Yearling Sales vs. Breeze Ups: Where Should You Buy?

Introduction

There are two options for buying racehorses with a flat campaign in mind – the Yearling Sales or Breeze Ups. At the Yearling Sales, which take place in the Autumn, horses are sold unbroken, wheras at the Breeze Ups, which take place the following Spring, part of the sales process is that the horses catalogued breeze for 2 furlongs. Breeze times are used by many as an input into their buying decision. Breeze Up sales have their critics. Young horses being pushed too hard, too young, with a preparation  that instills poor habits (‘boiled brains’), horses do not train on and are more prone to a lack of soundness. Added to that is a perception that horses sold at the Breeze Ups are expensive for what you get. There also exists the perfect totem for Breeze Up critics – The Green Monkey, who breezed in sub 10 seconds, was bought for $16m by Coolmore and never won a race. So is what happened with The Green Monkey indicative of what happens with many Breeze Up graduates? Or can a variant of Godwin’s Law be invoked, so that anyone who mentions The Green Monkey in a discussion regarding the merits of Breeze Up sales has automatically lost the argument? In this blog post the graduates from  Tattersalls Yearling Sales from the Autumn of 2011 are compared with the graduates from the Spring 2012 Breeze Up Sales that took place at Kempton (Ready to Run), Tattersalls Guineas, Tattersalls Craven and DBS. Racecourse performance is compared, along with prices paid.

Methodology

The analysis that underpins this piece was carried out in the R statistical environment accessing Raceform Interactive (RFI) data. This is the same data used by the Racing Post.  Sales information and racecourse performances (wins, runs, ratings) for the 2012 and 2013 flat seasons were collected. For analysis of racecourse performance horses were categorised as coming from either yearling sales, or breeze ups. Horses that sold at more than one sale were placed according to the category of the latest sale.

Catalogue Numbers, Appearance Rates and Withdrawals

Table 1 shows the number of horses in each sale category and the number of horses that went on to compete in a race. the appearance rate for Breeze Ups is 72%, higher than that for the Yearling Sales. The underlying data is from RFI, which records all GB and Irish racing and higher grade overseas races. Sales graduates that raced overseas at a lower level will not be included and so there is a degree of under-reporting in Table 1.  It is possible the Yearling Sales would be more affected by this than the Breeze Ups when overseas buyers are considered, even taking this into account there is little evidence that horses prepared for Breeze Ups are less likely to reach the racecourse.

The withdrawn columns show the numbers/percentages of horses that are withdrawn from sale but subsequently race. The withdrawal rate is twice as high for Breeze Ups. Because horses have to do more at the Breeze Ups than the Yearling Sales, it is not surprising a higher withdrawal rate exists. Consignors do not wish to jeopardise the sale value by sending horses to the Breeze Ups that are not ready to do themselves justice.

Category Catalogued Raced Raced (%) Withdrawn Withdrawn
Yearling Sales 1670 1137 68% 78 4.7%
Breeze Ups 601 434 72% 58 9.7%
Grand Total 2271 1571 69% 136 6.0%

Table 1: Catalogue sizes, appearances and withdrawals by category

Sales Prices

Table 2 shows the number of horses that were sold by category, as well as median, average and maximum prices. Sales exclude vendor buybacks and horses not sold, and the yearling sale numbers exclude those horses that went on to be sold at Breeze Ups. The median sale price was £38,000 at the Yearling Sales and £30,000 at the Breeze Ups. Averages and maximum sale prices were also higher for the Yearling Sales.  These numbers exclude any saving on training fees that accrues from buying ca. 6 months later at the Breeze Ups.

Category Number Median (£) Average (£) Maximum (£)
Yearling Sales 809      38,000             65,972   700,000
Breeze Ups 291      30,000             42,711   300,000

Table 2: Sale Information by category

Ratings Achieved by Sale Category

Table 3 shows, for each sale category, the median of the maximum rating achieved by each horse over its racing career in 2012 (2 year old) and 2013 (3 year old). Medians are also given for ratings achieved first time out, and considering the racing career in 2012 as a 2 year old only. The results for Yearling Sales and Breeze Ups are very similar. At the end of their 2 year old career ratings are both 69. At the end of their 3 year old career they are both 74. Horses sold at both types of sale are of similar quality and progress similarly from age 2 to age 3.

