Run Style Bias in Non-Handicap Chases

In this fourth and final part of my investigations into run style bias in National Hunt racing, I'll look at the effect of pace, or run style, in non-handicap chases, writes Dave Renham.

The previous three parts can be found below:

- Run Style Bias in Handicap Hurdles
- Run Style Bias in Non-Handicap Hurdles
- Run Style Bias in Handicap Chases

Run style is all about the position a horse takes up early in a race. Here at geegeez there is a pace section which splits the early positions of horses into four groups. The groups are called Led, Prominent, Mid Division and Held Up. Each group is also assigned a numerical value starting at 4 for led, and then 3 for prominent, 2 for mid division and 1 for held up. Essentially, ‘led’ means horses that led the race early, also known as front runners; ‘prominent’ equates to horses which race close up behind the leaders; ‘mid division’ refers to those racing in the middle portion of the field; while ‘held up’ covers the cohort close to or right at the back of the pack.

For this piece I will look at races with seven or more runners – for the other articles I used eight as my cut off, but non-handicap chases too often have smaller field sizes so I wanted to increase the overall data set. Indeed, despite including seven-runner races, in recent seasons the average number of qualifying races per year has been less than 100. That's quite a difference from the 2009 season when there were 226 qualifying races. Note also that hunter chases have been included in this dataset.

Overall Run Style Bias in Non-Handicap Chases

The first set of figures I wish to share with you are the overall run style stats for all National Hunt non-handicap chases in the UK from 1/1/09 to 31/7/21. These have been sourced from the excellent Geegeez Query Tool:

 

There is a definite advantage to early leaders / front runners here, with prominent racers notably second best. Horses that race mid division or are held up have remarkably similar records, both poor in relation to those campaigned more forwardly.

The strike rates for each run style section have stayed extremely consistent over the last 12 years or so, as the following bar charts illustrate. As with previous articles I have split the non-handicap chase data into two in order to compare 2009 to 2014 run style results with those for 2015 onwards. The bar chart below compares the win strike rates (SR%) over these time frames:

 

The difference in percentages is not significant when factoring in the reduced field sizes, so we can reasonably expect these run style patterns to continue in the coming season and over the coming years.

Onto the A/E values now and their comparison over the two time frames:

 

Again, there is very good correlation within the respective run style groupings.

The general pattern is clear, so let's drill down into different areas to see what differences, if any, there might be. With the data being consistent enough across the two halves of time I will analyse these areas over the whole period (Jan 1st 2009 to July 31st 2021).

 

Run Style Bias in Non-Handicap Chases by Distance 

I have split all race distances into three groups, as I did in the previous instalments in this series: the groupings are 2m 1f or less, 2m 2f to 2m 6f, and 2m 7f or more.

2m 1f or less

 

The shorter distance races seem to accentuate the front running bias. In addition hold up horses perform more poorly than the 'all distance' group. The stronger front running bias can be appreciated more clearly perhaps by comparing SR%, A/E values and Impact Values (IV) between these 2m1f or less contests with races of 2m2f or more:

 

Let us now split the last two groupings up and you will see they are similar, still giving an edge to front runners:

2m2f to 2m 6f

 

2m 7f or more

 

One factor to keep in mind in non-handicap chases is that there can often be a significant ability bias; that is, the horses at the front are frequently a good bit better than some of those at the back.

 

Run Style Bias in Non-Handicap Chases by Course

Let's move on to specific racecourses. The problem when slicing data to the course level is that sample sizes are quite limited, especially when focusing on specific course and distance combinations.

Only twelve specific course and distances have hosted thirty or more qualifying races during the period of study. These are the strongest front running biases from that small group:

 

Chepstow 2m 7f or more

At Chepstow they tend to race over 3 miles exactly (officially, at least). Twice in the last 12 years they have raced over further. Here are the run style splits by strike rate:

 

Leaders seem to have enjoyed a huge edge at the Welsh venue. The A/E values back this up from a betting perspective:

 

Front runners enjoy an A/E value of over 2.00 (2.16) with all other run styles falling well below 1.00. 

 

Exeter 2m 7f or more

At Exeter they race over 3 miles only. Here are the front running strike rates:

 

While not as strong as the Chepstow bias, it is still far more beneficial for a horse to be ‘on the front end’. Moreover, the prominent racer stats are strong, too, suggesting that this is not an easy C&D over which to come from off the pace. A/E values for the same now:

 

Again, we see good correlation, backing up previous observations. There is a less striking disparity between front of pack racers and later runners than at Chepstow's longer distance, but it is still comfortably the difference between long-term profit and the poor house.

 

Cheltenham 2m 4f and 2m 6f

Combining these two trips across the two courses (New and Old) at Cheltenham shows that that even with the fiercely competitive racing, and the individual track nuances, front runners remain the value:

 

As you might have come to expect the A/E values mirror the above run style split:

 

These are the three strongest course and distance run style biases I could find with big enough datasets. There will doubtless be others but some 'flyers' will need taking due to the small samples.

 

Run Style Bias in Non-Handicap Chases by Race Class

With such limited useful data at the course level, I decided to explore alternative areas. Class of race is something I have analysed before in relation to run style, but never in non-handicap chases. I decided to split the class of race into three groups, namely Classes 1 and 2, Classes 3 and 4, and finally Classes 5 and 6 (including the majority of hunter chases). Here are my findings for strike rates:

 

Now this is interesting. The orange bars, showing Class 3 and 4 run style results, clearly indicate at this class level the front running bias is at its strongest. Looking at the lowest class group (5 and 6) there is a front running edge but it is somewhat diminished. The highest Classes (1 and 2) have very similar figures for front runners and prominent racers. Those forward groups still have the edge on hold up horses but the bias is less potent than with the Class 3 and 4 group.

There are many ways one could interpret these findings. I am going suggest the following.

Firstly, in Class 1 and 2 races, these are often more competitive and hence it may be harder for front runners to repel later running challengers with a touch of quality. In Class 5 and 6 races, I surmise that front runners have less ability and, as such, are unable to sustain their pace throughout the whole race, thus fewer end up winning.

Finally, then, Class 3 and 4 races may then be the sweet spot, with horses that lead early having enough ability to see a race out while being faced with slightly lesser calibre rivals compared with Class 1 and 2 contests.

The above is, of course, just one interpretation and I may be wrong. Racing, and particularly analysing and betting on racing, is as much about opinions and theories as it is cold hard data.

 

Run Style Bias in Non-Handicap Chases by Field Size

My next port of call was to look at field size to see if smaller or bigger fields had any bearing on run style stats. I have again split the results up into three groups – races with 7 or 8 runners; those with 9 to 11 runners; and those of 12 or more runners.

