Running to Form: Days Off, Consistency and Race Type

Introduction

Prior to the recent running of 2014’s Cleeve Hurdle, Timeform’s Micheal Williamson blogged on the relationship between days off and the chances of horses running to form, with the backdrop of Big Buck’s long-awaited return to action. By coincidence I was in the middle of some analysis on the same subject, partly in anticipation of the start of the Flat season. The focus of this blog piece is the relationship between days off, consistency, race type and runs to form (RTF) for Flat and National Hunt (NH) races.

Data, Method & Universe

The source of the data is Raceform Interactive (RFI) with the analysis carried out in the R statistical environment. Flat and NH races are considered separately. Races in GB and Ireland only since 2007 up to mid-January 2014 are considered. Each time a horse runs its Racing Post Rating (RPR) is compared with the maximum RPR the horse has achieved up to and including race date. The difference between the two numbers is defined as the RPR relative (RPRrel). The maximum value RPR can achieve is zero. Following Timeform’s definition, if a horse runs within 5lb of its maximum rating it is considered to have Run To Form (RTF). Horses are classified as having either high or low consistency according to the percentage of times a horse has RTF relative to a cut-off of 50%. The choice of 50% is arbitrary. No allowance is made for the number of times a horse runs, or its age in assigning a consistency classification, even though the older/more often a horse runs the more likely it is to run more than 5lb below its previous best. Races are classified as either handicaps, pattern races or other. For Flat races the analysis is restricted to  horses aged 4 and above. The reason for this is to reduce the influence on the analysis of the return to racing after a long break of unexposed,  previously immature horses. For similar reasons in NH races the analysis is restricted to horses aged 5 and above. Days off between races are classified into the following 6 buckets: up to 10 days, 10 to 29 days, 30 to 59 days (1m to 2m), 60 to 179 days (3m to 6m), 180 to 364 days (6m to 1y) and 365 to 730 days (1y to 2y).

Analysis & Results

Days Off & Performance on the Flat

Table 1 shows the average RPRrel for each days off bucket.  The number of runs per days off bucket is also given.  Horses run closest to form with a break of less than a month between races, there is then a gradual deterioration in performance as the time between runs lengthens until an improvement of ca. 0.5lb with a break of between 6 months and a year, it is possible this is the period when horses are returning after a voluntary winter rather than enforced mid-season break.  Horses with a break of more than a year perform ca. 3lb worse on return than average.

Days Off Category Runs Runs% RPRrel avg (lb)
1 < 10 days           38,561 17.8% -19.4
2 10 to 29 days         110,358 50.9% -19.3
3 1m to 2m           32,299 14.9% -19.8
4 3m to 6m           19,995 9.2% -20.8
5 6m to 1y           13,012 6.0% -20.3
6 1y to 2y             2,602 1.2% -22.8
TOTAL         216,827 100.0% -19.6

Table 1: Breakdown of  runs and RPRrel by days off category – Flat

Days Off, Performance & Consistency on the Flat

Graph 1 below shows the deterioration in performance by bucket of days off by consistency. The rate of deterioration is similar for both categories. High consistency horses typically run ca. 13 lbs better than low consistency horses.

G2PerfConsisFlat

Graph 1: Days Off, Performance & Consistency on the Flat

Days Off, Performance & Race Type on the Flat

Graph 2 shows the deterioration in performance according to race type. In handicaps the deterioration in performance for a lay-off of more than a year is marked. Pattern race performers are not as affected by breaks, although also perform less well after a break of more than a year. The ‘other’ category is a ragbag of maidens, claimers, sellers and conditions races with results that are perverse relative to handicaps and pattern races.

G2PerfRtypeMk3

Graph 2: Days Off, Performance & Race Type on the Flat

Days Off & Performance for National Hunt Races

Table 2 shows the average RPRrel for each days off bucket for NH races.  The number of runs per days off bucket is also given.  Horses run closest to form with a break of less than 10 days or with a break of between 1 and 2 months. Longer breaks are associated with a deterioration in performance, with no equivalent upwards blip to that seen in Flat racing associated with breaks of between 6 months and a year. The rigours of National Hunt racing suggests racing that requires a longer recovery period and where improvement for the first run of the season should be expected. Horses running after a break of more than a year perform slightly worse than 3lb relative to the average.

Days Off Category Runs Runs% RPRrel avg (lb)
1 < 10 days           19,818 7.6% -17.6
2 10 to 29 days         117,268 45.2% -18.1
3 1m to 2m           57,475 22.2% -17.7
4 3m to 6m           33,380 12.9% -19.0
5 6m to 1y           23,425 9.0% -19.4
6 1y to 2y             7,826 3.0% -21.6
TOTAL         259,192 100.0% -18.3

Table 2: Breakdown of runs and RPRrel  by days off category – NH

Days Off & Consistency for National Hunt Races

Graph 3 below shows the deterioration in performance by bucket of days off by consistency. The rate of deterioration is similar for both categories. High consistency horses typically run 15 lbs better than low consistency horses. National Hunt and Flat exhibit similar patterns.