Ratings for first time out runs are lower for Breeze Up horses at 57.5 versus 60 for Yearling Sales graduates. This is an unexpected result. Breeze Up horses progress further from their first run to their maximum than horses sold at the Yearling Sales. The difference isn’t large, however the view that Breeze Up horses are as ready as they can be for racing isn’t borne out by the data. A possible explanation is as follows: Breeze Up consignors are concerned to get their horses to the sales, not wanting them to break down, as a result they veer on the side of caution and under rather than over prepare their horses. When these horses arrive with trainers, they fear the horses have been over prepared, given the reputation that exists for Breeze Up graduates, and the horses are trained more cautiously than Yearling Sales graduates that have been in their charge for longer. The end result is that Breeze Up graduates post lower ratings first time out than Yearling Sales graduates.

Category Rating Rating 1TO Rating 2yo Highest Rated
Yearling Sales 74 60 69 118
Breeze Ups 74 57.5 69 118

Table 3: Ratings by category

Win Rates and Runs per Horse

Win rates for Yearling Sales and Breeze Ups are similar, with 58% of Breeze Up and 55% of Yearling Sale graduates going on to win races. The number of runs per horse is higher for Breeze Ups graduates. The difference is 1.2 races per horse when all races as a 2 year old and 3 year old are considered. It is possible that the Breeze Up preparation selects horses that are able to withstand racing, and buyers are able to identify these horses at the Breeze Ups.

Category Win Rate Runs/Horse all Runs/Horse 2yo
Yearling Sales 55.3%                7.5                    3.7
Breeze Ups 58.0%                8.7                    4.2

Table 4: Win rates and runs per horse

Summary

A comparison of  racecourse performance and sales prices for ca. 1,500 Yearling Sale (2011) and Breeze Up (2012) graduates shows the following:

  • Breeze Up horses sold more cheaply
  • A similar proportion of horses reached the racecourse
  • Ratings achieved were similar
  • Breeze Up horses progressed somewhat more from first run to their maximum rating
  • Win rates were similar
  • Breeze Up horses ran more often

There is little evidence that the criticisms levelled at Breeze Ups are justified, with both types of sale offering opportunities to buyers.

More detailed performance information is available from www.breezeupwinners.com

Does Buying at Tattersalls Book 1 Lead To Guaranteed Success? Prices Paid vs. Racecourse Performance For The 2007 Graduates

Introduction

Record prices paid at the recent Tattersalls 2013 Book 1 Yearling Sale have hit the headlines. A Galileo filly, full sister to Oaks winner Was, sold for a record breaking G5m (G = guineas). The median price paid for a yearling came in at G130,000, an increase of 30% over 2012. Today (14th October 2013) the Book 2 sale starts, followed by Book 3 one week later. Yearling are categorised into the three books by Tattersalls based upon a range of criteria, including pedigree and confirmation. Book 1 is the most prestigious and its graduates typically sell for more than Book 2 graduates, which in turn sell for more than Book 3 graduates.  So how do the graduates of Tattersalls Yearling Sales perform on the racecourse? In common with all of the sales companies any Tattersalls graduate winning a prestigious race results in a tweet and/or email proclaiming where the horse was sold. But how do the graduates of the sales perform in aggregate? Trainer George Baker in a recent blog post alludes to the reality that some of these graduates will end up plying their trade at a basement level.  In this blog post the racecourse performance of all of the 2007 graduates from Books 1, 2 and 3 Tattersalls Yearling Sale is examined. The maximum rating achieved by each horse between 2008 and the end of the 2012 flat season was extracted from the Raceform database, including information from maidens, handicaps and pattern races and the ratings and race performance compared with their yearling sales price.

Yearling Sale Prices By Book

Over 1,500 yearlings were catalogued at Tattersalls Yearling Sale in 2007. Excluding those withdrawn, not sold or bought back, 1,136 yearlings were sold. The Book 1 median was G80,000, twice the Book 2 median of G40,000, with the Book 3 median coming in at G12,000.

Book Sold Median (G) Max (G)
1 447        80,000 1,000,000
2 393         40,000     300,000
3 296         12,000       72,000

Table 1: Tattersalls 2007 Yearling Sale Prices

 

Sale Prices & Subsequent Ratings

How do the graduates from this sale perform on the racecourse? Graph 1 below shows the relationship between prices paid and subsequent maximum rating achieved by each horse. The y axis has rating and the x axis sale price. The relationship is noisy. The correlation between price paid and subsequent rating is 0.20. If log prices are used so that the effect of some of the higher priced lots is dampened, the correlation increases to 0.28. At first glance it doesn’t appear as if much of a relationship exists at all. Does this suggest the work of bloodstock agents, trainers and owners trying to identify the best yearlings is of limited benefit?