For field size one needs to look at A/E or IV values rather than strike rates. Strike rates give an inaccurate comparison as seven-runner races are going to produce higher strike rates across the board than, say, twelve-runner races. I've used A/E as it offers an indication of market potential, higher numbers (above 1.0) leaning towards a suggestion of future profitability.

The bar chart below compares each section.

 

The data suggest that there may be less of an edge to front-runners in mid-sized fields (9 to 11). Unlike with the class data, I cannot offer a ready explanation for why this might be the case. I had expected smaller fields to do quite well in terms of front runners due to the limited competition numbers wise, but I had not expected bigger field races of 12 or more runners to be on a par with 7- or 8-runner races, however.

 

Run Style Bias in Non-Handicap Chases by Going

I wanted to study the going to see if faster or slower ground conditions made a difference. Here, I have split the data in two – firstly good going or firmer; secondly good to soft or softer. The bar chart shows the findings. The blue bars are good or firmer; the orange good to soft or softer:

 

One could argue there is a slightly stronger front running bias in softer conditions, as well as it seeming to be harder to win from the back or near the back (held up) when the turf is wet. However, the differences are relatively small so I'm not fully confident that this is the case.

 

Trainers showing a Front Running Bias in Non-Handicap Chases

Let's finish off by looking at trainers' front-running percentages. Below is a table highlighting the percentage of runners from a given trainer that front run. This type of information can be very useful when trying to work out which horse might lead early in a race, especially when there is little evidence in the form book. Here I have included those trainers with at least 50 runners under the conditions (7+ runner non-handicap chases, 2009 to end July 2021) :

 

There are some huge variations!

Donald Mc Cain’s runners lead over 39% of the time, just about four out of every ten runners; and Rebecca Curtis also seems to favour the front running option: not only do 31% of her horses take the early lead but 30% of those which lead have gone onto win their respective races.

 

Run Style Bias in National Hunt Racing Overall Summary

Looking at the four articles in this series as a whole, I hope readers can see the unarguable edge that front runners have in National Hunt racing. It is true that some front running biases are stronger than others, but in every article, thanks to a bit of extra digging, useful angles and stats have emerged to be deployed throughout the autumn, winter, spring and beyond.

If you have never personally researched run style angles or ideas, I really recommend doing so. Geegeez gives you the tools to unearth profitable pace/run style angles that very few other punters know about. And the great thing is, gathering and crunching data on Geegeez is a quick (and, dare I say it, fun!) process. Gone are the days of scrolling through formbooks and looking at one race at a time.

When you do find something interesting, or if you have any ideas you’d like me to research, please post them in the comments below.

- DR

Run Style Bias in Handicap Chases

In my first two articles in this series revisiting run style bias in National Hunt racing I looked at run style bias in hurdle races, handicap and non-handicap; for this third piece I will perform a similar study on handicap chases.

What I mean by pace (or run style) is the position a horse takes up early on in the race, normally within the first furlong or two, which often defines its running preference. The first few seconds of any race see the jockeys manoeuvring their horses into the early position they wish them to take up. Sometimes, of course, the horse has other ideas (!) and you may see a horse being restrained as it wants to press forward but the jockey is keen to hold it up. Horses ‘fighting for their head’ often pay the price later in the race as they have used up too much energy fighting their jockey early.

geegeez.co.uk has created some powerful resources and the "pace" section is probably the one I personally use the most. The stats I am sharing with you here are based on the site’s pace / run style data. These data on Geegeez are split into four sections – Led (4), Prominent (3), Mid Division (2) and Held Up (1). The number in brackets is the run style score that is assigned to each section. Below is a basic breakdown of which type of horse fits which type of run style profile:

Led – horses that lead early, usually within the first furlong or so; or horses that dispute or fight for the early lead (e.g. "pressed leader"). The early leader is often referred to as the front runner;

Prominent – horses that lie up close to the pace just behind the leader(s);

Mid Division – horses that race mid pack or just behind the mid-point;

Held up – horses that are held up at, or near the back of the field.

Overall Run Style Bias in Handicap Chases

As with the previous two articles - which you can read here and here - I have only looked at races with eight or more runners: this avoids many falsely run races which often occur when there are small fields. The first set of data I wish to share with you is the overall run style stats all National Hunt handicap chases races in the UK from the beginning of 2009 to the end of July 2021, a large dataset of around 65,000 scored runners*:

*the run style of some horses is indeterminate from their in-running comments; such horses are excluded from the sample

 

As I mentioned last time, it is important to be aware that the number of runners in each run style group differs: prominent and hold up categories usually have more runners within their groups. 'Leaders' is the smallest group as usually you only get one early leader in this type of race, occasionally two when there is a battle for the early lead. Hence although raw strike rates have significance, it is more important to look at the Impact Values (IV) and the A/E index (Actual winners/Expected winners). More information on these IV and A/E metrics can be found here. If you're not familiar with them, I'd strongly encourage you to check out that article: it may just change the way you look at racing form!

Looking at the table we can see that the early leader goes on to win approximately one race in every six, which is a solid performance, and leaders clearly have an edge as a whole. Prominent racers have proved the next most successful group of runners. These figures are very similar to the hurdle results we saw previously. Hence, as with hurdle races, when betting on handicap chases we should be looking for horses that potentially will lead or at least race close up to the pace.

The run style bias has remained relatively consistent over the last dozen years or so as the following bar charts show. I have split the handicap chase data into two time periods in order to compare 2009 to 2014 results with those for 2015 onwards. The bar chart below compares the A/E values over these time frames:

 

There is excellent correlation across all four run style categories showing that the profitable edge to front runners has remained consistent over the years, perhaps even increasing in more recent years. Comparing strike rates give us a similar picture:

 

Before moving on I would like to share with you the front runner performance data in handicap chases (8+ runners) by year.

 

I have discussed in previous articles how being able to accurately predict the front runner(s) would be a license to print money – this illustrates the point perfectly – just look at the Win PL (and EW PL) column(s)! Unfortunately, as discussed in some of my previous run style articles, predicting the front runner is far from an exact science – however if one could find a method where you could correctly predict it around 65 to 70% of the time, that would almost certainly suffice for long term profitability. I am fairly certain this figure is impossible to achieve if trying to find the front runner of every single race; however, some races are easier to predict than others pace wise and if you concentrated on a select few races it may well be possible. Remember, these returns are at starting price. Better could be achieved using exchange prices.

Answers to me and Matt on a postcard, please, if you are able to achieve the pace predicting ‘holy grail’! [Though I suspect you'd keep that to yourself!]

