum stepped up to a Group 3 next time at Newbury (15^th Aug) and continued the winning thread at odds of 4/1.

Arthurian Fable, the horse who finished 5^th, went on to win a handicap two races later as shown:

All in all, this Ascot race worked out extremely well from a negative pace bias perspective.

RACE 4 - 18^th June – 2:25 Ascot

The Britannia, a mile handicap at Ascot for 3yos only, is the next race I found. Big field handicaps over Ascot’s straight mile traditionally tend to favour horses from off the pace and even more so on softer ground. The Pace Analyser shows how the strong the hold-up bias has been since 2009 on soft/heavy ground in 1m handicaps (albeit from a small sample):

This race was no exception and conformed to the hold-up pattern. The winner won extremely impressively having been way off the pace early, but both Finest Sound (2^nd) and Overwrite (6^th) appeared to be ‘negative pace’ horses to note the race. The first seven home and their race comments are shown below:

Let’s look at the subsequent runs of Finest Sound and Overwrite. First Finest Sound:

To date just two more runs; a decent third next time out at Newmarket before a poor run at York. Meanwhile, Overwrite returned to the track 10 days later at Windsor winning a class 2 handicap:

The price of 11/5 was perhaps a bit disappointing given he was 40/1 when 6^th at Ascot, but this race again highlights that following horses that have run against a pace bias have the potential to win soon afterwards.

RACE 5 - 20^th June – 4:10 Ascot

One of the big handicap sprints of the year, the Wokingham, provides the next example:

Five of the first seven finishers raced from off the pace which seems a common theme at the Royal meeting regardless of distance. Hey Jonesy however, made all the running to win which not only looks a fine effort in the context of this specific contest, but when looking back through the history of the race it becomes clear that leading from start to finish in the Wokingham is nigh on impossible: in the last 30 renewals of this big field cavalry charge (going back to 1991) no horse has previously led from start to finish. The closest was Selhurstpark Flyer back in 1998, who led the centre group that day but was not the overall leader until hitting the final furlong. Hence this seems an even better performance than it originally looks. However, all that glisters is not gold, and Hey Jonesy has been well beaten three times since his big day in June, as we can see:

In many ways, that’s a good outcome because it reminds us that all approaches are fallible, and that sensible staking and managing our expectations are pivotal mental attributes even when deploying a solid strategy.

Back to the Wokingham, and Stone Of Destiny, who finished 6^th, is another horse that caught my eye having raced prominently. He was beaten less than two and half lengths. Although he was well beaten in his next two runs he then came 2^nd before prevailing at 16/1 in another marquee event, the Portland Handicap at Doncaster.

The question all of us should be asking at this point is would we have followed Stone Of Destiny until this Doncaster run? It is back to that quandary again, being down to individual preference with no right or wrong answer. Here are two of the possible ways it could have gone:

Stone Of Destiny having run two poor looking races in a row in his next two runs is discarded after race 2;
After doing some post-race analysis you notice that six furlongs may be a bit of a stretch for this horse. Let me elaborate on the reasoning you may have used to reach this conclusion. In the actual race he was 2^nd with just over half a furlong to go before fading slightly into 6^th. That meant he had won just once in 12 attempts at the six-furlong distance with the sole win being on debut in a novice event. Overall, his five-furlong record was better with two wins from nine including a class 2 handicap win at Ascot in the summer of 2019. It looks that although potentially effective at 6f, those last 100 yards, especially on a stiff track like Ascot, are a few steps too far. Hence it would be likely that you would upgrade his Wokingham run for not only running well against a pace bias, but also potentially battling his own distance bias, too.

It is almost certain therefore you would have backed him at Ascot next time over 5f (11^th July), a day on which he reared at the start which severely compromised his chance. Most people would immediately forgive that run if they’d seen it. His second subsequent run was at Goodwood in the Stewards’ Cup back over 6f (1^st August). This is a much easier 6f so you may have backed him again hoping he would just get the trip, or you may have swerved.

He again ran well for about five furlongs before fading badly in the final eighth of a mile. Once again he had credible excuses. His 3rd run after the Wokingham was at Sandown back over 5f. This would probably have looked a great opportunity and indeed he ran very well, finishing 2^nd.

So although three races in, Stone Of Destiny would still look like he is knocking at the door. You therefore decide to back him again next time dependent on conditions. The race as stated earlier was the Portland at Doncaster and although it says the distance is 6f on his race record (see above), it is actually 5f 140 yards. This equates to just over 5½ furlongs, though nearer six than five. You feel he is certainly worth a chance at this interim distance. He goes on to win as we know at 16/1. Happy days!

Both of those two scenarios could have emerged and I wouldn’t argue against anyone who chose either route. There are of course many other ways this could have played out and a good number of those I’m sure would have been logical as well.

So there we have it. Five races in and I have another five races to share and analyse in the second half.

All in all there have been some very positive signs for this method to date, albeit from an extremely small sample of races. Will the next five work as well? Honestly, I think it is highly unlikely that they will, and I certainly cannot envisage a similar outcome to the first race I looked at. But you never know. Let’s hope that we don’t draw a blank with the next five finding no future winners at all!

Also next time, I’ll show you how I researched this, and how you can find your own negative pace biases using the Geegeez toolkit.

- DR

Pace Analysis in Action: A See-Saw Day

19 October 2020/in Dave Renham/by Dave Renham

In this article I am going to go through a betting process / approach that I used over a day of racing primarily deploying the pace data found on Geegeez, writes Dave Renham. When there is a strong pace bias at a particular course and distance I would argue that this is the most important factor to take into consideration. The aim when studying each race is to hopefully pinpoint value selections using pace as the key consideration.

Different punters have different approaches to how they bet. Some vary staking, some stick to a price band, some dutch more than one runner; for me I tend to steer away from short prices and I am not averse to backing two or three runners in the same race. I am not saying this is necessarily the best strategy, but it is a strategy I am most comfortable with. I also often bet each way – again not the method for some but it is frequently my preference.

Some days can pass by with limited or no pace betting opportunities; however when looking at the racing for Monday 12^th October 2020 there were several races that caught my eye. I always lookout for certain courses and Musselburgh is one such course. On this Monday there were races that potentially offered us a real pace edge. Below I will look at each one individually and go through how I ‘tackled’ each one; as you'll see, it didn't all go my way - far from it - but the value game is about profit, not winners, and one good score was enough to finish in front.

1.30 Musselburgh – this was a 7f handicap and my starting point was this screenshot from Geegeez:

As a numbers man I prefer looking at the ‘data’ view rather than the graphic or heat map option and I order the four-race pace totals highest to lowest. I also change the going to cover all possible goings as my starting point and then narrow down to more specific goings when required. From the article I wrote about Musselburgh I know the bias seems to strengthen on softer ground as this graphic when looking at good to soft to heavy going shows:

I also adjusted the numbers of runners depending on the data set; here, with it being an 11-runner race, I have used 10 to 12 runners. If the data set was small I would increase this to perhaps 9 to 13 or 8 to 14.

Looking at the horses now, the race was not stacked with pace. Kupa River has the highest pace score of 14 having led early in two of his last four starts. Looking further back he has only led three times in the last ten runs. This tempers my enthusiasm in terms of him leading. I’m not saying he won’t, maybe the last four runs have persuaded the trainer that racing ‘on the front end’ is his best tactic. Alix James is next highest on 13 having led once and raced prominently three times in his last four runs. Going back further he has led in four of his last seven starts winning twice. There is a potential excuse, too, for perhaps not leading on his last two runs as he was drawn wide at both Ayr and Haydock making it difficult to cross to the inside and lead. There were three other horses that had led once in their last four starts but none of them had a long term front-running pace profile.