Prices Vs. Ratings

Graph 1: Tattersalls 2007 Yearling sale price (G) vs subsequent rating

 

Book Membership & Ratings Achieved

In common with much of the data in horse rating, aggregation enables relationships to be identified.  Table 2 gives the median rating achieved across all of the graduates for each of Books 1, 2 and 3. The best horse from Book 1 posted a rating of 135, the best horse in Books 2 and 3 posted similar ratings of 120 and 119 respectively. The median rating achieved by Book 1 graduates was 78, for Book 2 graduates 73.5 and for Book 3 graduates 68. So a relationship between price paid and subsequent rating does exist when the results are aggregated to the Book level. Note that improvements in ratings become progressively more expensive to buy. In trading up from Book 3 to 2, an extra G28,000 bought you an additional 5.5 points of rating, whilst in trading up from Book 2 to 1 you needed to spend an extra G40,000 to garner an additional 4.5 rating points.

Book Median Rating Max Rating
1 78 135
2 73.5 120
3 68 119

Table 2: Ratings achieved across Books 1, 2 & 3

Wins Rates in Maidens, Handicaps & Pattern Races

Table 3 gives the number of individual winners that came out of each book by race category, table 4 shows the same information expressed as a percentage of horses that sold in each book. The numbers do not sum to the total column because a horse can be a winner in each of the three race categories but only once in total. About half of all graduates from the Tattersalls 2007 Yearling Sales are still maidens and the proportion of yearlings that won at least one race seems to be little affected by the Book in which you wrre sold. However the benefits of buying from Book 1 become clear. Nearly twice as many graduates from Book 1 go on to win pattern races compared with the graduates of Books 2 and 3. Book 1 graduates also win the highest proportion of maidens. This result should probably be upgraded because they are likely to have to contest open maidens, which by their nature are the most competitive. Their sales price and stallion fee would preclude them from competing in auction and median auction races. There is also a knock on effect when open maiden horses go on to compete in handicaps. Race standards applied by the handicapper, allied to his ‘on a line through’ methodology, means that the handicap marks of Book 1 graduates may  leave less room for manoeuvre than the graduates of other books. It is also likely that Book 1 graduates will be trained with a view to possible Pattern company participation, thus competing in maiden company closer to full fitness than the graduates of other books. As a result Book 1 graduates that end up in handicaps could well be doing so on marks that most closely reflect their ability. All of these arguments can be reversed when the graduates of Book 3 are considered.

Book Maidens Handicaps Patterns Total
1 155 126 34 239
2 118 121 16 188
3 84 98 10 152
Total 357 345 60 579

Table 3: Individual winners by Book in Maidens, Handicaps & Pattern Races

Book Maidens Handicaps Patterns Total
1 34.7% 28.2% 7.6% 53.5%
2 30.0% 30.8% 4.1% 47.8%
3 28.4% 33.1% 3.4% 51.4%
All 31.4% 30.4% 5.3% 51.0%

Table 4: Percentage of individual winners by Book in Maidens, Handicaps & Pattern Races

Differentiation Within Books: Does Paying More Work Within Books?

In aggregate the more expensive horses perform better on the racecourse. Is there much difference in subsequent performance if the more expensive Book 1 graduates are compared with those that sold more cheaply from Book 1? Each Book was sorted and split into a top half and bottom half group based upon sale price. The median rating of each group was calculated. Table 5 shows the median price and rating for each of the top half and bottom half by Book. There is a clear relationship between sales price and subsequent rating within each book. In each book the difference is about the same at 9 rating points. The more expensive Book 1 graduates ended up with higher ratings than cheaper Book 1 yearlings. The same is true of Books 2 and 3. In each case the difference in median ratings is about 9 points. It is noteworthy that the incremental cost of each additional rating point depends on your starting rating. In Book 3 it costs G1,800 for every extra rating point, whilst in Book 2 it is G5,455 per point and in Book 1 G21,250. In this respect yearlings trade in much the same way as other trophy assets.

When pattern race winners are considered the more expensive graduates of Books 1 and 2 have more winners than those that sold more cheaply – it is most striking in Book 1, with 24 pattern race winners versus 10 from the bottom half. Table 6 gives this information by Book. The usual caveats apply with respect to interpretation given the small sample sizes.