G3PerfConsisNH

Graph 3: Days Off, Performance & Consistency for National Hunt

Days Off, Performance & Race Type for National Hunt Races

Graph 4 shows the deterioration in performance according to race type. Handicaps show deterioration in performance as the length of lay-off increases, with a marked drop for lay-offs of more than a year. In pattern races there appears to be a sweet spot of between 10 days and six months where horses have produced their best performances. Perhaps the recent trend for top class horses to be campaigned sparingly is justified. Lay-offs of longer than six months are more negative. In NH races the ‘Other’ category is less of a rag bag, containing maiden and novice races. The results here probably reflect progressive horses posting new ratings highs and are therefore of less use in determining what relationship exists between days off and performance.

G4PerfRTypeNH

Graph 4: Days Off, Performance & Race Type for National Hunt

Summary

There is strong relationship between days between runs and running to form. There are substantial differences in the results from handicaps versus pattern races, and whether a horse has exhibited consistency in the past, and all of these factors need taking into account in deciding upon the prospects for a horse in the context of how many days since it has last raced. There are some differences in the results between the Flat and National Hunt, and these differences are consistent with NH types needing a somewhat longer recovery period and benefiting from their first run of the season. In common with Timeform’s findings there is little evidence of the received wisdom that modern training methods mean long layoffs are less of an issue is true, even when the data is split into pre- and post-2010 time periods. It is probably the case that the successful return to action of a few high profile, high consistency pattern race performers, who on the evidence presented above are likely to run reasonably close to their previous best, has caused this view to gain common currency.

Owners Facilities Reviewed: York, Wincanton, Goodwood, Sedgefield, Huntingdon

York (Baytown Kestrel, Flying Bear)

York gives the impression that it has thought hard about how to make owners and spectators happy. I usually travel to York races on the train but this year took the car to the busy August festival. The owners car park is organised for quick entry and get away. Kim Bailey writes about how he’d like to see this introduced for owners car parks at UK racecourses. I can see why as it works very well. The owners building at York is brilliantly positioned, with a balcony that on one side overlooks the paddock and on the other the finishing line. You couldn’t wish for better viewing. The dining room is excellent – food is close to Ascot standards, albeit you have to pay. Canny Yorkshire folk. But I don’t mind at all – it’s good value. The owners bar was very busy. By mid afternoon sitting/standing outside was a more comfortable option, but with it being York’s August festival it’s understandable. York possesses a charm few courses in the country can match and it is a pleasure to own/part-own a horse running at the course.

Rating:     😀                                 😀                           😀                    😀                 😀

Wincanton (Douchkirk, Heath Hunter)

Wincanton states in the letter you receive when your horse is entered for a race at the course that “our owners facilities are some of the best in Jumps racing”. Hmmmmmm – they need to get out more. With a few minor changes they could be, but they aren’t there yet. There are usually queues for owners badges on arrival, the owners facility is very crowded with nowhere to sit and there are long queues for food. The ‘hot local pie’ on offer was, sadly, passed over due to the queues in favour of wanting to see some racing.  Views of the finish are good from the owners bar, but then you have to face the scrum inside to get a drink or go to the paddock. It’s interesting that Wincanton has an arrangement that ROA membership gives you access to the owners facility. I’m not an ROA member. I know Rachel Hood, ROA Chief Executive would find this ‘extraordinary’, consider it because ‘I’m not sufficiently immersed in racing‘  or wish to ‘free ride‘ on the efforts the ROA makes on behalf of owners. She wrote as much in the July 2012 edition of Owner Breeder magazine. Maybe that article was a parody and I’m not in on the joke. What I do know is that if racecourses such as Wincanton, with capacity constrained owners facilities, have arrangements with the ROA so that its members can use those facilities even if they don’t have a horse running, and that usage detracting from the experience of owners with runners on the day, those racecourses and the ROA are doing a disservice to those owners that do have runners and, in the long run, to all owners. In Wincanton’s defence the Clerk of the Course has stated its badge arrangements with the ROA are being reviewed and they are also looking at how to alleviate the overcrowding and queues. A few minor changes here and there and Wincanton could be miles better.

Rating:             😀                    😀

Sedgefield (Innsbruck, Heath Hunter)

Sedgefield looks after owners. Decent food in the owners bar, plenty of places to sit and a jolly atmosphere. The course itself is the epitome of weekday National Hunt racing. Viewing is ok, but none of the stands have the height to make it exceptional for anyone. If you’re lucky enough to have a winner you are looked after very well with a photograph of your winning horse in a frame presented to you within short order of the race having finished. A nice touch.