 

*

Let us now start narrowing down the stats into different datasets to see whether the front running bias is stronger or weaker under more specific conditions. With the data being consistent across the years I will analyse these areas over the whole time period (January 1st 2009 to July 31st 2021).

 

Run Style Bias in Handicap Chases by Distance

Time to see if race distance affects the run style biases at all in handicap chases. I have split race distances into three groups as I did for the previous pieces: the groupings are 2m 1f or shorter; 2m 2f to 2m 6f; and, 2m 7f or further. A comparison of strike rates within each run style group first:

 

As we can see there is little discernible difference in the run style data by distance in terms of strike rate. Leaders enjoy a strong edge at all distances while hold up horses struggle regardless of the length of the contest.

Onto comparing the A/E values now:

 

An excellent correlation once more showing that, regardless of distance, front runners enjoy a strong (and profitable) edge.

Finally, a look impact values:

 

Again, unsurprisingly given the previous two charts, the Impact Values continue showing a similar linear pattern: the closer to the front of the race a horse is in the early strides, the more likely it is to win.

 

Run Style Bias in Handicap Chases by Course

Next stop is to analyse which courses seem to have the strongest front running bias. I analysed the highest front running strike rates and the highest A/E values to come to a consensus. If a course made the top ten of either list it made it onto my final list. Overall 12 courses made one of the two the final lists, and those eight courses noted in blue bold font were in the top ten in both:

 

Let's look at some of these courses in more detail.

 

Run Style Bias in Handicap Chases at Doncaster

Doncaster has shown the strongest front running bias at the 2m 4f trip. The stats are quite remarkable and I had to triple check the data to make sure I was correct. There have been 28 races with the following run style splits:

 

As you can see 15 of the 28 races (54%) were won by horses that led or contested the lead early. Below is a pie chart showing the percentages of winners to races across each run style section.

 

What you also have to remember is that early leaders provided just 14% of the total runners. Hence, runners taking the early lead provided 54% of the winners from just 14% of the runners.

 

Run Style Bias in Handicap Chases at Hexham

Hexham’s figures for front runners are particularly strong at the shorter distances. They race at both 2 miles and 2 miles 1 furlong and the combined run style stats are as follows:

 

These figures indicate how vital it is to be on or close to the early pace at Hexham over these distances. 40 of the 47 races were won by early leaders or prominent racers which equates to 85% of all races. It is also worth noting that if the favourite or second favourite led early they went onto to win 13 races from just 22.

 

Run Style Bias in Handicap Chases at Perth

The majority of Perth handicap chase races are run over 2m4f or 3 miles. They do race over 2 miles and very occasionally at longer than 3 miles, but I want to focus in on the distances that have decent data sets. Over 2m4f there have been 52 qualifying races and over 3 miles there have been 73 races. The two charts below compare strike rates and A/E values at these two distances and as you can see the run style bias is virtually the same for each:

 

Perth, at these two distances, offer a strong front running bias and one that we should be able to continue to take advantage of in coming seasons.

 

Run Style Bias in Handicap Chases at Plumpton

The Sussex course of Plumpton favours front runners strongly at 2m1f and 2m4f, but at distances of 3m2f or more there is no edge at all.

 

The strike rate for front runners at the two shorter trips is more than double compared with the marathon handicap chases. A/E values show the same pattern with high figures of 1.91 and 1.87 for the shorter distances and just 0.88 for the longer trip.

 

Run Style Bias in Handicap Chases at other tracks

There are some courses and distances that do not favour front runners in handicap chases and here are a few stats which should steer you away from what you may have thought were potential betting opportunities:

  1. Over 2m / 2m 1f Chepstow has seen just 1 win from the front from 30 races;
  2. Over 2m2f to 2m6f Ffos Las has seen just 3 front runners prevail from 53 races;
  3. At Musselburgh the strike rate for front runners is the lowest of all courses with a figure of just 8.8% over all distances (SR% of under 6% at distances of 3 miles or more);
  4. At distances of 3 miles or more only four courses have seen more combined winners for horses that raced mid division or were held up, compared with combined winners for leaders / prominent racers – these were Aintree, Newcastle, Plumpton and Worcester.

 

Jockeys showing a Front Running Bias in Handicap Chases

Next I want to look quickly at jockeys and to specifically peer at those who go to the front more than the norm. Below is a table of the top ten jockeys in terms of percentage of front running rides compared with all rides. Hence if you had 1000 rides and went to front early in 200 of them your FR% would be 20%.

 

To give some context, the average figure for all jockeys stands at 13% in terms of leading early.

 

Charlie Deutsch not only likes to lead more than most, but his strike rate on such runners is impressive at 22.7% (A/E 1.52). Nico De Boinville and Harry Cobden are also worth mentioning as they are both very successful when taking the early lead.

De Boinville’s figures are as follows:

 

He is a jockey who seems to excel when close to or up with the pace. In contrast his record on horses that come from off the pace is poor.

Meanwhile, Harry Cobden’s figures are similarly impressive.

 

These numbers are, I think, quite enlightening.

 

Before moving away from jockeys I wanted to mention a stat that unfortunately is not relevant for today, but is one worth sharing, because to me it emphasises how good a jockey Tony McCoy was. When he was riding in handicap chases his win strike rate on horses that raced mid division / held up was just under 15%. The average figure for all jockeys whose runner had an early position in the back part of the pack stands at a measly 7%.

 

Trainers showing a Front Running Bias in Handicap Chases

The final section of today's article shows trainers' performance with front runners. Here are the trainers who have the best win strike rates from front runners – the chart below includes all trainers with a SR% in excess of 20%:

 

There are some big names here including Messrs. Henderson, Skelton, Hobbs and O’Neill. Seeing Jonjo O’Neill on the list is interesting because he rarely sends his runners out into an early lead as the pie chart below clearly illustrates:

 

I am not sure why O’Neill favours hold up tactics so much as he is more than twice as successful in strike rate terms with his front runners compared to his hold up horses. It might be that some owners prefer their runners patiently ridden...

It is clear that some other trainers have a greater understanding of the importance of early run style, as illustrated by the stats for Donald Mc Cain and Charlie Longsdon:

 

There are boundless possibilities in terms of researching micro-angles from run style in handicap chases, this article only scratching the surface to that end. Hopefully this article has again demonstrated that if you are not considering run style when making your selections, it might be a very good idea to start doing so. I also hope you are inspired to use the Query Tool on Geegeez to crunch some data and find your own pace / run style angles.

Thanks for reading,

- Dave

Run Style Bias in Handicap Hurdle Races

This is the second instalment in my latest series on run style bias in National Hunt racing. After analysing non-handicap hurdles last time, it is time to move onto handicap hurdle races.