When median ratings are compared the more expensive graduates of Book 1 performed best, followed by the more expensive graduates of Book 2. However the next best performer is a tie between the more expensive Book 3 graduates and the cheaper yearlings from Book 1.  Yet the more expensive Book 3 graduates have a median sales price less than half that of the cheaper Book 1 graduates, albeit with fewer pattern race winners. If there can ever be value in buying yearlings it appears that, at least in 2007, buying the most expensive Book 3 graduates paid off on the racecourse. It is possible this result is an artefact of the 2007 yearling draft, looking at the results from other years would answer this query.

Median Price Median Price Median Rating Median Rating
Book Top Half Bottom Half Top Half Bottom Half
1         165,000         46,500 82 73
2           70,000         24,000 79 69
3           21,000           6,500 73 64.5

Table 5: Prices paid and ratings within books

 

Book Top Half Bottom Half
1 24 10
2 10 6
3 6 4

Table 6: Pattern winners by book top and bottom half

Summary

Results from the Tattersalls Yearling Sale from 2007 show a noisy relationship between individual sales price and subsequent rating. However in aggregate the relationship becomes clear – the more expensive yearlings, taken as a group, subsequently performed better on the racecourse. It is when pattern races are considered that the benefits from buying at Book 1 were at their most apparent. The median sale in Book 2 took place at G40,000. In Book 1 this doubled to G80,000. Whilst it might seem poor value that spending twice as much resulted in an increase of just 4.5 rating points in the median ratings for Book1 versus Book 2, it nearly doubled the chances of buying a yearling that went on to win a pattern race. Yearlings are priced off the right had tail of the distribution of expected future ratings, and it is the right-hand skewness inherent in the expected future ratings of Book 1 yearlings that causes them to sell so much more expensively than yearlings catalogued in Books 2 and Book 3. The lottery ticket you buy when shopping at Book 1 has a much greater chance of coming up. When prices within Books are considered the same relationships are confirmed. Buying the more expensive graduates from within each Book resulted in higher ratings than attempting to bargain hunt amongst the cheaper yearlings in each Book. In Book 1 buying the more expensive yearlings resulted in nearly 2.5x as many pattern race winners. Now the noisiness of the relationship shown in Graph 1 above means that bargains were available at all prices and in all books, however the probability of buying a bargain yearling that subsequently performed well at the racecourse was maximised if you bought from amongst the more expensive Book 3 graduates.

Top Rated Selections: Often A Long Wait Between Drinks – Why?

Introduction

Tune in to Racing UK or ATR and the chances are the focus will be on picking the winner of the next race. The Racing Post has pages of form and commentary distilled into selections, naps and tips, typically resulting in one selection per race being made. Tipsters tables contain one selection per race,  Tom Segal’s Pricewise column in the Racing Post usually recommends one and occasionally two selections in a handful of Saturday races. For any gambler the key measure of success is the amount of money made or lost over a reasonable time period, and implicit in the various pieces of advice on offer is that one selection per race is the way to achieve gambling success. It seems obvious – there can only be one winner, I just need to find it! One of the consequences of making one selection per race is that you are maximising the chances of sustaining a long losing run. The volatility of your profits/losses are also maximised, as is the path dependency of your trading strategy. None of these are attractive characteristics.  Apart from the effect on your bank balance, losing runs can lead to self-doubt as methodology and existence of a trading edge are questioned, yet the length of the losing run  may be just noise, in line with what you might expect given the size of your trading edge. So what sort of losing runs might you expect given different degrees of edge over the market?  In this blog post Monte Carlo Simulation (MC) is used to compare losing runs given different degrees of trading edge and at different odds.

Methodology

A ten runner race is set up with a set of book odds where the book sums to a 7% over-round. A rating is attached to each horse, and the true odds of each horse winning is defined to be a function of the book odds and its rating. The function works so that highly rated horses have lower true odds than the book odds and vice versa for lowly rated horses. One of the parameters in the function is the degree to which the ratings have an edge over the market. The greater the edge the more the book odds are adjusted. The approach is Bayesian in nature.  The ratings used are arbitrary – they express in numerical form the the likelihood of a particular horse winning – the results presented here are not specific to the use of rating systems. Implicit in any bet placed by a gambler in a probabilistic setting is a set of underlying decisions based upon preferences or rankings that can be thought of as a set of ratings, even if they aren’t expressed as such.