Rating:         😀                           😀                    😀                 😀

Huntingdon (Dr. Darcey)           

You’d think on a rare sunny day in February that three people sitting on a deserted set of steps each drinking a cup of tea wouldn’t raise an eyebrow. When those steps are outside the owners enclosure opposite the winning post at Huntingdon racecourse it’s an occasion for the security guards to move in. Apparently the health and safety risks were too great for us to continue with our reckless tea drinking. No matter the tea was in a pathetic little paper cup with a sad teabag bobbing up and down within it – the spillage risk was too great for Mr & Mrs HiViz to bear. You’d think a featureless racecourse next to a motorway  that doesn’t have a fixture list to set the world alight might want to differentiate itself as a course based upon, say, friendliness, or facilities, or, I don’t know a decent hot meal, or tea served in china cups, or something, anything (!) that suggests a bit of effort. No chance. Huntingdon fails and fails badly. I can only imagine that Huntingon and Newbury raceourses are twinned. Huntingdon is a course to avoid as an owner.

Rating:  none

Goodwood (Silken Thoughts, Platinum Proof, Palazzo Bianco, Flying Bear)

Goodwood has plenty going for it as a racecourse. A wonderful setting and home to the fantastic Glorious Goodwood festival. The amount of racing gives many owners a shot at having a runner there.  Plus the course hasn’t messed things up as it has expanded – certainly not for owners. The views from owners seats at Goodwood is the best of any racecourse in the country. The owners pavilion is stylish with an excellent choice of food, and whilst it gets busy service is good. Food and drink isn’t cheap, but it hardly seems to matter. If you grab a table paddock side on a sunny day, where else would you rather be?

Rating:     😀                                 😀                           😀                    😀                 😀

Owners Facilities Reviewed : Ascot, Bath, Cheltenham, Newbury and Wolverhampton

Ascot (Flying Bear, Palazzo Bianco)

The best owners experience in the country. Whilst there are some aspects of the new stand that don’t quite work as well as they could – too much space between the paddock side and track side in the interior of the stand, sight lines in some places that aren’t perfect, the interior too hot in the Summer, too cold in the Winter, these are minor quibbles. Ascot probably receives some criticism because it is the flagship track in the country with the highest standards expected.  By contrast Cheltenham, given its facilities, gets away with little criticism. The Ascot owners facility overlooks the pre-parade ring, an inspired placement on the part of the architects team that were responsible for the re-design of Ascot.  The owners facility is in two parts – a bar and a dining room. The food in the dining room is a wedding style buffet. Top quality – and free to boot. The wine list has some gems, too. The bar next door is very comfortable and has large picture windows that open to allow you a view of the pre-parade ring.In the stands owners viewing isn’t quite opposite the finishing post but is close enough. Organising badges, and for Royal Ascot, paddock passes, all very easy. The staff were friendly, efficient and welcoming.  Going racing as an owner at Ascot is a pleasure. I’ve also had the good fortune to be part-owner of a horse that won at Ascot. There were plenty of families with young children in our party, and winning connections were made to feel entirely at home, even in spite of the impromptu creche that had been created. Hats off to Ascot.

Rating out of 5:       😀         😀           😀           😀             😀

Bath (Dr. Darcey, Orla’s Rainbow, Baytown Kestrel)

ARC, owners of Bath, have started to make more of an effort with owners, and things have improved noticeably in 2013 versus previous years. It’s still tough to get a seat in the owners area, but the food choice is much improved with a separate, albeit somewhat soulless, dining room at the back with a decent choice. The paddock area is close by, and whilst I don’t recall an area for owners viewing it’s never a problem to find  a spot in the stand with both a decent view of the course and close to the finishing line.

Rating out of 5:        😀         😀

Cheltenham (Alcalde)

I hope the redevelopment of Cheltenham results in an improvement in it’s owners facilities. Whilst the food on offer in the temporary marquee was decent enough, the large round tables mean you feel as if you are at a large wedding where you don’t know many guests. The owners bar is placed down near the 1f pole and is reminiscent of a 1950’s pub gone to seed. Owners viewing isn’t great either, further from the finish line than ideal – I’d choose to stand nearer the finish where the viewing is better.  For many people the pleasure of having a runner at Cheltenham outweighs the owners experience. I remember going to watch England play at Wembley in the 1970s. I didn’t notice the facilities were rubbish because of the wonder of  being at the match. I wouldn’t put Cheltenham in the rubbish category, but as the home of jumps racing its owners facilities should match those on offer at Ascot.