So Alix James looked the most likely front runner to me in a race of little pace. His draw, though, for the third race running was high (away from the inside). However, before putting a line through him I wanted to look at the draw/pace combinations data which you can find in the ‘draw’ tab of the race in question. Here I found some good news:

As can be seen, being drawn high is not such an insurmountable challenge for horses to a) get to the lead, and b) be successful. Inside draws (low) do lead more often but in reality there is little in it. High draws actually have the best strike rate which is a clear positive.

Alix James looked the pace angle to me so I just wanted to check other factors about this horse. I noted he was two from two at the course having won over course and distance in July on good to soft. He was only 2lbs higher here and the class of the race was the same. The main ‘fly in the ointment’ was his last run when he was beaten out of sight when favourite. Last year I noted he ran very poorly at Ayr in September but, eight days later, returned to form finishing a decent 3^rd at Chester: he had proved he can bounce back from a poor run.

My conclusion was that Alix James was the value option. If he led early then there was an excellent chance he would at least hit the frame. He was forecast at 14/1 but the best I managed to get was 15/2 BOG. I backed him each way as I felt, with a shortish priced favourite and a race lacking depth, that was the right call.

What happened in the actual race?

The start of the race panned out as planned with Alix James getting to the lead; however, he was never in complete control up front and despite still being in front three furlongs from home, he started to fade in the final quarter mile. He finished a pretty distant 8^th of 10 in the end (there was a non runner).

Conclusion: I feel it is really important to have a personal debrief after each race whether your bet was successful or not. It is part of the learning process and, believe me, you never stop learning regardless of how experienced you think you might be. I suppose the key question, irrespective of result, is always ‘would I make the same decision next time given a similar set of circumstances and data?’

My answer to myself was, if given the same type of scenario in the future, yes I would probably make the same decision. I correctly picked the front runner: the long term 7f stats at Musselburgh show that if you consistently pick the front runner you will generate long term profits.

2.30 Musselburgh – this was another 7f handicap – Class 2 this time.

At first glance this was more competitive than the first race from a pace / front running perspective, at least when looking at the last four run pace totals. On closer inspection though the top two in the list, Three Saints Bay and Muntadab, were the only horses to have led in their past four races: Three Saints Bay three times and Muntadab once. Both horses had decent long term pace profiles - Three Saints Bay had led in seven of his last 13 races and Muntadab in nine of his last 13. The stats were strongly suggesting that one of these two would lead early. Both had decent form on good to soft and both had won on soft.

The concerns for both was recent form. Three Saints Bay had failed to reach the frame this summer in seven starts although on the positive side he had finished close over course and distance on July 1^st (beaten ¼ length when 3^rd of 6) and three starts back had led at Beverley into the final furlong before fading late on. Musselburgh is an easier 7f than Beverley and also around 90 yards shorter in distance. Muntadab won at Epsom back in July but since then had been well beaten in his last six runs. On the flip side of course their poor recent form had seen them both look potentially well handicapped.

Best prices early doors for the pair were 9/1 on Three Saints Bay and 33/1 on Muntadab. I thought Muntadab offered some value at such odds – you don’t have to be right very many times at this sort of price to make money in the long term. Hence I went each way for Muntadab but decided to go with Sky Bet at 28/1 as they were offering four places. I felt Three Saints Bay was priced about right but I knew he was extremely well handicapped and that he had been very well backed last time out (16/1 into 17/2). Therefore my guess was that he would start shorter than 9/1 and if he did then the 9/1 would offer good value.

What happened in the actual race?

Well I was right about Three Saints Bay as he was backed off the boards late into 4/1 joint favourite. He also got to the front early and dictated the race but perhaps went slightly quicker than ideal. He was still leading into the final furlong before being nabbed around 150 yards out. He was beaten 1½ lengths back in 2nd, while Muntadab was possibly a little unlucky at the start and was forced to 'stay in his lane' as the horse drawn inside him kept him from cutting across. To make matters worse the jockey then went much wider after about 50-100 yards ending up nine horses from the rail and, from there, he was never going to challenge. His finished 8^th.

Conclusion - Ultimately racing is about getting value and getting 9/1 early (albeit with a small rule 4) about Three Saints Bay was a value bet. Muntadab was not competitive this time, but as I said earlier you don’t need many big priced runners to win to make money in the long term. If given the same race profile in the future I think I would make the same two bets.

3.00 Musselburgh – 5f handicap was next on my list of races to check out:

The front-running bias at 5f is not quite as strong as the 7f bias but it is still pretty strong and this was a very simple and quick race for me to decide upon one selection. Autumn Flight is a habitual front runner having led in his last six races and also 12 of his last 14. Add into the mix that on good to soft or softer he had won four times and been placed a further four times from 15 starts, and he looked the logical call. He was also 12/1 early morning and with a short priced favourite this looked a solid each-way bet.

What happened in the actual race?

Autumn Flight did get to the front but perhaps had to expend more energy than ideal in the first furlong. With two furlongs to go he was still leading and seemingly going well but by the final furlong he was being joined at the front and gradually slipped back finishing a close up 4^th.

Conclusion

By the time this race was run the going was soft and getting more testing by the minute. When I had dug down into the pace data the previous evening the good to soft to heavy stats for front runners still showed a front running bias for this field size. However, if I had checked only the soft or heavy stats I would have noted that it becomes a much more level playing field. Whether that would have put me off the selection I’m not sure but it would have made the decision more difficult.

Looking at the pace profile of the race I had expected that Autumn Flight would have had a relatively easy lead, but he needed to be rousted quite vigorously to get in command by the end of the first furlong. Ultimately, this, coupled with the more testing ground, cost him in the final furlong – even so he was only beaten by 1½ lengths. I think overall the bet was a decent one being one place away from getting a return for my money.

3.30 Musselburgh – the second division of the 5f handicap.

As with the previous sprint this race has a clear pace angle with Somewhere Secret. The concern was the draw as he drawn furthest from the rail. Generally at Musselburgh the early leader grabs the rail and therefore I wanted to check the draw/pace combinations data once again to see whether a low draw was a big disadvantage for a potential front runner.

As can be seen, from a win perspective a lower draw would have been ideal; however, there is little in it in terms of the place data and, actually, front runners have made a small each-way profit even when drawn low. Somewhere Secret had form on easy ground (four of his five wins had come on good to soft or softer) and at an early 8/1 BOG he was my first pick.

Another horse that interested me was Glory Fighter. At first glance he was not the archetypical 5f horse that I would normally be interested in. In his last three runs he had dwelt and lost lengths early; in fact, he totally blew his chance in his most recent race rearing at the start. However, two starts back, he had finished 7^th beaten only 2 lengths, despite a dreadful start. Earlier in the season, Glory Fighter had won two races in August, importantly not missing the break, and racing close to the pace. My eye was also caught by the jockey booking of Jamie Gormley, who had ridden him in his first two starts of the season back in June. That horse and jockey combo combined to be placed both times and Gormley had raced prominently in one race and led in the other. If he got away on terms I thought at double figure odds he would have a good chance. One of those successes this season had been on good to soft so he had shown he could act with cut in the ground. I got 10/1 BOG on Glory Fighter.

What happened in the actual race?

Somewhere Secret tried to force the issue but never got to the lead and ultimately it was the outside draw that was his downfall. He raced competitively but never got close to the rail and, by the time he entered the final two furlongs, the writing was on the wall: he finished 7^th. Glory Fighter on the other hand read the script; thankfully he did not miss the break and raced close up in 5^th early. He was produced at exactly the right time, hitting the front around the furlong pole and winning relatively well in the end. His 12/1 SP was an added bonus.