Monte Carlo methods are used to run the race 30,000 times (defined as one simulation, this is equivalent to betting on 15 races a week for 40 years) using the true odds, as defined earlier, to determine the probability of each horse winning. If the winner coincides with the horse that is also top rated, the gambler wins. The book odds associated with the top rated selection and the level of edge are kept constant per simulation run. The process is repeated so that simulations are run at 4 different book odds and 4 levels of edge, to give 16 simulations in total. The book odds chosen are evens, 3/1, 6/1 and 9/1 and the levels of edge chosen to correspond to differing levels of Return on Capital (RoC) of 10%, 5% , 0% (break-even) and -7%.  The latter case represents someone with no edge whose losses over time equal the book over-round.

Relationship Between Edge,  Book Odds and True Odds

Table 1 below gives the relationship between the odds at which you back and the true odds for given levels of edge. So backing at 6/1 with a 10% edge represents true odds of 5.3/1. At a 5% edge backing a 3/1 shot represents true odds of 2.8/1, and backing an even money shot with a 10% edge has true odds of 4/5. The difference between book and true odds is small and sets the context for the analysis that follows. Whilst not the subject of this blog post, tables such as this can be used to give trigger levels at which bets become interesting for a given level of perceived trading edge.

Book Odds with 7% over-round 10% edge 5% edge break-even no edge
evens 0.8 0.9 1.0 1.1
3/1 2.6 2.8 3.0 3.3
6/1 5.3 5.6 6.0 6.5
9/1 8.1 8.5 8.9 9.7

Table 1: Book odds and true odds for differing levels of edge

Relationship Between Edge, Book Odds and Losing Run Length

Table 2 below gives the maximum losing run that from each simulation. The longest losing run experienced from betting at constant odds of evens with a 10% edge was 14 races, at 9/1 with a 10% edge 80 races. The reason it is often a long wait between drinks for top rated selections is the size of the trading edge compared with the odds at which horses are backed. Since the number in Table 2 represent the extreme case of the simulation, the length of losing run that occurs 5% of the time  is reported in Table 3.  Note how the length of losing run changes little with edge. If you typically bet at 6/1 and think you have a 5% edge, and you are on your 17th losing wager, there are no obvious signs from Tables 2 and 3 that you are experiencing anything other than a losing run that occurs one time in twenty. If Pricewise has a 10% edge and gives 3 selections a week all at 9/1, these results suggest that at worst  he could go half a year without a selecting a winner. Note that in practice gamblers will be betting wherever value is perceived regardless of book odds, and the fixing of odds across all simulations is artificial. However it would be straightforward to weight the results to reflect the proportion of bets you typically placed at various odds.

In finance one criteria used to judge the quality of returns delivered by investment managers is the Sharpe Ratio. This penalises returns by the volatility of the return stream. Inspection of table 3 shows that the highest Sharpe Ratio would come from betting even money shots. To emphasise, there is no suggestion that betting even money represents greater value than betting at bigger odds. The simulations are set up so the Return on Capital achieved are the same, and the value inherent in the even money shot is the same as in the 6/1 shot. However the path to terminal wealth followed by betting at evens is inherently less volatile than betting at bigger odds.

Book Odds with 7% over-round 10% edge 5% edge break-even no edge
evens 14 14 16 19
3/1 24 27 27 27
6/1 59 59 60 65
9/1 80 80 80 80

Table 2: Book odds and maximum losing runs  for differing levels of edge

Book Odds with 7% over-round 10% edge 5% edge break-even no edge
evens 3.2 3.5 3.8 4.2
3/1 8.7 9.3 9.8 10.6
6/1 16.9 17.8 18.8 20.3
9/1 25.2 26.4 27.9 ;30.3

Table 3: Book odds and 95% probability losing runs

Relationship Between Edge, Book Odds and Time to Last Cumulative Loss

The results presented so far are unaffected by staking plans. In Table 4 below the number given represents the last race in the simulation at which cumulative profits are negative. This gives a sense of the number of races for the signal inherent in the edge to outweigh the noise. For level stakes betting at 6/1 with a 10% edge , profitability is always positive from the 2,324th race. Note the substantial step up in the wait for cumulative profitability when betting at 6/1 compared with 9/1 at the 5% edge level, and when betting at 3/1 compared with 6/1 at the 10% edge level.  The results highlight the increased path dependency inherent in betting at higher odds. The range of possible outcomes is such that it can take much longer to move into positive cumulative profitability.