Rating out of 5:        😀         😀

Newbury (Alcalde, Silken Thoughts)

Oh dear. An excellent racecourse with clueless management and inefficient, officious staff. I’m of the view that the quality and behaviour of a management team in a business is reflected in the attitudes of its staff towards customers, and in the case of Newbury I hope the current search for a new Chief Executive results in an appointment from outside the current management team. Whoever is appointed can then, hopefully as a priority, sort out the treatment of owners and customers. There is also an atmosphere at Newbury that contrasts with that existing at the majority of other racecourses in the UK. It may have something to do with the cavernous Oktoberfest-style drinking halls, both permanent and temporary,  that exist. A re-design of these may improve matters here. My last visit as an owner to Newbury suffered from the following: queues for owners badges, no record of e-mail requests for badges at the owners desk, with questioning from the staff that suggested it was my fault they hadn’t read the e-mail, paddock stewards intent on preventing my teenage sons from entering the paddock with me, officious stewards at the owners facility, an uncomfortably crowded owners facility with no space to sit down, queues for drinks at the owners bar, and a long wait for food orders – we gave up and went to the on course fish and chip shop, where the food is decent and the service exemplary – in contrast to that experienced almost everywhere elsewhere on course. To put the tin hat on it our car was broken into in the owners car park. More security staff in the car park rather than acting as the fashion police might help here.  Newbury is a racecourse that benefits from an excellent fixture list and proximity to Lambourn. Good horses end up running at the course almost by default. The racecourse ought to be able to turn these benefits to its advantage. Yet it is a business which has lost money 4 years in the last 5 with no growth in turnover and attendance figures described as disappointing by the Chairman in reporting on its interim results last month.  Whilst these might be problems generic to racing, it is also a course that unlike others has had problems with mass brawls, fines for under-age drinking, the placement of concert stages for music nights so that viewing of the home straight is obscured, and horses being electrocuted in the paddock. The latest dress code furore can be added to the list of pratfalls that appear to be the speciality of  Newbury’s management team, which doesn’t appear to have made a connection between disappointing attendance figures, imposing a dress code and poor customer service. At the moment a course to avoid as an owner.

Rating out of 5: none

Wolverhampton (Magic Ice, Platinum Proof)

Wolverhampton offers decent facilities for owners. There is a good sized owners bar/room, decent hearty food on offer with viewing of the paddock from one end of the room and viewing of the track from the other. So why don’t I look forward to having runners at the track? It’s probably because the whole is so much less than the sum of the parts. There isn’t much of an atmosphere and the racing doesn’t inspire. But that is more my problem than that of the track – but in terms of being looked after, Wolverhampton does a decent job for owners.

Rating out of 5:    😀           😀             😀

High Class Novice Chase Candidates: Numbers, Yard Concentration 2008-13

In the last week Nicky Henderson complained about the programme for Novice Chasers, his comments culminating with the line “And that’s why there will be no chasers in three or four years time” .  A forthright summary of his comments can be found on Dan Kelly’s excellent blog here , which firstly covers the ongoing concerns about the Betfair Chase distance, then moves on to the Novice Chase programme in the context of Nicky Henderson’s comments. So leaving the programme book aside, how does the pipeline of high class horses going Novice Chasing look year by year? Using Racing Post Ratings (RPR) the number of horses rated above 145, 150, 155 and 160 is given in Table 1 below for each of the years 2008-2013 inclusive. To qualify horses must be with GB based trainers, never have run in a Chase, achieved the rating at a GB track and have run within twelve months of the end of April of each of the years considered. These filters are designed to capture high class Hurdlers that are candidates for Novice Chasing. The filters will include Hurdlers that won’t go Chasing, and excludes recruits to Novice Chasing from overseas, so the list isn’t complete. Still, these effects should be the same year on year and not affect a year on year comparison. Table 1 shows the pool of candidate horses has varied between 46 and 70 in the last six years, with no clear trend. The numbers for 2013 suggest a healthy pool of candidate horses for Novice Chasing relative to the recent past.

Year RPR 145+ RPR 150+ RPR 155+ RPR 160+
2008 46 29 15 9
2009 70 41 23 10
2010 59 34 18 11
2011 63 38 21 13
2012 55 35 18 13
2013 64 40 22 13

Table 1: High Class Novice Chase Candidates 2008-13

Using horses rated 145+, how has the concentration of horses by training yard changed over the last six years?  Table 2 shows the number of training yards that have 1 only, 2 to 5 and at least 5 high class Novice Chase candidates. So in 2008 17 yards had one candidate. In 2013 there were 19 such yards. No real pattern exists year by year. However it is in the yards with at least one candidate that the picture has changed. In 2009 there were 11 yards with 2 to 5 candidates. By 2013 this had dropped to just four yards. The view that high class Novice Chase candidates have become increasingly concentrated at the largest training yards is borne out by the data. Table 3 shows the same information but represented by total number of horses. The number of candidates in 2013 at smaller yards is the lowest it has been in the last six years and the number in the larger yards the highest. Increasing yard concentration exists.