Conclusion

This race perhaps shows that you do sometimes have to look more deeply into the pace figures and the ‘in running’ comments. Glory Fighter could easily have missed the break for a fourth race running and that probably would have scuppered his chance, but these are the decisions as punters we have to ponder. Also, as stated earlier, the going had deteriorated from when making my decisions/selections, so I would tentatively suggest I got lucky here. Having said that, there is plenty of truth in the saying you are better to be lucky than good!

So there you have it – a bit of mixed bag of results but that’s racing. It is important to point out that making profits is not really about finding winners. If you want to back lots of winners then back favourites! If you want to make long term profits then you need to find an edge and value selections – I believe pace can undoubtedly give us that edge.

- DR

Pace Wins The Race: 5f All Weather Handicaps

14 February 2019/in Dave Renham, Horse Racing Blog/by Dave Renham

We still have several weeks of the all-weather season left so I have decided to look to see how strong the pace bias is on the sand, writes Dave Renham. I have not previously looked in detail at all weather pace bias in my Geegeez articles so now seemed as good a time as any.

Just in case you have not read my previous articles on pace I will briefly summarise a few things. Firstly when I discuss pace my main focus is the initial pace in a race and specifically the position horses take up early on. Most of you will be aware that on geegeez.co.uk racecards there is a pace section, and the stats in this article are based on the site’s pace data.

This info is split into four groups - Led, Prominent, Mid Division and Held Up, and after each race all the horses are assigned points in regards to which position they took up early in the race. Leaders get 4, prominent runners 3, horses that ran midfield 2, and those held up score 1. Just over 96% of all UK and Irish runs since 2009 have been scored, the other 4% unable to rated from the comment. For clarity, at the time of writing, 1,169,760 of 1,218,499 comments have been scored.

In previous articles, I have highlighted certain distances / race types that generally favour front runners both on the flat and over the jumps. My first five articles looked at 5f handicaps where pace bias is arguably at its strongest, but I did not look in detail at any course data for the six UK all weather tracks – my main focus was turf handicaps. Hence, a touch belatedly perhaps, it is time to address that now!

The first set of data I wish to share with you is the overall pace stats for 5f all weather handicaps with 6 or more runners (the data for this article has been taken from the last 5 complete years, 2014 to 2018):

Pace comment	Wins	Runners	SR%	IV
Led (4)	254	1137	22.3	2.04
Prominent (3)	360	2874	12.5	1.15
Mid Division (2)	67	1026	6.5	0.62
Held Up (1)	183	2735	6.7	0.61

These figures clearly illustrate the advantage to horses which have led, or disputed the lead, in 5f all-weather handicaps. In fact, the Impact Values - a measure of how much more likely than normal something is to happen, 1 being 'normal' - suggest that 5f handicap pace bias is slightly stronger on the all weather than it is on the turf.

The main data cover all handicaps with six or more runners; I have next looked at splitting these data into groups – 6 to 8 runners; 9 – 10 runners; 11 or more runners. Here are my findings:

6 to 8 runners

Pace comment	Wins	Runners	SR%	IV
Led (4)	119	459	25.9	1.86
Prominent (3)	138	956	14.4	1.04
Mid Division (2)	22	249	8.8	0.64
Held Up (1)	65	757	8.6	0.62

9 to 10 runners

Pace comment	Wins	Runners	SR%	IV
Led (4)	85	446	19.1	1.81
Prominent (3)	146	1083	13.5	1.28
Mid Division (2)	30	435	6.9	0.66
Held Up (1)	68	1125	6.0	0.57

11 or more runners

Pace comment	Wins	Runners	SR%	IV
Led (4)	50	232	21.6	2.60
Prominent (3)	76	835	9.1	1.10
Mid Division (2)	15	342	4.4	0.53
Held Up (1)	50	853	5.9	0.71

It seems therefore the front running bias is as its strongest when there are more runners. An IV of 2.6 for front runners is extremely high for races of 11 or more runners.

Of course, each all weather course has its own unique confirmation and, consequently, its own set of stats. Here is a view on the courses individually, presented in alphabetical order:

Chelmsford

Pace comment	Wins	Runners	SR%	IV
Led (4)	51	194	26.3	2.26
Prominent (3)	40	346	11.6	1.00
Mid Division (2)	22	252	8.7	0.78
Held Up (1)	30	410	7.3	0.63

Just over a quarter of the 5f handicap races at Chelmsford have seen the early leader going on to win. This is a very high percentage and worth noting. It is also worth pointing out that in races of 11 or more runners 9 of the 27 races (SR 33.3%) have been won by the front runner (IV 3.84). Not only that, another ten have been placed. Hence just over 70% of all front runners in these bigger field races have finished in the first three.

Kempton

Pace comment	Wins	Runners	SR%	IV
Led (4)	23	84	27.4	2.36
Prominent (3)	24	170	14.1	1.22
Mid Division (2)	4	72	5.6	0.49
Held Up (1)	8	177	4.5	0.39

It is a shame that Kempton seem to have so few 5f handicaps these days as the front running bias is at its strongest here. There is a decent inside draw bias here also and it should come as no surprise that front runners from the lowest three stalls have secured 11 wins from 33 (SR 33.3%). The IV is 2.88 for those well drawn pace setters. Hold up horses have a dreadful record also which is worth mentioning too.

Lingfield

Pace comment	Wins	Runners	SR%	IV
Led (4)	54	208	26.0	2.13
Prominent (3)	57	377	15.1	1.24
Mid Division (2)	16	227	7.0	0.59
Held Up (1)	31	436	7.1	0.58

Lingfield is another of the all weather courses to demonstrate a strong front-running bias over 5 furlongs. Additional insights are hard to find, although early leaders who were drawn 1 (the lowest draw) have produced 14 wins from 36 (SR 38.9%).

Newcastle

Pace comment	Wins	Runners	SR%	IV
Led (4)	22	137	16.1	1.74
Prominent (3)	37	393	9.4	1.03
Mid Division (2)	11	183	6.0	0.67
Held Up (1)	40	473	8.5	0.92

Newcastle has the weakest front-running stats of the six all weather courses, almost certainly linked (like Southwell) to it being a straight five as opposed to running around a turn, but an Impact Value of 1.74 still indicates front-runners do have an edge. Hold up horses perform quite well here so it is not a course and distance I personally get too involved with.

Southwell

Pace comment	Wins	Runners	SR%	IV
Led (4)	27	142	19.0	1.81
Prominent (3)	94	730	12.9	1.23
Mid Division (2)	4	102	3.9	0.41
Held Up (1)	14	342	4.1	0.40

The second lowest IV (1.81) for front runners, and again the straight nature of the track is likely a factor at a course where pace setters do well at other distances. Note that horses which try to come from midfield or off the pace really struggle over the five at Southwell. I have found no major additional angles to profit from, but ultimately steer clear of horses that regularly are held up.

Wolverhampton

Pace comment	Wins	Runners	SR%	IV
Led (4)	77	372	20.7	1.90
Prominent (3)	108	858	12.6	1.16
Mid Division (2)	10	190	5.3	0.52
Held Up (1)	60	897	6.7	0.61

Decent front running stats for Wolverhampton, too. Front runners when drawn close to the inside rail, (draws 1 to 3), have scored 32 times from 132 races (SR 24.2%) with an IV of 2.14.

Before I finish, we can use these numerical figures to create course and distance pace averages. I have done this by adding up the pace scores of all the winners at each course and dividing it by the total number of races. The higher the average score, the more ‘biased’ the course and distance is to horses which lead early or race close to the pace. This hopefully gives us the final piece of the jigsaw. Here are the 5 furlong handicap pace averages for the six aw courses:

Hopefully this article has demonstrated how strong the front running bias is on the all weather over the minimum trip of 5f in handicap races. The four turning courses offer a huge edge in my opinion. My next article is going to look at 6f handicaps on the all weather so watch this space!