Pace, or the running styles of horses, has long been an area of interest as any bias can potentially give us an edge when analysing a race. It is still an area that many punters ignore, and the longer that goes on the better as far as I am concerned!

Apologies for the regular readers of these pieces, but for new readers I must give a quick explanation of pace (or run style, which for our purposes are interchangeable) and how Geegeez can help you.

The first furlong or so of any race sees the jockeys try to manoeuvre their horses into the early position they wish them to adopt. Some horses get to the front and lead (referred to as front runners); some horses track the pace just behind the leader(s); other horses take up a more middle of the pack position, while the final group are held up near to, or at the back of the field. Geegeez racecards have a pace tab which is split neatly into four sections which match the positional descriptions above. So we have: Led (4), Prominent (3), Mid Division (2) and Held Up (1). The number in brackets are the scores that are assigned to each run style, which for a mathematician like myself are really helpful as I can make easy comparisons between different runners, courses, trainers, jockeys, etc.

As with my previous research I have only looked at races with eight or more runners – this avoids many falsely run races which are more likely to occur in a small field scenario.

The first set of data I wish to share with you is the overall run style dataset for all handicap hurdles races in the UK from 1/1/09 to 31/7/21. I have used the Geegeez Query Tool for all my number crunching – the pace section on Geegeez is another area on the site where you can gather individual course run style data from:

 

These figures are far more even than we saw in the non-handicap hurdle research. In non-handicap hurdles we saw front runners (early leaders) win roughly 18% of the time, form the smallest run style group. Here, though, leaders have won only around 12% of the time. That is to be expected given the generally more competitive nature of handicaps when set next to non-handicaps. Further, before we write off a leader / front running run style bias, it should be noted that the A/E figures still give front runners a positive market edge (1.06), as does an impact value (IV) of 1.35 - meaning early leaders are winning about a third more often than the overall population of handicap hurdlers.

That said, it is clear that the front running bias is weaker in handicap hurdles compared with non-handicap hurdles.

The success for each run style section has stayed extremely consistent over the last 12 years or so, as the following bar charts illustrate. I have split the handicap hurdle data into two in order to compare 2009 to 2014 results with those for 2015 onwards. The bar chart below compares the A/E values over these time frames:

 

That's an amazingly strong positive correlation across all four categories in market influence (A/E) terms.

 

Comparing the strike rates give us a similar picture of consistency:

 

Now it is time to start narrowing down the stats into different data sets to see whether any stronger edges emerge. With the data being consistent across the years I will review the following over the full time period (Jan 1st 2009 to July 31st 2021).

Run Style Bias in Handicap Hurdles by Distance

Let us first look to see if race distance affects the strike rates or A/E values. I have split race distances into three parts as I did for the previous article: the groupings are again 2m 1f or less; 2m 2f to 2m 6f and 2m 7f or more. Here is a comparison of strike rates within each group:

 

These are a remarkably consistent set of figures for each run style group, regardless of distance.

Below are the Actual vs Expected (A/E) figures*.

* A reminder that you can read about all of the metrics we publish on geegeez.co.uk in this article

 

Once again, there is correlation across the board: perhaps slightly poorer front running stats for the longer distances, but that is probably not statistically significant. All early leader / front running A/E values are in excess of 1.00, which is noteworthy.

 

Run Style Bias in Handicap Hurdles by Course

The second area to analyse is by racecourse.

Normally I like to concentrate on positive front running courses but to give readers more useful information I feel it is also worth sharing the course records where front runners perform relatively poorly. These tracks have all seen front running win strike rates of under 10% in the past 12 seasons, which may only partly be explained by field size:

 

We need to be wary about Cheltenham’s low figure as this is skewed by the fact that the average field size there has been a huge 16.5 runners. Hence, as front running tracks go I would liken it to Wetherby – below average, but nowhere near as poor as the raw strike rate performance implies.

Moving onto to the positive courses in terms of front running (early leaders) performance, and below is a look at those tracks with a handicap hurdle race front running win strike rate% greater than 13%:

 

14 courses make the list and I want to compare this list to the course list with the highest front running A/E values, with the hope (and expectation) of seeing most of the courses in both graphs:

 

As can be seen, 13 of the 14 courses appear in both graphs / lists – Leicester and Ayr are the ones to appear just once. This is extremely positive, implying the run style advantage to those who go on from the outset is still not fully factored into the market (insofar as it is predictable before the race begins - nobody said this was an exact science!), and it makes sense to look at a couple of these courses in more detail.

Bangor on Dee

Bangor-on-Dee tops the front running list in terms of strike rate and lies second when comparing A/E values. You may recall from the first article in this series that Bangor also topped the front running charts in non-handicap hurdles over 2m 1f or less. I did not look in detail at other distances at Bangor in that piece but I can reveal that the 2m4f trip in non-handicap hurdles saw a front running win strike rate of 32.6 % with a huge A/E value of 1.79. This add further confidence to the very positive looking handicap hurdle data here.

Let me break the Bangor handicap hurdle data down. I am going to be looking at percentage of winners from each run style section. Here is how the percentage split looks for all courses. This will help us when trying to appreciate the strength of any bias:

 

Over this trip the front running bias is moderate – the percentage figure for winning front runners is 16% compared to the all courses average figure of 15%. The one group that has performed above the norm here is the mid division group – 23% of the winners at Bangor compared with 18% for all courses.

Over two and a half miles, we see a big difference with front runners winning roughly a third of all races: 33% compared with the overall course average of 15% is a very significant finding and a very strong looking front running bias.

 

Onto the longest Bangor hurdle distance now of three miles:

 

Again, a decent enough front running bias over this trip. 22% of all winners have been front runners which gives them a solid edge of around 50% on the average front running strike rate at all courses across all distances. The A/E value for front runners over this trip is an attractive 1.66.

At Bangor therefore, potential front runners over 2m4f and beyond are definitely worth noting.

 

Ascot

I was quite surprised to see Ascot as giving front runners such a clear edge in handicap hurdles. I had perceived Ascot handicaps to be very competitive and thought front runners might actually struggle. However, at all distances Ascot’s front runners perform extremely well. Below are the two mile data:

 

23% of two mile Ascot handicap hurdle races were won by front runners – remember the average all courses figure stands at 15%. The A/E value is strong at 1.68.

 

I have lumped the intermediate 2m 4f and 2m 6f data together as they are similar distances and give us a bigger collective data set:

 

There is a stronger edge here with 27% of races won by front runners and fully 60% won by front runners or prominent racers. The front running A/E value is a huge 1.83.

 

Over the longest Ascot hurdle range of three miles, the figures are thus:

 

Again, there is a really solid front running edge (A/E 1.70) and, related, it seems harder for hold up horses to prevail (22% strike rate compared with the all courses average figure of 32%).