Year 1 horse only rated 145+ 2 to 5 horses rated 145+ 5 plus horses rated 145+
2008 17 7 1
2009 13 11 3
2010 17 8 2
2011 19 6 3
2012 11 8 3
2013 19 4 4

Table 2: Number of yards with Novice Chase candidates rated 145+

Year up to 5 horses 5+ horses Total horses rated 145+
2008 39 7 46
2009 39 31 70
2010 41 18 59
2011 37 26 63
2012 31 24 55
2013 29 35 64

Table 3: Novice Chase Candidates Yard Concentration

The falling field sizes in Novice Chases cannot be blamed upon the number of horses that could go Novice Chasing. Candidate numbers are healthy. So either the programme book or yard concentration is to blame. The changes made to the Novice Chase programme in the last year or two should have led to an increase in field sizes. The only explanation for their falling in the 2013-14 so far is the refusal of the larger yards to race their best horses against each other. The campaigning of horses is largely a matter for the trainers and their owners. However, if the BHA react to the concentration of the best horses in a few yards by making changes to the programme book to reflect campaigning realities, it is difficult to imagine this leading to a dearth of Novice Chasers in a few years time. Some trainers would argue that Novice Chasing is different from Novice Hurdling and their concern is primarily one of horse welfare.  The first implication is that anyone arguing the opposite position does not have horse welfare at heart. Not a position anyone wishes to inhabit lightly. The further implication is that a series of uncompetitive races should exist so that high class horses can learn the ropes. This will then benefit their long-term career, which, in turn, benefits racing. Perhaps to address both small field sizes and welfare concerns a series of zero prize money Australian style ‘Barrier Trial’  Novice Chases at racecourses could be introduced, with the full cost of hosting these races borne entirely by the owners. No handicap marks would be awarded and no betting available. These trials would allow for legitimate schooling in public in near race conditions. Lowly handicapped horses could take part knowing their handicap marks will be unaffected, better horses could make their own way home, learning the ropes as desired by trainers.  The quid pro quo would be that the Novice Chase programme would be further reduced. Welfare concerns are addressed by the existence of Barrier Trails, whilst field sizes in Novice Chases would increase because of the reduced number of races, improving the viewing spectacle for the racing public.

Trainer Form: Signal or Noise?

Introduction

On day two of the November 2013 Cheltenham meeting David Pipe drew a blank from his seven runners. For many people this result pointed to the Pipe stable being out of form. But whatever might have been ailing the yard on Saturday had disappeared by Sunday morning, with four winners, including The Greatwood, one of the most competitive handicap hurdles in the calendar. No doubt on Sunday evening the Pipe yard was marked out as one to follow. So what of trainer form, is it possible to identify yards that are in or out of form? In the woefully misnamed ‘Statistics’ section of the Racing Post the ‘Hot Trainers’ table uses Strike Rate (winners to runners) over the last 14 days , whilst  the ‘In Form’ table in the ‘Trainerspot GB’ table uses Run To Form, again over the last fortnight. Neither table is useful.  Both are based upon too few runners to be able to draw any meaningful conclusions. These tables are an excellent example of attempting to draw inference from a small information set – whilst this instinct helped us survive when faced with perceived mortal dangers in the past, the very same instincts are likely to mislead in the more prosaic setting of horse racing. Whilst the data in the  ‘In Form’ table isn’t useful, this is only because there are too few observations to be able to draw any firm conclusions. However, the idea of considering trainer form as an average or median of how close to form the horses under the trainers care are running makes intuitive sense.

The analysis that underpins this piece was carried out in the R statistical environment accessing Raceform Interactive data focussing on the 2010-11 and 2011-12 National Hunt seasons. Thanks to Simon Rowlands and James Willoughby for their input.

Trainer Form Variable Definitions

The starting point for the analysis that follows is to define and calculate a Run To Form (RTF) variable. RTF is defined as follows:  the Racing Post Rating (RPR) achieved by each horse in a race subtracted from the maximum RPR achieved by each horse in its runs up to and including the race in question. A horse has to have run more than three times to qualify for consideration. This filter is used to reduce the influence of lightly raced progressive horses. The maximum value RTF can take is zero.

Trainer Form Absolute (TFA)

The next step is to define and calculate a measure of trainer form. Trainer Form Absolute (TFA) is the median RTF for all the runners of a trainer over a particular time period.  Using the 2010-11 National Hunt season Graph 1 shows a histogram of TFA for those trainers that had at least 50 runners over the season. 132 trainers qualified. Note the negative skew. This is a common characteristic of form data in horse racing.  It is difficult to run close to form wheras there are many and varied reasons for horses running below form. The negative skew in RTF at the horse level aggregates to negative skew in TFA at the trainer level. Graph 2 shows the same information as a Box Plot.