- Dave Renham

The Importance of Pace in Three Mile Handicap Chases

7 January 2019/in Dave Renham, Horse Racing Blog/by Dave Renham

After a break of a few months I am back to look at some more pace angles in an attempt to find potentially profitable avenues, writes Dave Renham. My last pace article looked at handicap chases at up to 2m 1½f; this time, I will focus on longer distance (2m 7f to 3m 3f) handicap chases.

The data I have researched is from the past five years (2014 to 2018) for UK racing, using the Geegeez Gold Query tool.

When I talk about pace I mean the initial pace in a race, and specifically the position horses take up early on. The pace data on Geegeez is split into four – Led (4), Prominent (3), Mid Division (2) and Held Up (1). The number in brackets is the pace score that is assigned to each section.

The first set of data to share contains overall pace statistics for handicap chases of 2m 7f to 3m 3f for the period of study (a minimum number of six runners in a race).

[N.B. It should be noted that when using the Geegeez Query tool you currently need to enter the parameters 3m to 3m 2f. The Query tool uses increments of 2 furlongs and when you put in 3m - 3m2f it actually covers races from 2m 7f to 3m 3f]

Pace comment	Runners	Wins	SR%	IV
Led (4)	2282	430	18.84	1.68
Prominent (3)	4894	626	12.79	1.14
Mid Division (2)	2076	160	7.71	0.75
Held Up (1)	5086	406	7.98	0.71

Despite the fact we are looking at long distance handicap chases, we can clearly see that horses which led or disputed the lead early have a definite edge. Prominent racers have a fairly decent record too, while horses more patiently ridden early tend to underperform.

Best performing tracks for front runners (2m7f - 3m3f handicap chases)

As when I looked at 2m – 2m 1½f pace data, there are significant differences in the course figures for these contests, with some courses being much more suited to early leaders and front runners than others. Here are the courses with the best strike rates in terms of front runners at the circa three mile range (minimum 25 front runners to qualify):

Course	Front Runners	Wins	SR%
Carlisle	54	15	27.8
Sedgefield	26	7	26.9
Taunton	67	18	26.9
Kelso	62	16	25.8
Newton Abbot	69	17	24.6
Wincanton	79	19	24.1
Hexham	84	19	22.6
Plumpton	62	14	22.6
Lingfield Park	32	7	21.9
Ascot	48	10	20.8
Newcastle	45	9	20.0

For record the strike rate for Fakenham for front runners was 28.6%, but there were only 21 races so it has not been included in the table due to too small a sample.

Looking at the courses with the best impact values (IV) offers a potentially more accurate measure of front running bias. [For more information on Impact Value, click here]

Course	Impact value for Front runners
Carlisle	2.46
Taunton	2.28
Kelso	2.20
Ascot	2.14
Hexham	2.14
Wincanton	2.09
Sedgefield	2.06
Newton Abbot	2.00
Cheltenham	1.95
Hereford	1.89
Uttoxeter	1.88
Lingfield Park	1.85

As can be seen, the strike rate and IV lists are very similar, with Carlisle, Taunton, Kelso, Ascot, Hexham, Wincanton, Sedgefield, Newton Abbot and Lingfield Park appearing on both.

Poorest performing tracks for front runners (2m7f - 3m3f handicap chases)

At the other end of the scale below are the courses with the poorest stats for early leaders/front runners in handicap chases of 2m 7f – 3m 3f:

Course	Front Runners	Wins	SR%
Fontwell Park	52	7	13.5
Cheltenham	67	9	13.4
Huntingdon	56	7	12.5
Aintree	33	4	12.1
Bangor-on-Dee	66	8	12.1
Wetherby	57	6	10.5
Sandown Park	39	4	10.3

Sandown and Wetherby have not been favourable for front runners it seems, but again let us delve into the Impact Values to help to substantiate the picture. The table below shows courses that have an IV of less than 1.20 for front runners/early leaders.

Course	Impact value for Front runners
Fontwell Park	1.03
Bangor-on-Dee	1.01
Huntingdon	1.01
Sandown Park	0.95
Wetherby	0.92

Just five courses with moderate IVs and, essentially, these figures suggest that front runners at these courses win roughly as often as they should given a fair playing field (an IV of 1.00 is ‘standard’). Hence, according to the Impact Values the remaining 36 courses all have an edge for front runners varying from a small edge to a considerable one.

Course Pace Averages (CPA)

So far, I have focused solely on front runners, but now I want to try and give a more rounded course and distance profile for each course. To do this I have once again created course pace averages.

These are complied by adding up the Geegeez pace scores of all the winners at a particular course and dividing it by the total number of races. The higher the average score, the more biased the course and distance is to horses that lead early or race close to the pace. Here are all the courses listed, in course pace average (CPA) order:

Course	CPA	Course	CPA
Fakenham	3.14	Sandown Park	2.65
Sedgefield	3.06	Uttoxeter	2.64
Hereford	3.00	Chepstow	2.64
Taunton	2.93	Hexham	2.61
Ascot	2.89	Musselburgh	2.61
Doncaster	2.89	Exeter	2.60
Wincanton	2.88	Kempton Park	2.60
Lingfield Park	2.88	Newbury	2.57
Market Rasen	2.88	Towcester	2.56
Plumpton	2.87	Fontwell Park	2.53
Cartmel	2.83	Catterick	2.52
Warwick	2.82	Huntingdon	2.50
Stratford	2.80	Leicester	2.50
Perth	2.76	Ffos Las	2.49
Newcastle	2.75	Cheltenham	2.49
Kelso	2.74	Wetherby	2.46
Southwell	2.73	Bangor-on-Dee	2.43
Carlisle	2.73	Aintree	2.42
Newton Abbot	2.71	Worcester	2.41
Haydock Park	2.69	Ayr	2.23
Ludlow	2.69

These averages arguably give a more overall pace ‘feel’ to each course – as noted earlier, Fakenham (which tops the list) has had few races in reality.

It is interesting to note that Carlisle is only joint 17^th on this list having been top in terms of front runner stats. This is because 20 of the 46 races have been won by horses that gained a pace figure of either 1 or 2. The fact that there have been 15 wins for front runners has been negated somewhat by this, aided notably by the moderate performance of prominent runners (just 6 wins from 46 races).

Taking all the information at hand, I would suggest that the following four courses offer the strongest pace bias – Sedgefield, Ascot, Taunton and Wincanton.

Ascot’s overall figures are worth sharing as an example:

Pace comment	Runners	Wins	SR%	IV
Led (4)	48	10	20.83	2.14
Prominent (3)	78	10	12.82	1.33
Mid Division (2)	51	1	1.96	0.22
Held Up (1)	108	6	5.56	0.57

Having all the Ascot stats at our fingertips helps to illustrate how strong a bias there has been in recent years with 20 of 27 races won by horses that led early or raced prominently – this equates to 74%.

2m7f - 3m3f handicap chase pace data, by field size

Before I close, I want to share some different ‘splits’ in terms of number of runners. The data I have looked at for this article has come from races with 6 or more runners, so is quite a wide range. In the following three tables I have split the 2m 7f – 3m 3f handicap chase pace results into races of 6 to 8 runners, 9 to 11, and 12 runners or more.