 

I have one final stat to share regarding Ascot handicap hurdles: fancied front runners, whose price was 6/1 or shorter, won 15 of 41 races. If you had been able to predict that these 41 horses would lead early, backing all of them would have returned you an impressive 88p in every £1 bet. Oh, for a crystal ball!

 

Other strong course / distance front running biases

Below is a list of other course / distance combinations where front runners have done especially well in recent years:

Sedgefield 3m 4f

The marathon distance of 3 miles 4 furlongs at Sedgefield would not necessarily be a track and trip where you’d expect handicap hurdling front runners to thrive. However, the stats suggest otherwise – the bar chart below compares the win strike rate percentage for each of the four run style categories:

 

Front runners have enjoyed a massive edge, backed up by a huge A/E figure of 2.26. It also can be seen that hold up horses have a miserable record showing that is extremely difficult to make up ground here over this distance. Most lower class marathon handicap hurdlers lack a gear change: who knew?!

 

Haydock 3m

Not quite as strong a bias as the Sedgefield one, but a significant advantage to the front again nonetheless:

 

Front runners with this kind of strike rate coupled with an A/E of 1.92 is not to be sniffed at!

 

Cartmel 2m 1f 

The final course/distance combo to share graphically is Cartmel's 2m 1f win strike rate, which demonstrates another strong looking front running bias:

 

Front runners in this context have produced a very satisfactory A/E value of 1.63.

 

Sticking with Actual vs Expected, there are five other course and distance combinations whose A/E value for front runners is in excess of 1.50 – they are:

Catterick 2m

Ffos Las 2m

Newbury 2m and 2m 1f

Exeter 2m 1f

Musselburgh 2m 4f

 

Those are well worth noting, and may provide a starting point for your own Query Tool research should you feel so inclined.

 

Hold up horses

For fans of hold up horses, there is a handful of course and distance groupings where the late runner A/E sneaks above 1.00. The A/E values are in brackets in the table below:

 

In races at these tracks and over these distances, front runners do not enjoy the advantage, conceding that to hold up horses. For the record, the Lingfield Park data in each grouping is very small indeed so caution is advised.

 

Run Style Bias in Handicap Hurdles: Summary

To conclude, front runners enjoy far less of an edge in handicap hurdle races when compared with non-handicap hurdles, but there are still a number of courses (and/or specific course/distance combinations) where we need to be aware of a possible edge.

Elsewhere, there is a smaller number of track/trip combinations that tend to favour hold up horses.

Knowing how a race may pan out from a running style perspective is always an important factor to consider, and the knowledge of any potential biases a significant bonus. Hopefully the information above, allied to specific race pace maps found on this website, will give you a leg up with your handicap hurdle betting.

- DR

Pace Bias in Non-Handicap Hurdle Races

With the evenings now sadly drawing in, many punters will soon begin to think about the upcoming National Hunt season, writes Dave Renham. So Matt and I felt it was the right time to revisit pace bias in National Hunt racing. In the past I have written several articles for Geegeez on the topic of pace and for this piece I am going to take an in depth look at non-handicap hurdle races.

I appreciate many of you reading this will have read some or all of my previous articles, but for new readers it is important to explain what pace in a race means and how we measure it. Pace in this context is connected with the running styles of the horses. When I look at pace bias my main focus is the initial pace in a race and the position horses take up early on.

geegeez.co.uk has an excellent pace analyser tool and the stats I am sharing with you in this article are based on that tool’s pace data. The data on Geegeez are split into four styles and accompanying points – Led (4), Prominent (3), Mid Division (2) and Held Up (1). The numbers in brackets are the pace scores assigned to each section.

For this article I have only looked at races with eight or more runners – this avoids falsely run races which often occur when there are small fields.

The first set of data contains the overall pace stats from all 8+ runner National Hunt non-handicaps in the UK from 1/1/09 to 31/7/21:

 

It is important to keep in mind that the number of runners in each pace group varies: there are far more runners in the prominent and hold up categories as you can see. 'Leaders' is the smallest group as usually you only get one early leader in this type of race, occasionally two when there is a contested early lead. Hence although raw strike rates have relevance, it is more important to look at Impact Values (IV) and the A/E index (Actual winners/Expected winners).

Leaders clearly have an edge as a whole, with prominent racers the next most successful. Therefore, as a general rule of thumb, in non-handicap hurdle races you want to be focusing on those horses that are the most likely to lead early (or at least race prominently and close to the front end).

When we have looked at draw biases on the flat we became aware that such biases can evolve and change over time. In terms of pace bias, though, I have always hoped (or assumed) that they are less likely to change much, if at all, over time. To check this theory out I decided to split the non-handicap data into two and compare 2009 – 2014 with 2015 onwards. The bar chart below compares the A/E values over these time frames:

 

Excellent correlation across all four pace categories so, because A/E is a measure of market performance, this gives increased confidence that the value in any pace biases is likely to replicated in the foreseeable future. Comparing the strike rates shows a similar level of consistency across the two time periods:

 

So we have a good starting point from which to start narrowing down the stats into different data sets to establish whether front running bias is stronger or weaker under more specific conditions. As the data seems consistent across the years I will analyse these areas over the whole time period (2009 to July 31st 2021).

 

Impact of Run Style by Race Distance, Non-Handicap Hurdles

I always feel distance is the best place to start when drilling down into pace data. A look first at the shorter distances.

2 miles 1 furlong or less

 

These figures are similar to the overall stats for all distances, so let us review by course. The chart below compares A/E values for all courses (min 50 races) – courses with A/E values of 1.00 or bigger are shown:

 

Bangor On Dee has the highest front-running A/E value at 1.48 and when we break the overall course stats down, we can see other metrics which point to that extremely strong front running bias:

 

Not only does the front running edge strengthen, it is clear that hold up horses struggle even more than the norm. For the record, if you had been able to predict the front runner(s) in each race at Bangor you would have made an SP profit to tune of 38 pence in the £. If only it was that easy!

The next chart shows the courses with the lowest A/E values for front runners over this trip:

 

Doncaster racecourse has the poorest figures for front runners and the overall stats for the course are as follows:

 

I think what this shows is that the course and distance stats are definitely worth drilling down on. The difference between Bangor and Doncaster at this distance range is very significant.

Before moving distances I would like to share some stats around performance of "the favourite" based on their running style:

 

Again, this shows clearly the importance of pace and running style. It still bemuses me how certain trainers continue to hold up their runners, when surely it is generally worth pushing them up with or close to the pace.

 

2 miles 2 furlongs to 2 miles 6 furlongs

It is always difficult to group National Hunt distances ‘perfectly’ when analysing large data sets, but for this article I wanted to split the full gamut of race distances into three parts and this seemed like a sensible middle distance grouping.