TFormHisto

Graph 1: Distribution of trainer TFA NH season 2010-11

TFormBoxPlot

Graph 2: Box Plot of trainer TFA NH season 2010-11

So does a ranking of TFA indicate in form trainers at the top and out of form trainers at the bottom? Inspection of Graphs 1 and 2 highlights the problem with using TFA as a measure of trainer form. The range of TFA across trainers is so wide that the top and bottom of the TFA list won’t change often enough to be able to identify trainers in and out of form – for example if Nicky Henderson normally runs at a -5lb TFA and is currently running at -8lb TFA he would still be near the top of the TFA list, wheras he is running 3lb below his normal TFA rate. It is also of note that the variability of TFA per trainer is correlated with their TFA. Either the better horses, who are at the better yards, run more consistently, or the better trainers are able to get their horses, who are better than those elsewhere, to run more consistently. Or a combination of the two. In this context better means those yards with the highest TFA values.

Trainer Form  Relative (TFR)

Given the concerns about using TFA a measure of relative run to form can be defined and calculated that takes into account the usual RTF per trainer. Trainer Form Relative (TFR) is defined as the difference between TFA in a particular time period and TFA in a previous time period. TFR enables a direct comparison between trainers with widely different absolute levels of form (TFAs). Now Nicky Henderson’s -3lb TFR can be compared with a trainer whose TFA is normally -12lb and is currently running at -9lb, to give a +3lb TFR.

For the analysis that follows TFR is calculated for each of the seven months October 2011 through to April 2012. TFRs are calculated by taking the TFA in each month by trainer and subtracting the TFA posted by trainer for the previous season 2010-11.  So, starting with October 2011, how is its TFR related to the TFRs posted one month later? Graph 3 below shows a significant relationship. At first sight this appears to be clear evidence that trainer form in October 2011 helps predict trainer form in November 2011.

TFormt_t+1

Graph 3: Relationship between TFR October to November 2011  

What happens if we compare TFR in October 2011 with months further out? If form is temporary the relationship should decline through time. If October form predicts November form, it shouldn’t predict December form to the same degree. In the jargon we can postulate an  autoregressive AR(1) process. What we see in the data is the relationship shown in Graph 3 is as strong between October and November as it is between October and other months. See Table 1 below for correlation coefficients between t and t+1, t+2, t+3 using November 2011 as month t.

Correlation of November 2011 TFR with

December 2011             0.44

January 2012                0.51

February 2012              0.43

March 2012                    0.47

April 2012                       0.37

Table 1: Correlation of TFR months t with t+1, t+2, t+3 etc

We shouldn’t observe the same level of correlation across the months. It suggests form has a permanent component to it – an oxymoron. So how to explain this result? Imagine we can fast forward one year. We calculate TFA per trainer based upon the season 2011-12. This enables us to compare the results of a trainer in 2010-11 with the next season 2011-12. If we classify TFR as ABOVE or BELOW zero, and then further classify according to whether a trainer had a BETTER or WORSE season in 2011-12 relative to 2010-11, we see how RTF looks month by month in Table 2 below.

BETTER 2011-12 form                                  WORSE 2011-12 form

                              ABOVE       BELOW                                                            ABOVE       BELOW

ABOVE                     76               42                                                                         8                  28

BELOW                     33               16                                                                       29                109

Table 2: classification of form by month by year

Remember we have peaked into the future in calculating Table 2. It isn’t available until the end of the second season. The number of observations in the ABOVE-ABOVE and BELOW-BELOW categories are too high for the TFR measure to be useful as an indicator of form. In other words when a trainer is ABOVE or BELOW form in a particular month it is likely that they will continue in that category for the next month and the next month after that and for the duration of the season. The problem here is that the comparison used in the TFR calculation, namely the form of the trainer from the previous season, is likely to suffer from bias.  For some trainers it will be higher or lower than the true level of form a trainer can expect, and for those that posted towards the extremes of TFA they are likely to revert back to some degree in the next season. Bias such as this is difficult to remove and as a result relative measures of trainer form such as TFR are as flawed in their own way as absolute measures of trainer from such as TFA.

Summary

I started this analysis with the prior view that trainer form probably exists.  My view now is that it if it does exist it is very difficult to measure.  Absolute measures of trainer form do not exhibit enough variability, wheras relative measures have problems in deciding on an appropriate comparison. For some the measures of trainer form defined above might be too simplistic, arguing that more complex definitions are required. This is entirely possible. But as complexity of definition increases, particularly if it is one of many derivations tried, so does the risk that the measure will work only for the sample of data on which it was tried. If you torture the data for long enough it will tell you anything.