6 to 8 runners

Pace comment	Runners	Wins	SR%	IV
Led (4)	1233	267	21.7	1.51
Prominent (3)	2296	347	15.1	1.05
Mid Division (2)	548	63	11.5	0.82
Held Up (1)	1967	202	10.3	0.72

9 to 11 runners

Pace comment	Runners	Wins	SR%	IV
Led (4)	703	111	15.8	1.55
Prominent (3)	1643	188	12.4	1.12
Mid Division (2)	746	60	8.0	0.80
Held Up (1)	1867	147	7.9	0.77

12+ runners

Pace comment	Runners	Wins	SR%	IV
Led (4)	346	52	15.0	2.12
Prominent (3)	955	91	9.5	1.35
Mid Division (2)	782	37	4.7	0.67
Held Up (1)	1252	57	4.5	0.64

Interestingly, the 12 or more runner group has comfortably the highest Impact Value for front runners, notwithstanding the understandably lower strike rate. Therefore, these data suggest that the front running bias increases as field size increases. I wonder who would have thought that?

Dave Renham

The Importance of Pace in 5f Handicaps: Part 5

20 August 2018/in Dave Renham, Geegeez Gold, Horse Racing Blog/by Dave Renham

This is the fifth instalment in a series of articles looking at pace bias in 5f handicaps, writes Dave Renham. In previous articles (the first of which is at this link, subsequent ones linked to from there) I have looked at a variety of angles including examining courses, as some offer a stronger front running bias than others; I have looked at the Geegeez pace ratings and how top rated pace horses have performed in terms of win percentages and profit/losses; I have also looked at predicting pace.

The Actual Front Runner

In this article I am going to focus solely on the actual early leader (front runner) of each race to see whether there are any patterns or decent angles that can be gleaned from the data. I have looked at 200 races once again focusing on handicap races with 6 or more runners. I have not used races where it was unclear who led early (this happens roughly 3 times in every 100 races). At this juncture, it is important for me to note that I term the front runner or early leader to be the horse that takes the lead within the first furlong. If a horse has led for 50yds and then is overtaken I assume the front runner to be the horse that took the lead after 50yds, not the horse that led just for 50yds. For the record in most sprint handicaps the horse that takes the lead in the opening strides is still leading after 1 furlong.

My first idea was to look at the leaders and what their position had been in the Geegeez pace ratings. To recap, horses on the Geegeez pace-card have their last four runs highlighted with the most recent run to the left and each horse has an individual total for their last four runs. 16 is the maximum score and 4 the minimum (this is assuming they have had at least 4 career runs).

To begin with I decided to split the runners into “thirds” like I have done in the past for draw bias. Hence in a 12-runner race, pace rated 1 to 4 would lie in the top “third” of the pace ratings, those rated 5 to 8 in the middle “third”, and those rated 9 to 12 in the bottom “third”. It should also be noted that I also adjust the pace positions when there are non-runners – for example in a 10 runner race if the 3^rd highest pace rated horse is a non-runner, then the horse rated 4th becomes 3rd, 5^th rated becomes 4^th rated, etc. Here then are the figures where the leaders/front runners came from in the pace ratings broken into ‘thirds’:

Top third of pace ratings	Middle third of pace ratings	Bottom third of pace ratings
69.5%	24%	6.5%

As you can see the early leader came from the top ‘third’ of the pace ratings roughly 7 races in 10; in addition horses from the bottom third of the pace ratings took the early lead just once in every 15 races on average. This is a positive result – perhaps the result we might expect, but it is good to see that the Geegeez pace ratings clearly help in terms of pinpointing the area where we are most likely to find the actual front runner. It is also interesting to note that in races of 12 or more runners the early leader came from the top third of the pace ratings just under 75% of the time; in races of 8 runners or less this figure dropped to 64%. This suggests, albeit with relatively limited data that using the pace ratings to try and find the front runner works best in bigger fields.

To add some more ‘meat to the bones’ I have split the pace ratings into halves rather than thirds and the table below shows the breakdown:

Top half of pace ratings	Bottom half of pace ratings
85.5%	14.5%

Hence, when you are trying to predict the front runner in a 5f handicap, the Geegeez pace ratings look the best starting point. If you can essentially narrow the potential front running candidates down to 50% of the field or less, you are giving yourself a much better chance of predicting the early leader.

As I have mentioned in previous articles, front runners in sprints over this minimum trip do have a huge edge – in this sample 22.5% of all races were won by the early leader and 51.5% of front runners made the first three. Hence the more often we can successfully predict the front runner the better.

In terms of the 200 early leaders in this sample, I next looked at their last two races and combining these last two pace figures (maximum of 8). Here are the findings:

Pace total (last two runs)	Number of races ‘led’
8	47
7	44
6	50
5	37
4	16
3	2
2	4

Thus, 70.5% of all leaders had scored 6, 7 or 8 points in total when combining their last two pace scores. This data has a similar pattern to the top ‘third’ data for the last four races, as one would expect.

Just imagine if you were able to predict the front runner in every race - you would make a huge profit. Indeed if you could achieve this correct prediction around 70% of the time I would estimate you would still make very healthy profit; remembering even if the horse you picked as the front runner does not actually lead, it can still win!

In my fourth pace article I noted that just under 40% of top pace rated horses did actually lead; I did not though look at horses that were 2^nd or 3^rd pace rated. This time I have, and in 146 of the 200 races (73%) the early leader had been in the top three of the Geegeez pace ratings.

As I hope you can see, the Geegeez pace ratings do give an excellent indication of pace set up in a race. Whether you use the top third method; the last two runs method, or the top 3 in the ratings method.

In Play Options

There are of course other punting options in terms of front running ideas. One such idea is to trade the front runner ‘in play’. The argument for this approach is logical – front runners lose around 3 and a half times more often than they win so why not trade? Horses that lead in 5f handicaps generally contract in price so why not try to make the most of this fact? Now you could trade to achieve a free bet – eg back the horse at 11.0 pre-race and lay in play at 6.0. If the horses loses you get your stake back; if it wins you have a winning bet at 5/1.

Another option for traders is ‘dobbing’ - dobbing is a term I came across a few years back – I am not sure where it originates from, but basically ‘DOB’ means ‘double or bust’. Essentially if our bet/trade is successful, we double our original stake, if it is not successful we ‘bust’ or lose our stake. It may be easier to explain by giving you an example:

Let us imagine you back a horse pre-race at 8.0 for £10; in order to create a potential DOB you try and lay at half the odds for double the stake – so a lay at 4.0 for £20. If the horse hits 4.0 or lower in running, your lay bet will be matched and regardless of the result you will win £10 (less commission). Here is the simple maths behind the two potential winning outcomes - if the horse goes onto win the race you get £70 returned from the ‘back’ part of the bet; you lose £60 on the ‘lay’ part of the bet giving you that £10 profit; if the horse does not go onto win, you lose your £10 stake from the ‘back’ bet, but gain £20 from the lay stake – again giving you a £10 profit. Naturally, if the lay part of the bet is not matched you will lose your £10.

There are other ‘in play’ trading methods/options/ideas when it comes to front runners, but I don’t want to get bogged down looking at too many of these. Suffice to say, front runners tend to contract in price; some see their price drop dramatically.

In relation to this, one thing I wanted to look at was at what point was the early front runner overtaken? The longer a leader leads over 5f, in general the shorter the price will become ‘in play’. Here are my findings:

At what point was the front runner overtaken?	% of leaders
Not overtaken (led all the way)	22.5
Overtaken in final half furlong (within 110 yds of the finish)	14
Overtaken between the furlong pole and half a furlong from the finish	19
Overtaken 1.5f from the finish to the furlong pole	23
Overtaken between the 2 furlong pole and 1 and half a furlongs from the finish	13
Overtaken before the 2 furlong pole	8.5

This should make pleasing reading for would be ‘in play traders’ – over 55% of front runners are still leading at the furlong pole; nearly 80% are leading 1.5 furlongs from the finish. There will be many of you reading this who have seen your horse lead at the furlong pole only to get swallowed up or beaten close home; perhaps now you have a trading option/idea which could potentially take away some of that pain in the future!