Note that employing staking plans such as The Kelly Criterion would potentially improve this level staking result so that the month numbers were lower, particularly for the higher odds results presented, however since the cumulative profits/losses will have meandered around zero the effect on the broad thrust of the conclusion reached is likely to be small.

Book Odds with 7% over-round 10% edge 5% edge
evens              12            432
3/1            628         2,673
6/1         2,324         2,919
9/1         2,923         8,444

Table 4: Book odds and number of races and last breake-ven race

Conclusions

If you choose to bet on the horse that represents your top pick in a race, and you adopt this as a betting approach over many races, you are maximising the total profits you can expect to accrue over time. However this approach has costs associated with it. Whilst maximising expected total profits, you are also maximising both the volatility of your trading profits and exposure to path dependency.

Losing run length is primarily driven by the odds at which you back horses. It is difficult to identify that you have lost your edge in the middle of a losing run because losing run length is primarily driven by the odds at which you bet rather than the size of your betting edge. What may appear to be a loss of ability could merely be an unlucky run that is merely noise.  The reason it is often a long wait between drinks for top rated selections is the size of the trading edge compared with the odds at which horses are backed.

Betting at shorter prices minimises trading profit volatility, path dependency and reduces losing run length. Splitting your stake across more than one selection in a race will (subject to your edge being similar across all runners in a race) increase the probability that your edge will be reflected in your trading profits. These profits will not be as large as if you had made one winning selection, however what you make will be made far more often.  Betting on a number of horses in a race effectively creates one shorter priced aggregate bet. This has a number of attractive features – it reduces losing run length, reduces trading profit volatility and reduces exposure to path dependency. The cost of this approach is that over the long run total profits will be less than betting on one selection only. The trade-off between the two approaches is interesting. Given the associated drawbacks, it is surprising the one selection per race approach appears to be so little questioned and so popular.

Jamie Spencer – Riding Style & Results: What Does The Data Tell Us?

Introduction

The recent criticism by Luca Cumani of two of Jamie Spencer’s rides this year on Mount Athos by Luca Cumani ( “it’s on record that he was given two very bad rides” has caused a good deal of comment and publicity. Simon Holt devotes his column in the Racing Post Weekender this week (25th September edition) to a discussion of Jamie Spencer’s riding style, concluding that “this is a jockey with a bit of star quality and his career record provides impressive defence against the critics”.  As Simon Holt points out, the hold up style he adopts can lend itself to criticism if a horse is perceived as being delivered too late, such as his recent ride on York Glory in the 2013 renewal of the Beverley Bullet. However much of the criticism leveled appears to be founded on one or two rides, rather than by considering his performance over many rides.  In this blog post all of Jamie Spencer’s rides in the 2013 flat season (to 25th September) were examined in terms of riding style, Impact Values and ratings. The rides of a number of other jockeys (Ryan Moore, Richard Hughes, James Doyle and Joe Fanning) were also examined. With each of these jockeys having ridden over 400 rides each this season to date, there is plenty of data to interrogate.

Definition of Running Style/Early Pace Position

The analysis that underpins this piece was carried out in the R statistical environment accessing Raceform Interactive (RFI) data. This is the same data used by the Racing Post. In running comments were used to identify the Early Pace Position (EPP) adopted by each horse in each race contained within  the database. In this blog post the terms EPP and ‘running style’ are used interchangeably. Five categories of running style were defined: leading(1), prominent (2), midfield (3), held up (4) and in rear (5).   Armed with an EPP by horse by race, the most frequently adopted running style by each horse can be identified. These EPPs can be used in conjunction with the remainder of the information contained within the RFI database to examine the relationship between running style and jockey performance. Horses had to have run at least 3 times for an EPP to be assigned to the horse, so if for example, Orfevre ran three times, twice in the lead (style 1) and once prominently (style 2), he’d be assigned an EPP of 1. After this parsing exercise we have the running style adopted by each horse in each race that it took part, and the running style each horse has adopted most frequently in the past.