There is another possible use of trainer form – but more in how it is perceived by the market. Consider Graph 4 below. It shows TFA on the x-axis and Strike Rate on the y-axis by trainer for the 2010-11 season. It is the same data expressed in different ways.

TFormTFA_SR

Graph 4: Strike Rate vs trainer form

Strike Rate is a popular measure of form, RTF (and its variants TFA and TFR) less so. Yet Strike Rate is noisier and contains less information than RTF. Given the popularity of trainer form as an idea, and the popularity of Strike Rate as a proxy for trainer form, it is possible that the runners of trainers with a high/low Strike Rate relative to their TFA could have odds that are too far away from their correct values as the market considers these trainers, based upon a faulty premise, to be in or out of form. Armed with the appropriate data this is a testable proposition.

Winning Distances: Trip, Going, Field Size, Race Class & Handicapping

Introduction

The distance that horses finish relative to each other in horse racing is an important consideration in deciding what rating to apply to each horse post-race by public and private handicappers. Whilst it is obvious that trip will affect winning distances, what of going, field size and race class? To what extent do these factors make a contribution, and does the official handicapper take these factors into account in handicapping horses post-race?

Method, Dataset & Definitions

The analysis that underpins this piece was carried out in the R statistical environment accessing Raceform Interactive (RI) data for turf handicap races that took place during the 2011, 2012 and 2013 flat seasons in Great Britain. Races were placed into categories as follows:

Trip – Sprint (up to 6.5f), Mile (6.5-9.5f), Mid-distance (9.5-12.5f) and Long-distance (12.5f+)

Going – Heavy (HY), Soft (S), Good-Soft (GS), Good (G), Good-Firm (GF) and Firm (F)

Field Size – Tiny (fewer than 4 runners), Small (5 to 12 runners) and Large (more than 12 runners)

Race Class – High (Classes 1, 2 and 3) and Low (Classes 4, 5 and 6)

The number of races that took place in each category is given in Table 1 below.

Trip 2011 2012 2013
LONG 494 483 510
MID 450 421 448
MILE 1145 1103 1170
SPRINT 350 339 348

Table 1: Number of races by year by trip

Ground classifications used were those applied by RI rather than the official going. Proportions of races by Going category are given in Table 2a below. The effect of the wet weather in 2012 and dry summer in 2013 can be seen in the proportion of races that took place on the Soft and on Good-Firm in each year.

Going 2011 2012 2013
F 0.0% 0.6% 0.6%
GF 14.4% 14.6% 22.3%
G 65.5% 41.1% 57.4%
GS 14.8% 21.7% 12.6%
S 4.7% 17.1% 5.9%
HY 0.5% 4.9% 1.2%

Table 2a: Proportion of races by year by going category

The number of races by year by Field Size is given in Table 2b below. Field Sizes fell in 2013. The argument that fast going was responsible for the drop in Field Sizes is spurious. In 2011 there were 287 races on GF with small Field Sizes. In 2012 this decreased slightly to 262 races. In 2013 there was a substantial increase to 475 races. Other factors are responsible for the drop experienced in 2013.

Field Sizes 2011 2012 2013
LARGE 576 574 491
SMALL 1863 1772 1985
TINY 52 32 120

Table 2b: Number of races by year by field size

In Table 2c below the relationship between Race Class and Field Size is shown. As expected there is a greater proportion of High Class races with Large Field Sizes. In the analysis that follows races categorised as TINY were excluded from the analysis.

Race Class LARGE SMALL TINY
HIGH 558 963 29
LOW 1083 4656 175

Table 2c: Number of races by class and field size

 

Winning Distances and Going

Graph 1 below shows winning distances by Trip for each Going category. Winning distance is defined as the distance between the winner of a race and the horse coming third.  There aren’t many races that take place on Firm Going and as a result its black line representation on the graph should be treated with caution. Notice how winning distances are similar for the GS, G and GF categories, wheras for Soft and Heavy Going winning distances are quite different. There is also a non-linear relationship between winning distance and Going as Trip increases in distance. The minimum number of categories of Going that best describes winning distances is three:  Heavy, Soft and an amalgamation of the other Going categories. We know from Table 2a that few races take place on Heavy going. As a consequence excluding these races, rather than amalgamating with the Soft going category, will improve the balance of the analysis that follows.

plot1

Graph 1: Winning distance by going category

Winning Distance and Race Class

On average winning distances are higher in Low Class races. Graph 2 below shows median winning distance by Trip by Race Class. The relationship is linear with trip for Low Class races. For High Class longer distance races the median winning distance is lower than for mid distance races. This is counter intuitive. It could be explained by High Class long distance races being run at a different pace – more of a crawl and sprint, resulting in compressed winning distances, rather than an end to end gallop.