Actual front runners by odds

Finally, I looked at the prices of the horses that led early. Here is a breakdown:

There were 61 leaders that started 5/1 or less;
There were 52 leaders that started between 11/2 and 9/1;
There were 51 leaders that started between 10/1 and 16/1;
There were 36 leaders that started 18/1 or bigger.

So a relatively even split. Again this is almost certainly good news for ‘in play’ traders as there is excellent scope for trading front runners that start big prices. Indeed of those bigger priced runners (18/1 or bigger) 17 of the 36 were still leading at the furlong pole (a handful of these went onto win).

I hope you have found this article interesting and given you further food for thought. Maybe there should be a Geegeez competition next flat season to see who can pick pre-race the highest percentage of front runners in 5f handicaps. In fact it doesn’t have to be restricted to 5f races – maybe 5 to 7f races. Anyway, one for Matt to think about perhaps!

- Dave Renham

The Importance of Pace in 5f Handicaps: Part 4

29 June 2018/in Dave Renham, Horse Racing Blog/by Dave Renham

After hours, actually weeks of number crunching, I am able to share my most recent findings regarding pace in 5f handicaps, writes Dave Renham.

In this fourth article I have started to look in more detail at the Geegeez pace data focusing for the most part on the last four runs of each horse. Links to the first three articles are here:

Part 1

Part 2

Part 3

Horses on the Geegeez racecard have pace figures assigned to their last four runs, with the most recent run to the left. To recap the pace figures are split into four groups - Led, Prominent, Mid Division and Held Up. Pace points are given to each group - led gets 4 points, prominent 3, mid division 2 and held up 1. Therefore totals can range between 4 and 16.

My focus for this piece has been 5f handicaps (turf and all weather) with at least 6 runners from 2017. There were 465 such races in total and at present I have manually collated data for 200 of these, from which I will share my initial findings. The plan next month is to complete the research and report back on the results for all the races. Handicaps are generally the best medium for this type of research because one is usually dealing with seasoned campaigners who have raced many times in their careers.

I have noted before that front runners have a significant edge in these short sprints and this is clearly seen from the pace figures of these 200 winners:

Pace figure of winner	4	3	2	1
Win %	25%	43.5%	8%	23.5%

As we can see 25% of all races have been won by the horse that took the early lead. Considering front runners made up around 13% of runners in the sample, we can say that front runners have won nearly twice as often as they should (25% versus 13%); this is assuming all horses have an equal chance in each race. Of course, that may not necessarily be the case, but the 13% figure is not going to be too far away from the true chance. For the record, prominent racers provided 40% of all horses so this pace bracket also win slightly more often than ‘one would expect’; horses that raced mid-division provided around 13% of all runners so have under-performed statistically, as have hold up horses who provided around 34% of all the runners.

As I have mentioned in previous articles, with such an advantage in 5f handicaps it makes sense to investigate ways of trying to predict the front runner. In the third article I looked at the most recent race only and the pace figure gained from it. This time I am going to look at the performance of the top-rated pace runners using the last four races.

In each of the 200 races I collated the pace figures for each horse by putting them in order of pace points, then looking to see from which pace position the winner came. I was hoping of course to see a bias towards the top-rated pace horses in terms of number of wins.

Here are the findings:

Pace rank	Wins	Races	SR%
1	26	200	13.0
2	21	200	10.5
3	26	200	13.0
4	31	200	15.5
5	23	200	11.5
6	17	200	8.5
7	21	179	11.7
8	10	153	6.5
9	10	127	7.9
10	4	96	4.2
11	7	68	10.3
12	2	48	4.2
13	1	32	3.1
14	1	22	4.5
15+	0	9	0.0

Hence the top-rated pace horse (the one with the most pace points) won 26 of the 200 races (13%). On the face of it this does look a little disappointing. It should also be stressed at this point that there may have been 200 races, but due to several of these having joint top-rated pace horses, there were in fact 266 horses that were top- or joint-top ranked.

That brings the win strike rate down to under 10%. Before you reach for the Kleenex, I do have some positive news. If you had backed these top-rated pace horses to level stakes, your 266 selections would have yielded a small profit to SP. Even better returns would have accrued if you had backed them at Betfair SP – at £10 per bet the profit after commission would have been just under £530. This equates to a return of about 20p in the £. Very satisfactory returns for what is essentially a simplistic method.

With a notable difference between the number of winning front-runners and the number of winners with the highest pace rank coming into the race, what these findings indicate once more is that predicting the front runner is far from an exact science. It is clearly not just a case of picking the horse in the race with the most pace points from their last four runs. What that table does seem to indicate though is that the more points you have the more chance you have of winning.

The top-rated pace horse did lead in nearly 40% of the races; the table below shows the run style of the top-rated pace horse in the reviewed races:

Pace Figure	Races	% of horses
4 – Led	105	39.5
3 – Prominent	106	39.8
2 – Midfield	23	8.6
1 – Held up	32	12.0

So those top-rated pace horses coming into a race have generally led or raced up with the pace, which is clearly what one would expect. However, when I started this series of articles I was hoping to find a method that would predict the front runner at least 50% of the time, if not 60%. Not around 40%! It is interesting to note that in the third article I found that horses that had led in a 5f handicap last time out, went on to lead in their next race 42.5% of the time. So perhaps the most recent race is more important than combining the last four when looking at pace figures, though in truth the difference in terms of the sample size is negligible.

My next port of call was to look at the actual pace figure gained by the top rated or joint top-rated pace horse. 16 (four pace figures of 4) is the highest pace figure a horse can achieve.

Here are the findings:

4 race pace total (top rated horses only)	Wins	Runs	SR%
16	2	31	6.5
15	8	78	10.3
14	7	87	8.0
13	5	32	15.6
12	2	32	6.3
11	2	5	40.0
10	0	1	0.0

These figures suggest nothing particularly clear cut at this stage – however, when I have looked at all 465 races hopefully a pattern may start to emerge.

Before moving on I would like to discuss a theory. There is a perception that if there are two or more potential front runners in a race, then that race will be set up for a ‘closer’. The theory is that there will be a strong battle for the lead where the leaders essentially ‘cut each other’s throats’ – allowing a horse to come from off the pace and win.

I wanted to try and test this theory as best I could. I decided therefore in each race to work out the pace average of the top four rated pace horses. If the theory held any validity, then I expected the record of the top rated pace horse would be poor when the four horse pace average was higher. Here are the findings:

Top four rated pace average	Top rated pace runners	Wins	SR%	BSP profit to £10 stakes	ROI%
14 and above	48	3	6.3	– £220	– 45.8
13 to 13.75	77	5	6.5	– £193	– 25.1
12 to 12.75	69	5	7.2	– £232	– 33.6
11 to 11.75	51	7	13.7	+ £363	+ 71.2
9 to 10.75	21	6	28.6	+ £320	+ 152.4

It seems that this theory does hold water, although I appreciate that not all top-rated pace horses lead. Having said that most top-rated pace horses race up with the pace and thus are not coming from ‘off the pace’ to win. The races where the top four horses averaged 14 or above produced the lowest strike rate and the worst returns. Conversely the races with relatively low averages produced extremely positive returns.

I have also looked at the combined win and placed strike rates to see if they correlate with the win strike rates:

Top four rated pace average	Top rated pace runners	Wins / places	Win/placed SR%
14 and above	48	10	20.8
13 to 13.75	77	19	24.7
12 to 12.75	69	22	31.9
11 to 11.75	51	19	37.3
9 to 10.75	21	12	57.1

It is pleasing to see the win and place strike rates increase as the four horse pace average decreases – just like the win data showed.