Here are the pace data for all courses for all non-handicap hurdle races over the 2 mile 2 to 2 mile 6 trip:

 

The figures are similar to the shorter distances though possibly the front running bias hass very slightly diminished. In terms of courses, amazingly Bangor on Dee is top again from a front running bias perspective – there is unquestionably a marked advantage to those horses that lead early at Bangor.

 

I thought for this interim distance group I would investigate some run style trainer data. I wanted to see which trainers had been the most successful when sending their runners out into the early lead in non-handicap hurdle races of 2m 2f to 2m 6f.

To that end, below are two graphs – firstly, trainer performance with front runners in terms of win strike rate; and secondly, looking at their respective A/E values.

 

 

As you might expect there are a high proportion of trainers that appears in both charts. Nicky Henderson tops both lists but this does not mean he sends a huge proportion of his runners to the front early; it shows, however, that when he does they fare extremely well. For the record here is Henderson's breakdown by running / pace style over this distance block:

 

His front runners clearly do best in terms of win strike rate, A/E value and IV. It is interesting though that only 11% - one in nine - of Henderson's horses actually take the early lead. But nearly half of them win!

It does make me wonder if trainers are really aware of pace bias... Below is his 'pace pie chart' in terms of percentage of runners that demonstrate a particular pace or running style.

 

44% of his runners raced off the pace early which is far too large a number in my opinion.

 

2 miles 7 furlong or more

The third and final grouping are the longer distance non-handicap hurdle races, from just shy of three miles upwards.

 

There are far fewer longer races as can be seen, but the same pattern emerges. Front runners perform best with prominent runners next best.

 

Trainers by Run Style (All distances)

I have already touched upon trainers but thought it might be interesting to create some trainer pace figures. To create the trainer pace figures I have simply added up the Geegeez pace points for a particular trainer and divided it by the number of runners. The higher the average the more prominent the trainer tends to race his charges. I have created trainer pace figures which cover all distances in non-handicap hurdles. Here are the trainers with the highest averages:

 

Rebecca Curtis tops the list and clearly favours positioning her runners nearer the front than the back. Her 'pace pie chart' below demonstrates this even more clearly:

 

As you can see 25% of Curtis's runners take the early lead, while another nigh on 50% race prominently and close to the pace. Ms Curtis is a trainer who understands the importance of forward run styles. It should come as no surprise therefore that you would have made a profit backing all of her runners ‘blind’ during this time frame. For the record, 53 of Curtis's runners were held up, and only 4 won (SR 7.55%). Compare this to 23% and 21.83% win strike rates for her early leaders and prominent racers.

Let us now review Alan King’s pace pie chart as a comparison to Curtis.

 

His pace average stands at 1.99 with a measly 2% of his runners sent into an early lead. Overall losses for King have been significant especially with runners that raced mid division or near the back early.

*

I do believe that pace in a race is something which must be factored in to your betting. Pace biases vary from race type to race type, distance to distance, course to course, etc. However, if you are prepared to do some digging that other punters are not, you will give yourself a significant edge over the crowd.

This article has hopefully offered a good chunk of information to digest, but in reality I have barely scratched the surface. If you really want to profit from run style/pace then the Geegeez tools are there for you to test your own ideas and crunch pace data to your heart’s content.

- DR

Using Market Rank to Assess Trainer Performance

When it comes to horse race betting, the role of the trainer is of pivotal importance to a great many punters, writes Dave Renham.

That may simply be the trainer themselves, with no filters applied: just as some punters have favourite jockeys, many have favourite trainers and, equally, other trainers they tend to ignore. Trainer form at the course, trainer form over the past 14 days, trainer records with 2yos, the trainer / jockey combo are examples of slightly more refined potential ‘trainer weapons’ in a punter’s armoury.

Personally, I feel trainers and trainer stats have their place but for me they are far from the ‘be all and end all’. Having said that, I believe that digging a little deeper into trainer performance can be a useful exercise. Looking for an edge that most punters would be unaware of is always worth investigating!

A Different Approach to Assessing Trainer Form

In this article, then, I am attempting to evaluate trainer performance in a different way from the ‘norm’. The basic idea is to compare the odds rank of each trainer’s runners with their finishing positions. This is intended to offer a much broader perspective of trainer performance, rather than simply focusing on winners, strike rate and/or returns. I am hoping that we may find a few lesser known trainers whose horses tend to outrun their odds – an ‘over performance’ if you like.

The data I have collated covers three full seasons of UK flat racing (2018 to 2020) and I have focused solely on handicaps. I am using handicaps because they are generally a more consistent data set to use where runners have a theoretically more equal chance in the round.

As with any method there are potential flaws or issues that need to be discussed. Principally, the comparison of finishing position with odds position is going to hinder horses that start favourite as they will be unable to ‘over perform’. The best they can do is match their odds position by winning the race. Hence trainers who have had a good number of favourites will be at a disadvantage using this approach. Having said that, there are ways to try and balance the data as I will attempt to demonstrate later.

There are three possible outcomes in terms of position in the market compared to finishing position:

  1. Expected result – eg a horse 3rd in the betting rank finishes 3rd, a horse 7th in the betting rank finishes 7th etc;
  2. Positive result – eg a horse 5th in the betting rank finishes 2nd, a horse 9th in the betting rank finishes 5th etc;
  3. Negative result - eg a horse 4th in the betting rank finishes 6th, a horse 2nd in the betting rank finishes 4th etc.

 

Trainer Performance

So let us look at trainer performance using these parameters. Firstly, here are the top 25 trainers in terms of positive results using this approach. The table shows the breakdown of terms of total runs, number of positive results, number of negative results and number of expected results. It also breaks these down into percentages – positive percentages, expected and positive percentages combined, and negative percentages:

 

All trainers have a ‘positive and expected combined’ percentage of at least 60%. Lisa Williamson tops the list with 61.12% of her runners outperforming their position in the odds market (82.54% positive / expected combined). However, her overall win strike rate is around 3% so although her runners tend to run above expectations she is not a trainer that we can easily exploit. Indeed, most of the trainers in this list have relatively modest overall win strike rates, but I would say if you fancy one of their runners, you can at least expect it to run well and more likely than not to run better than its price suggests.