Jockey Rides, Horse Ability and Starting Prices

To help put Jamie Spencer’s riding style in context the following jockeys were chosen for comparison: Ryan Moore, Richard Hughes, James Doyle and Joe Fanning. The first two are vying for champion jockey in 2013, James Doyle has recently been appointed Prince Khalid Abdullah’s jockey, whilst  Joe Fanning is known for adopting front running tactics and should provide a contrast with the riding style adopted by Jamie Spencer. Table 1  gives information about the ability of horses ridden (using the median rating across all rides ) by each jockey and betting market expectations  using average and median Starting Prices (SPs). All rides in the 2013 flat season were considered. Ryan Moore rides horses with the most ability, posting a median RPR of 81, followed by Jamie Spencer , Richard Hughes, James Doyle  and then Joe Fanning. Note that the SPs for Ryan Moore and Richard Hughes’s rides are close, suggesting the betting markets typically rate their chances similarly. Jamie Spencer comes next in terms of market expectations, with James Doyle last after Joe Fanning, even though, on average, he rides more highly rated horses.

Jockey Median Rating of Rides Average SP Median SP
J Fanning 69 10.4 7.0
R Hughes 76 5.7 4.0
J Doyle 73 12.7 7.5
J Spencer 78 8.7 6.0
R Moore 81 5.5 4.0

Table 1: Median ratings of rides and SP information for selected jockeys

Early Pace Position Profiles

The proportion of horses in each EPP category is given in Table 2, along with wins per category and associated Impact Values (IVs). Impact Value has its usual definition. The IV for front runners is 1.88. As is widely known front runners win more frequently than other  running styles. IVs  for EPP styles 2 (prominent) and 3 (mid-division) are similar at 0.94 and 0.99 respectively, with hold up horses performing somewhat worse at 0.83 and horses that race in rear reporting the lowest IV of 0.60. The IVs reported here by riding style suggest that the most important decision a jockey can take is whether to front run or not. After that, racing prominently or in mid division has similar outcomes, whilst being held up or in rear suggests that the further back you race from a midfield position, the less likely it is that you will win races. There is an important caveat here – the EPP adopted it is not entirely in the jockeys hands, but conditioned on a number of factors, only some of which are in his control. However we do know that on average horses do appear to have a favoured EPP, and this is useful for some of the analysis that follows.

EPP wins runs proportion IV
1 963 4466 12% 1.88
2 408 3787 10% 0.94
3 1714 15097 39% 0.99
4 814 8550 22% 0.83
5 479 6329 17% 0.66
TOTAL 4378 38229 100% 1.00

Table 2: EPP running styles, proportions and Impact Values

Jockey Riding Styles

Perceptions are borne out by the data – Jamie Spencer rides far fewer horses in mid-division than other jockeys, preferring to hold them up or ride them in rear.  Table 3 takes every ride of each jockey and amalgamates by EPP. The differences in EPP adopted by Jamie Spencer are substantial compared with the other jockeys in the table. Note that he rides as least as many front runners and prominent horses as Ryan Moore and James Doyle, it is the mid-division category that he eschews, with more than half of his rides categorised as either held up or in rear.

Jockey EPP1 EPP2 EPP3 EPP4 EPP5
J Fanning 19% 13% 43% 16% 9%
R Hughes 17% 7% 35% 20% 21%
J Doyle 10% 6% 37% 29% 19%
J Spencer 13% 5% 25% 27% 31%
R Moore 10% 8% 40% 23% 20%

Table 3: Riding styles adopted by jockey

Does this result hold when checked against the most frequent riding style of the horses ridden by our jockeys?  Table 4 shows there is some evidence that Jamie Spencer tends to ride more horse that have a hold up running style. However, this could have been caused by the fact that he might be the only jockey to have sat on the horse and thus contributed to its running style. This makes  interpretation more difficult. On balance, however, comparing the riding proportions in tables 4 and 5  shows that Jamie Spencer does appear to ride his mounts with more restraint than is usually the case.

Jockey EPP1 EPP2 EPP3 EPP4 EPP5
J Fanning 11% 15% 33% 20% 21%
R Hughes 6% 13% 31% 29% 22%
J Doyle 4% 10% 29% 32% 25%
J Spencer 4% 8% 31% 30% 27%
R Moore 6% 10% 33% 30% 20%