This takes me onto the second theory where there is a perception that if there is just one ‘genuine’ front runner in the race, that runner has a good chance of getting a ‘soft’ lead and this increases their prospects of leading all the way. The table above seems to suggest when there is less ‘pace’ in the race, potential front runners have a better chance of winning. However, we cannot be sure that a race with, say, a top four rated pace average of 11 has a sole front runner. Consider the following two scenarios:

Scenario 1: Pace average of top four pace horses = 11

Horse A – 15

Horse B – 10

Horse C – 10

Horse D – 9

Scenario 2: Pace average of top four pace horses = 11

Horse A – 12

Horse B – 12

Horse C – 11

Horse D – 9

One way to perhaps test this ‘soft’ lead theory is to look at the gap between the top rated pace horse and the second top rated pace horse. Here are these findings looking at the performance of the top rated pace horses in each case:

Gap between top and 2^nd rated	Top rated pace runners	Wins	SR%	BSP profit to £10 stakes	ROI%
0	126	10	7.9	– £364	–28.9
1	75	4	5.3	– £495	–66.0
2	44	7	15.9	+ £323	+73.4
3	15	4	26.7	+ £525	+350.0
4	5	0	0.0	– £50	–100.0
5	1	1	100.0	+ £85	+850.0

This once again is not a perfect test because the top rated pace runner does not always lead! However, what it does seem to suggest is that the top rated pace horse has done extremely well when there has been a gap of at least 2 points between them and the second rated. I appreciate the data set is relatively small, but nonetheless the signs are good. I did look at the win and placed data here and the correlation was less strong – the problem perhaps is the data set for a gap of 3 or more is so small. I will revisit this after looking at all the races and share that data. [Alternative theory for lack of place correlation is that trail blazers are often binary types, who either win or drop out completely – Ed.]

For the final part of this article I want to look at the profile of the 200 winners in terms of pace. I initially looked at their four race pace totals and noted that 128 winners (SR 64%) had a total of 10-16 while 72 winners (SR 36%) had a total of 4-9. It seems therefore at first glance that the horses with higher pace ratings have outperformed those with lower ones. However, we can all manipulate data and hence we need to know how many runners were in each of the two pace brackets. Fortunately we have a relatively even split as the table shows:

4 race totals for all runners	Win SR%	% of actual runners in all races
Between 4 and 9	36%	48.5%
Between 10 and 16	64%	51.5%

To clarify this means that horses with a pace total of 10 or higher (from their last four runs) have won 64% of all races from 51.5% of the total runners. Hence, as we would have hoped, horses with higher pace ratings do perform better in 5f handicaps than lower pace rated horses. In reality if ‘pace’ made no difference whatsoever then these horses should be winning 51.5% of races not 64% - in reality, they are roughly 1.25 times more likely to win than statistically they ought.

So, it’s time now to start looking at the other 265 races to see whether the statistical patterns noted in this article are replicated over a bigger sample. At present we can make the following observations:

Front runners have a huge edge in 5f handicaps
Top pace rated runners (using the last four races) have a relatively low strike rate but have shown a 20% profit to BSP
Top pace rated runners have taken the early lead around 40% of the time (led or raced prominently in just under 80% of races)
Top pace rated runners have a much better strike rate in races where the top four pace rated runners produce an average of less than 12
Top pace rated runners have a much better strike rate in races where they have a 2 point or bigger gap to the second pace rated horse
Horses pace rated 10 win almost twice as often as those rated 9 or lower

*The fifth and final part in this series can be found here*

- Dave Renham

The Importance of Pace in 5f Handicaps: Part 3

3 June 2018/in Dave Renham, Geegeez Gold, Horse Racing Blog/by Dave Renham

In my first two articles I looked at pace in five-furlong handicaps focusing primarily on courses, writes Dave Renham.

Part 1, which then links to Part 2, can be found here.

The data suggest that some courses offer a much stronger pace edge than others. However, all the research points to the fact that front runners in 5f handicaps have a definite edge almost regardless of where the race is being run. When I say ‘definite edge’ perhaps I should clarify that front runners win far more often than statistically one might expect.

To recap, when I talk about pace my main focus is the initial pace in a race and positions the horses take up in the opening couple of furlongs. As mentioned before the Geegeez website splits pace data into four groups - Led, Prominent, Mid Division and Held Up. These groups are assigned numerical values – led gets 4 points, prominent 3, mid division 2 and held up 1. When I used to tip ‘back in the day’, I created similar pace figures, but used values from 5 to 1, and also used the last six runs rather than the last four. I don’t think there will ever be a ‘perfect’ method for creating pace figures, but I am sure the Geegeez method is as good as any.

Horses on the Geegeez racecard pace tab (data view) have their last four UK/Ire runs highlighted, with the most recent run to the left and each horse has an individual total for their last four runs. Hence the highest last four races pace total a horse could achieve is 16 (four 4s), while the lowest is 4 (four 1s). This is assuming of course that they have had at least four career runs.

With such an advantage in 5f handicaps it makes sense to investigate ways of trying to successfully predict the front runner. One starting point would simply be to look at the horse’s combined pace figures in the race in question and choose the horse with the highest figure. Let us look at a recent example to help make this idea clearer to the reader. The race was run on the 31^st May at Hamilton – it was a 5 furlong handicap with 7 runners. Pre-race the 7 runners had the following pace totals:

5f sprint pace tab example

One difficulty for predicting the front runner in this particular race was that you had three horses at the top with very close figures. Also none of the runners had led a race early in more than one of their last four starts meaning that they were not ‘out and out’ front running trail-blazers. As the race panned out, the three most likely front runners took up the first three positions early on: Jabbarockie led narrowly to Jacob’s Pillow who in turn raced just ahead of Dapper Man. Hamilton’s 5f favours front runners reasonably strongly, as can be seen from the green pace ‘blobs’ in the image, and not surprisingly perhaps the winner and runner up came from these three.

As we can see, this race panned out in a very similar way to how the pace figures had predicted it would. However, correctly predicting the front runner of the top three rated was clearly not ‘a given’. This of course is one of the problems with blindly going for the highest rated pace horse. Having said that, one would expect the highest rated pace horse to lead far more often than the lowest rated pace horse! My aim is to look at this idea in more detail in the future.

For this article I am using a slightly more simplistic approach. I am focusing on the most recent race only. To begin with I looked at horses that gained a pace figure of 4 (by leading early) last time out in a 5f handicap to see what pace figure they achieved in their very next run. I was hoping of course that a decent percentage led early on next time out. Here are my findings:

Pace figure

(next run after leading over 5f LTO)

% of runners

42.5%

39.2%

8.3%

10.0%

This is quite encouraging with 42.5% of runners leading on their very next start. In addition less than 20% of them raced midfield or further back in the pack early on. At this juncture, it should be noted that horses that were taken on for the lead last time out scored slightly lower in terms of leading next time (led roughly 34% of the time). These are the horses that gained comments such as ‘with leaders’, ‘disputed lead’ etc – for the record these runners still gain a 4 score for these comments.

I then looked at the data for horses that had gained a 4 pace score last time out in 6f handicaps. 6f races are still considered sprints, and the front runner generally has an edge in these races too. However, this edge is less strong than it is over 5f. I was intrigued however to see how the next time out figures panned out – would last time out front runners, lead again? This is what I found:

Pace figure

(next run after leading over 6f LTO)

% of runners

31.0%

44.4%

12.5%

12.1%

Down to around 1 in 3 who managed to lead next time, although 75% either led or tracked the pace (which I guess can be taken as a positive). The figures for horses that were taken on for the lead last time out again scored lower (just 21% of these runners led next time).

It seems sensible given this initial data to concentrate on 5f handicaps for the remainder of this article. This does not mean we cannot gain a pace edge over other race distances too, but I feel the front running bias works best over the minimum distance of 5f.