In order to try and find a group of trainers that we may be able to profit from, it makes sense to look at a more focused type of runner nearer the head of the market. To that end, I narrowed the search to horses that were not favourite but were priced from 4/1 to 12/1. The theory is that these runners will go closer to winning if they outperform their odds position. It also eliminates favourites who ultimately can only match their market rank, not exceed it:

 

Brett Johnson, who is second in the list, has made an SP profit within this price bracket of 18p in the £. His runners have hit the frame an impressive 42% of the time. Indeed, several of the trainers in this table made a profit to SP and they are shown in a bar chart below. It shows their win strike rate% in blue and their percentage profit in orange. They are ordered with the most profitable starting from the left:

 

For the record, four other trainers would have made a profit betting to Betfair SP – they were Christine Dunnett, Antony Brittain, Grace Harris and Linda Perratt.

Trainer Performance: Comparison Values

Another way to compare finishing position with market position is to calculate what I will call a ‘Comparison’ Value. In order to explain clearly what I mean, let me show you how to calculate this figure by using a simple example.

We start by looking at the difference between the market position and the finishing position. Let us imagine trainer ‘A’ has had 10 runners with the following results:

 

So ten races and we then add up the difference column. This gives us a total of 12. To get our ‘Comparison’ Value we then divide this total difference by the total number of races. So in this example we have 12 divided by 10. This gives us a ‘Comparison Value’ of 1.20. In other words, on average the runners from this hypothetical trainer have finished 1.2 places higher than their odds rank suggested they should.

Clearly trainers can achieve positive or negative Comparison Values depending on their overall performance. I have calculated these figures for all trainers over this three year period – again I have ignored any favourites for the same reason as discussed earlier in the article.

Below are the trainers who have achieved a figure of 1.00 or greater.

 

The figures are slightly skewed due to the fact that most of these trainers primarily run less fancied horses. It therefore makes it easier for them to outperform their odds rank over time. Thus it again makes sense to use this ‘comparison’ method closer to the head of the market, by deploying our 4/1 to 12/1 price bracket (and again excluding favourites). This creates a more level playing field.

At this point the figures for all trainers drop markedly and only three have managed a positive Comparison Value – Michael Attwater, Derek Shaw and Mike Smith (R Michael Smith). However, here are the top 30 trainers within this price bracket in terms of highest Comparison Values:

 

I do feel these trainers are ones to keep on the right side of with runners that are priced around the 4/1 to 12/1 mark in handicaps. Not only would I look to exploit them for occasional straight win bets, I would look closely at each way options (doubles and trebles) as well as placepot options. For any spread bettors out there, an unconventional way of evaluating trainers and their likely performance has definite potential. Maybe one of the ideas mentioned here could provide the genesis of that sought after edge.

Summary

No method, idea, or rating is fool proof. Ideas I have discussed in this article certainly come into that category. However, in order to try and stay ahead of the game, it is worth our while thinking ‘outside the box’. Going against the crowd often pays dividends as you are more likely to obtain value for your selection, if the masses aren’t backing it too.

There are countless ways to analyse data: I’m not saying what I have done here is perfect, but it is a different slant and was interesting and enlightening from my personal perspective. I hope you’ve taken something from it as well.

  • DR

 

When Trainers Run Two in the Same Race

A dilemma that faces punters from time to time is when a trainer saddles two or more runners in the same race, writes Dave Renham. Do you take the obvious option and back the shortest-priced runner? Or is there value in backing the outsider of the pair? Whichever approach you take, it’s likely that many of you can recall times when you backed the wrong one!

The scope of this article is restricted to looking at trainers’ performance when they have exactly two runners in the same race. The data has been taken from UK flat races (turf and all weather) from January 1st 2014 to June 28th 2021. I have restricted it to two runners purely for ease of data compilation, as well as the fact that not many trainers run three or more horses in the same race on a regular basis (Aiden O’Brien the obvious exception).

All profit and loss is calculated to Industry Starting Price. For the shorter priced horse of the pair I will call this the “first string”, the bigger priced runner will be known as the “second string”.

Let us first look at trainers that have had at two or more runners in the same race on at least 100 occasions (hence at least 200 runners overall). There have been 49 trainers that qualify against that stipulation:

 

Below are the combined results of all runners for each trainer (i.e. both first and second string):

 

Not surprisingly, just three of the 49 trainers show a profit when looking at both strings as a whole. It is hardly likely that backing both runners for every trainer in every race is going to make a profit long term. But let's see what happens when we break the data down and compare strike rates between first and second string runners. I have done this in four graphs in order to show the comparison pictorially and, hopefully, more clearly.

My approach was to add up the winners and work out which percentage of all the winners came from the trainer’s first string (shorter priced runners) and what percentage came from the second. For Charlie Appleby, for example, he has had 85 winners of which 61 were first string runners (71.8%); 24 winners came from second string runners (28.2%). The blue bar accounts for first string runners, the orange bar for second string.

 

Overall, when combining all 49 trainers, roughly 75% of the winners have come from their first string entries, thus 25% from their second string. I would guess these figures would be roughly what we might have expected.

As can be seen, however, there is a wide fluctuation when analysing the performance of individual trainers. John Bridger, for instance, has had no winners from his second string runners, whereas Scott Dixon has very even stats with 17 first string winners (56.7%) compared to 13 second string winners (43.3%).

 

Trainers to note with first string runners

Eight trainers have made a blind profit to SP with their favoured runner of the pair, while a couple have essentially broken even. The table below gives their individual stats ordered by win profit / loss.

 

Of course, we have to be careful when looking at relatively ‘raw’ data like this: two trainers have made a profit purely due to one big priced winner each - Mick Appleby's figures are skewed due to an 80/1 winner, while Gary Moore had a 50/1 winner. It is also worth noting that Dean Ivory had two winners at 50/1 which make up most of his £123 profit (though he was still profitable even allowing for that brace of bullseyes).

Let's now dig a little deeper into some individual trainers.

 

John & Thady Gosden

The Team Gosden partnership, whose stats include Gosden Senior on his own previously, have broken even with their first string runners from a very decent sample size. I thought it would be worthwhile to see if breaking the data down further may reveal a potentially profitable angle or two.

With that in mind, let's first look at race type – the bar chart below compares strike rate (in blue) and ROI% (profit/loss) in orange.

 

 

As can be seen, there were crippling returns in handicaps from a modest strike rate (relatively) of around 13%.

The Clarehaven yard enjoyed similar strike rates, at around double the handicap clip, in maidens and other non-handicaps (e.g. Group, Listed, Stakes races etc), excluding novice races; similar returns, too, with a tiny loss in maidens and a tiny profit in non-handicaps.

Far and away the best figures for Gosden’s first string runners have come in Novice races, where they've notched a strike rate of 33% with strong returns of 14p in the £ at SP.

The Novice race stats can be improved slightly if we focus on the front end of the market. Gosden’s first string runners that have started 4/1 or shorter have provided 35 winners from 97 (SR 36.1%) for a profit of £20.19 (ROI 20.8%).