Table 4: Riding styles by horse

Relationship between Running Style (EPP) and Ratings Achieved

A  measure that compares the rating of each run relative to the maximum rating the horse has achieved is defined as the Relative to Maximum – RTM.  Table 5 below shows average RTM by running style style. On average horses run ca. 18lb below their maximum rating. This is no surprise – ratings are negatively skewed – bounded on the upside by ability and the relatively rare confluence of a set of circumstances that allows a horse to achieve its maximum rating,  and exposed to substantial downside as any number of events (going, draw, pace, opposition, trip and so on)  cause horses to run below their best. Horses with a  prominent running style (EPP 2) are most likely to perform below their best. Remember from table 2 horses that race prominently deliver lower IVs than those that race in mid-division.  It is possible that the pressure of racing prominently conspires against these horses. The best RTM numbers reported are for horses that are held up or ridden in rear. Given the IVs for these categories are substantially lower than 1, a likely explanation for them running more closely to their maximum rating is that they are running on past beaten horses to be placed rather than winning. This has implications for their handicap ratings relative to their ability.  In tables 4 and 5 we have IVs and RTM values by running style classification for all races that took place on the flat in 2013. These tables give us a sense of how often horses win given the their riding style, and to what degree they run close to their maximum form.  Now we turn to the same information at the individual jockey level.

Early Pace Position (EPP) Rating To Maximum (RTM) – average
1 -18.4
2 -19.0
3 -17.9
4 -17.7
5 -17.0

Table 5: RTM by EPP style category 

Jockey Performance: Impact Values & RTM Ratings

Two approaches to measuring jockey ability are those used by John Whitley, often mentioned by James Willoughby on Racing UK, and Timeform. In this blog post two measures already employed, Impact Values  (IVs) and Run To Maximum (RTM) , are calculated at the jockey level. Impact Values by jockey by running style are reported in Table 6 below, RTMs by running style are reported in table 7.  Ryan Moore performs the best across both measures.  On average his rides perform about 8lb better than average (-8lb vs -18lb) and ca. 3lb better than the other jockeys considered here. Particularly noteworthy is his performance on front runners, where he performs nearly 10lb better than average, with an IV of 3.9.  Joe Fanning performs best when he rides front runners.  Richard Hughes, James Doyle and Jamie Spencer perform similarly to each other based upon RTMs – about 5lb better than average, but ca. 3lb behind Ryan Moore. If Starting Prices and horse ability are considered, James Doyle performs particularly well. Perhaps the betting market has underestimated his abilities – if so, his recent appointment by Prince Khalid Abdullah and the likely increase in the quality of his mounts  is likely to change this.

Turning to Jamie Spencer:  he performs best on front running rides, delivering similar IVs to Richard Hughes and yet performing 2.5lb better on average.  What of his hold up rides? Considering horse that are held up or ridden in rear (EPP 4 and 5) , Jamie Spencer’s rides perform second only to Ryan Moore in terms of RTM. Yet the IVs for both of these categories are the second lowest of the jockeys considered here. There are a couple of interpretations. The first is that hold up horses are running into places, achieving respectable ratings and yet not winning. The second is that the horses are being ridden in a style that maximises their chances of running close to their maximum ratings, and the IVs will, over many more rides, reflect this.

Jockey EPP1 EPP2 EPP3 EPP4 EPP5
J Fanning 2.52 1.41 1.13 0.39 0.93
R Hughes 2.76 2.25 2.04 1.65 1.75
J Doyle 1.35 1.14 0.97 1.69 1.79
J Spencer 2.73 2.24 1.69 1.21 1.05
R Moore 3.90 1.74 2.21 1.34 2.07

Table 6: Impact Values by jockey by EPP classification

Table 7 below shows RTM averages by jockey by EPP category. A discussion of IVs and RTM by jockey follows table 7.

Jockey EPP1 EPP2 EPP3 EPP4 EPP5
J Fanning -15.3 -20.4 -17.8 -16.4 -15.5
R Hughes -13.5 -11.8 -12.9 -13.0 -12.9
J Doyle -12.6 -15.1 -11.7 -13.1 -13.9
J Spencer -11.0 -14.7 -13.3 -11.6 -12.6
R Moore -8.5 -10.2 -9.8 -9.4 -10.0

Table 7: RTM by jockey by EPP classification

Summary

  • Ryan Moore is viewed by many as the best rider in the UK – the analysis in this blog post supports this view.
  • James Doyle rides as well as Richard Hughes and Jamie Spencer and  has done so on longer priced horses with less ability.
  • Jamie Spencer rides horses further back than their usual position in races, and in doing so enables them to run closer to their maximum rating. The data suggests riding further back is a matter of choice. Whilst riding horse further back typically compromises their chances of winning races to a degree, the Impact Values for Jamie Spencer’s hold up rides are significantly above the average and also greater than 1. However they are also below that reported by Richard Hughes, James Doyle and Ryan Moore. It is possible that over time and over many more rides, the fact that his mounts are running closer to maximum ratings will be reflected in higher Impact Values than delivered in the 2013 flat season.