DistClass

Graph 2: Winning distance and Race Class

Winning Distance and Field Size

Winning distances are higher in Small Field Size races. Graph 3 below shows the median winning distance for Small and Large Field Sizes. It is possible the Field Size and Race Class winning distance effects are related due to the high relative proportion of High Class races with Large Field Sizes.

DistFSize

Graph 3: Winning Distance and Field Size

Contributions to Winning Distances

The information presented above shows that winning distances are affected by Trip, Going, Field Size and Race Class. Since some of these categories are related to each other analysis of variance (ANOVA) is used to attempt to disentangle the effects and see if all or just a subset of categories are important. In addition we can identify interaction (non-linear) effects, such as that between winning distance and Going. In Table 3 below a summary of the ANOVA table is presented. Apart from the obvious result that Trip and Going are highly significant in terms of explaining winning distances, Field Size and Race Class are important in their own right. In addition two interaction variables are included – Trip with Going and Trip with Race Class. The former is intuitive, the latter less so.

Category                    F Value                   p-value

Trip                              187.626                  2e-16

Going                             91.278                   2e-16

Field Size                      85.227                  2e-16

Race Class                    64.553                   1e-15

Trip*Going                    8.237                   2e-05

Trip*Class                      6.904                  0.000122

Table 3: ANOVA table of contributions to Winning Distance

Winning distances and Subsequent Handicap Changes

The official handicapper has detailed his policy with respect to handicapping here.  Given the wide range of inputs that he states go into his handicapping decisions, we should find a relationship between changes in handicap mark and the race categories examined in the previous section. A variable that takes into account handicap mark changes and winning distances is defined as follows:

lbPerL = (Mark change for winner – Mark change for 3rd)/(Winning distance 1st-3rd)

Graph 4 below shows winning distance on the x-axis and handicap changes winner to third on the y-axis. Whilst there is a relationship (correlation=0.6) there are other factors in addition to winning distances that are used to revise handicap ratings.

DistORchg

Graph 4: Winning distance and handicap changes

Pounds Per Length and Going

Handicap changes per length are lower for races that take place in Soft going. The median difference is 0.25 lbperL. So for with winning distances of 2 lengths, median handicap changes in Soft going are ca. 0.5lb less than on quicker Going.

ORchgGoing

Graph 5: Pounds per Length and Going

Pounds Per Length and Race Class

Handicap changes per length are higher for High Class races. The difference is 0.34 lbperL. With winning distances lower in High Class races, it appears as if the handicapper applies a standard handicap increase to the rating of winners regardless of Race Class.

ORchgClass

Graph 6: Pounds per Length and Race Class

Pounds Per Length and Field Size

Handicap changes per length are higher for races with larger Field Sizes. The difference is 0.33 lbperL. As with Race Class, it appears as if the handicapper applies a standard handicap increase to the rating of winners regardless of Field Size.

ORchgFS

Graph 7: Pounds per Length and Field Size

Understanding the Contributors to Handicap Changes

ANOVA is used to check if the differences seen in the graphs above are statistically significant. Table 4 below shows the handicapper does take into account Going, Field Size and Race Class in the handicap changes he applies to winning horses – the p-values show that each category explains a significant component of the lbperL variable. In the next section we examine if sufficient account is taken of the different race categories.

Category              F Value                 p-value

Trip                          106.119                < 2e-16

Going                         27.191               1.90e-07

Race Class               45.673               1.52e-11

Field Size                  42.151               9.10e-11

Table 4: Contributors to Winning Distances

Is Sufficient Account Taken of Different Race Categories?

If the handicapper takes sufficient account of race categories it should be the case that horses run equally well in their next race. The variable PctBtn (thanks to Simon Rowlands of Timeform for suggesting this variable, for example here) is defined as the percentage of horses beaten next time out by the winner of each race. If the handicapper has done his job, there should be no difference in the average PctBtn variable by race category. ANOVA is used again. Table 5 contains the results. The results for Field Size are statistically significant. It appears as if the handicapper does not raise the handicap mark of winners of large Field Size races by enough, since they beat a higher proportion of their rivals next time out than winners of races in other categories.

Category                   F Value                   p-value

Trip                             0.442                       0.7230

Race Class                0.098                       0.7545

Field Size                  4.821                        0.0282

Going                        0.668                        0.4137

Table 5: Contributors to Winning Distances

Summary

In addition to the obvious effect of Trip and Going on winning distances, Field Sizes and Race Class are also significant contributors. Whilst the handicapper appears to take these factors into account in setting handicap marks, in the case of large fields size handicap winners it appears that winners are insufficiently penalised. It is a small step to suggest that placed horses from large Field Size races are worthy of particular attention next time out.

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