My next port of call was to look at horses that had gained a pace score last time out in 5f handicaps of 1 – these are the horses that raced at the back of the pack LTO. I was hoping to see that they predominantly raced at the back of the pack early on in their next run, or at least did not lead early very often. This is what I found:

Pace figure (next run after a pace score of 1 LTO over 5f)	4	3	2	1
% of runners	7.9%	35.5%	22.1%	34.5%

Interestingly a pace score of 3 has been achieved the most, although a score of 1 was not far behind. Pleasingly from a research point of view only 8% of runners that were held up at the back LTO scored a 4 and led early on their next start. The stats suggest therefore that horses that gained a 4 pace score LTO in 5f handicaps are over 5 times more likely to lead next time out than horses that gained a 1 pace score.

There are of course many factors that determine how likely a horse is to lead – not just their pace score over their last four runs, or their pace score LTO – but as I have alluded to earlier the pace competitiveness of the other runners in the race. One huge factor that has to be taken into account is the draw at certain courses. If we look at Chester over 5f one can see that it is extremely difficult to lead from a wide draw. In handicaps with 8 or more runners horses from the top third of the draw have managed to take the early lead just 13% of the time. This drops to a measly 7.5% when there have been 10 or more runners. Chester is not unique in that respect either – Beverley in 5f handicaps (10 runners or more) has seen the top third of the draw lead early just 16% of the time whereas the bottom third of the draw has assumed an early advantage 52% of the time. Thus the draw must be factored in at some courses.

I looked next at whether leading in a bigger field made it more likely you would lead next time – my theory being that to lead a bigger field would need more early pace than if you were running in a smaller field. I looked at 5f handicaps with 12 runners or more, and it should be noted that if the race had split into more than one group, I chose the overall leader only. However, the figures virtually matched the overall 5f figures as the table below shows:

Pace figure (next run after leading over 5f LTO in a 12+ runner race)	4	3	2	1
% of runners	42.4%	39.8%	7.6%	10.2%

My next port of call was looking at horses that had won a 5f handicap LTO by making all the running – these runners earn comments such as ‘made all’, ‘made most’, ‘made virtually all’, etc. My theory was that horses in form that had led LTO were more likely to lead on their very next start. This time, the data backed up the theory:

Pace figure (next run making all or making most over 5f LTO)	4	3	2	1
% of runners	51.2%	36.8%	4.8%	7.2%

For the first time we exceed the 50% mark in terms of horses that lead.

Perhaps at this juncture it is worth elaborating on why being able to predict the front runner in 5f handicaps is worth the effort. It has been noted that front runners win more often than they should statistically, but the key point is that they potentially offer huge profits. Now clearly you are never going to be able to predict the front runner all the time, but the higher percentage you achieve, the greater your chances of making decent long term returns.

Finally in this article I want to offer another approach in terms of trying to predict the front runner in 5f handicaps – this is simply focusing on individual horses that traditionally have shown a desire to lead early. Now, this is likely to limit your potential bets considerably but if you were able to create a list of say 25 such horses you would have a good chance of turning the stats in your favour. Let me look at one such horse – Bosham. At the time of writing (June 1^st 2018), Bosham has raced 67 times in his career and has led early in 41 of those races – this equates to 61.2% of the time. We can improve upon this by digging a bit deeper into his record: it improves to 63.8% in 5f races; in 5f races in single figure fields (9 or less runners) this improves to 71.4% (from 21 races); in 5f races running round a bend this improves to 76% (from 25 races).

Bosham last raced on the 31^st May at Chelmsford over 5f. This race was also a good example of when the Geegeez pace stats for the last four runs have worked perfectly. These were the runners in the race with their pace totals:

Bosham was a very likely leader on a speed-favouring track, and prevailed at 7/1

Bosham looked the most likely front runner having led in each of his last four starts and so it proved. Of course if you had looked at his career record this would also have pinpointed him as a likely front runner. Another positive was that he had a decent draw in 4 which meant he was close to the favoured inside rail. As it turned out, Bosham led early and went on to win relatively unchallenged at 7/1. For the record the joint-second rated pace runner, Crosse Fire, a 16/1 shot, raced in second early on before fading into fourth in the final furlong.

The data in this article cements the fact that early pace is be a highly significant factor in horseracing, and 5f handicaps in particular. Geegeez Gold offers users the insight for any race within the Pace tab, and subscribers are strongly encouraged to take some time to get to grips with it. Such time investment is quite likely to generate a robust financial return.

***Part 4 can be viewed here***

- Dave Renham

p.s. if you're not yet a Gold subscriber, you can get a taster of the pace functionality either by registering as a free user and checking the pace in our free Gold races (up to six daily), or you can take a 30 day trial for £1. Click here to start your trial.

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Tag Archive for: Dave Renham

General 'Recent Form' Trainer Statistics

Trainers with a yearly win strike rate of 8% or less

Trainers with a yearly win strike rate of between 9% and 12%

Trainers with a yearly win strike rate of between 13% and 16%

Trainers with a yearly win strike rate of between 17% and 20%

Trainers with a yearly win strike rate of 21% or more

Individual 'Recent Form' Trainer Statistics

Individual Trainer Angles to Note

Summary

Does the market position of the horse on debut make any difference in their next few runs?

How successful are beaten favourites on their next start?

Is wearing blinkers for the first time a positive or a negative?

How does the weight a horse carries in a handicap chase affect the result?

What percentage of races are won by a horse from the top three in the betting?

Have you any breeding stats that will help with my National Hunt betting?

Are there any trainers who do particularly well in bumpers?

Which trainers do best with horses that make their career debut in a hurdle race?

At the Cheltenham Festival Irish trainers seem to excel. What is the record of Irish trainers in all UK National Hunt Races?

Trainers with sole runners on the day – are any worth following?

What is the comparison of novice chase debutants with horses having their second chase start in a novice chase?

Ryan Moore Introduction

Ryan Moore: Overall Record

Ryan Moore: UK v Ireland

Ryan Moore: Record by Year

Ryan Moore: Record by Betting Odds / Price (SP)

Ryan Moore: Record by Distance

Ryan Moore: Record by Course

Ryan Moore: Record by Trainer

Ryan Moore: Record by Run Style

Ryan "More": Extra stats and nuggets

Ryan Moore Main Takeaways

What is negative draw bias?

Examples of negative draw bias

A system from the '90s

Identifying negative draw bias horses (and a shortcut)

RACE 6 - 4th July – 4:55 Epsom

RACE 7 - 5th July – 3:15 Haydock

RACE 8 - 8th July – 8:40 Newbury

RACE 9 - 17th July – 12:35 Beverley

RACE 10 - 17th July – 3:40 Beverley

Putting ‘Negative Pace Bias’ to work for you

6 to 8 runners

9 to 10 runners

11 or more runners

Chelmsford

Kempton

Lingfield

Newcastle

Southwell

Wolverhampton

Best performing tracks for front runners (2m7f - 3m3f handicap chases)

Poorest performing tracks for front runners (2m7f - 3m3f handicap chases)

Course Pace Averages (CPA)

2m7f - 3m3f handicap chase pace data, by field size

The Actual Front Runner

In Play Options

Actual front runners by odds

Pace figure of winner

4

3

2

1

Pace rank

Wins

Races

SR%

Pace Figure

Races

% of horses

4 race pace total (top rated horses only)

Wins

Runs

SR%

Top four rated pace average

Top rated pace runners

Wins

SR%

BSP profit to £10 stakes

RACE 6 - 4^th July – 4:55 Epsom

RACE 7 - 5^th July – 3:15 Haydock

RACE 8 - 8^th July – 8:40 Newbury

RACE 9 - 17^th July – 12:35 Beverley

RACE 10 - 17^th July – 3:40 Beverley

Gap between top and 2^nd rated