 

Roger Varian

There are some interesting data to share also regarding Roger Varian. His first string runners have an excellent record when sent off at single figure odds. Under these circumstances Varian’s runners have provided 27 winners from 98 runners (SR 27.6%) for a healthy profit to SP of £36.82 (ROI +37.6%). This can be improved further if we ignore handicaps, with 23 of the 75 runners winning (SR 30.7%) for an overall profit of £38.19 (ROI +50.9%).

If we focus on horses 10/1 or bigger Varian has managed just one win from 39 attempts.

A final side note for Varian is that he has struggled at Ascot with just 1 success from 23 in this context doubly-represented context.

 

Richard Fahey

The record of Richard Fahey with his first string runners is also interesting. Overall his figures look relatively modest – 177 winners from 1305 runners (SR 13.6%) for a loss of £265.74 (ROI -20.4%). However, when we break it down we see some big differences:

 

 

Virtually all of Fahey’s losses have occurred in handicap races. In maidens and novice events he has broken even, and from a small sample of runners in low grade sellers and claimers made a tidy profit.

Breaking the maiden data down further, focusing on Fahey runners priced 8/1 or shorter has produced 29 winners from 103 runners (SR 28.2%) for a healthy profit of £46.49 (ROI +45.1%).

Worst First String Returns

Before moving onto second strings, it is worth sharing the stats of the trainers with the worst overall returns for the first strings:

 

 

I was surprised to see Sir Michael Stoute languishing in this list; he some very poor figures indeed. Clearly the first strings of the above trainers are worth avoiding in most, if not all, circumstances.

Trainers to Note with Second String Runners

To finish off let's briefly look at trainers' second string performances. As you would expect strike rates are much lower and profits are generally hard to come by. Indeed the highest strike rate in our sample of 49 trainers is just 9.9% for Charlie Appleby, with the next best a mere 7.3% for the Gosden stable.

Messrs. Burke, Dascombe, Ivory, Dixon, Hammond and Beckett were the only trainers to make a profit on their runners, and only because of a huge priced winner here or there which skews their figures.

Some high profile trainers have very poor records with their second string runners as the line graph below shows. The blue line represents their individual strike rate and the orange line shows their return on investment (ROI%). All trainers in the graph have shown losses in excess of 33p in the £; Jamie Osborne stands the worst on that front with an 85p loss for every £1 bet. Ouch!

 

 

Trainer statistics as we know come in many forms – course stats, favourite stats, horses on debut, etc. The ones I have shared with you in this article are less well advertised. Hopefully you will find them useful either pinpointing possible bets or, just as importantly, helping to avoid poor value ones.

- Dave Renham

 

Punting Angles Using Sires & Damsires: Part 4

Looking for Punting Angles using Sires / Damsires (Article 4)

This is the fourth in a series of articles looking at sires and damdires. In this article I will dig deeper into damsires and their performances, writes Dave Renham.

Article 1 is here

Article 2 is here

Article 3 is here

Damsires are the fathers of dams (mothers) of the respective horses: the maternal grandfather is another way to understand it.

The data for this piece, as with the previous three, covers 1st January 2011 through to 31st December 2020 – ten years – and all profits/losses have been calculated to Industry Starting Price. I am using a longer time frame because certain sires now coming to the end of their stud career will still be influential as a damsire for several more years to come.

In my previous article on damsires (article 3 linked to above) I looked at some general data to begin with and then focused on a few key players in that context to try and find useful angles, both positive and negative. For the first part of this study, I am going to focus on 2yo race data.

Races involving 2yos are the types of race where pedigree research is probably used the most and can still present one punter with an edge over another. The reason punters use pedigree data in 2yo races is that 2yos have little or no form to go on, and hence they need an alternative direction or starting point.

Last time, I shared the top 25 damsires in terms of strike rate in 2yo races. This time I am going extend the list to all damsires who have had a least 200 runs (in 2yo races) – 125 damsires to be precise!

 

 

As can be seen, the strike rate varies from a top performing 18%+ to below 6% which is a significant range; hence I felt despite the ‘enormity’ of the table it was worth sharing it all. Too often when sharing horse racing data, writers focus solely on the better-performing components rather than giving a broader overall context of the subject.

Arguably one of the hardest types of race to unpick is an early season 2yo contest where most or all of the runners are yet to race. As punters we have a few pointers such as looking at the trainers and, in some of the more high profile 2yo races, there will be useful press snippets giving some quotes and possible gallops reports. Some will also look at foaling dates, how much the horse cost as a yearling, and whether it has any big future race entries. However, pedigree analysis (analysing sire and damsire data) is an integral weapon in the armoury when trying to unravel the 2yo puzzle.

So before jumping further into the 2yo damsire data let's compare the overall strike rates of 2yos on debut, on their second start, and on their third start.

 

 

As can be seen, 2yos making their debut win just under 8% of the time (7.8%), whereas this increases to just under 13% (12.9%) on their second career run, before edging down a little to 11.9% on their third career start. This means juvenile runners are roughly 1.66 times more likely to win on their second start compared with their debut. That is a stat worth keeping in mind.

2yo on debut

Time to drill down into the 2yo debut data in terms of individual damsires.

Any damsire with a strike rate considerably above the baseline figure of 7.8% is worth noting from a positive perspective; likewise any damsire with a strike rate well below the baseline is worth noting from a negative standpoint. Here are 2yo debut stats for all damsires in the time period (100 runs minimum):

 

 

Street Cry as a Damsire

Street Cry heads the list in terms of strike rate with an impressive debut winning percentage of 17.5%. The table below compares Street Cry’s damsire strike rate for 2yo debut runs through to a 4th start or more (as a 2yo).

 

 

This profile is very unusual with a much better debut record than second career run record. As you can also see, 3rd career start figures are particularly impressive with Street Cry grand-progeny scoring once from every four runs.

Reverting to 2yo debuts for horses that have Street Cry as their damsire, it should be noted they win more than twice as often over sprint trips compared with races of 7f or more:

 

 

A 26% hit rate over 5f and 6f has unsurprisingly produced a tidy profit of 28p in the £.

 

Pivotal as a Damsire

Switching to Pivotal we have a really good number of debut races to analyse – nearly 600 in fact. Pivotal proves to be very consistent as a damsire with his 2yo debutants.

 

 

There is no significant edge in any of three areas shown above.

Pivotal progeny on debut seem to act on any going but they may have a slight preference for softer turf. On soft or heavy they have won around 16.5% of the time; on good to soft through to firm they have won just under 12% of the time.

I noted previously that normally 2yo strike rate improves considerably from first to second career start. Street Cry bucked the trend and below are all of the damsires from our long list to have produced a higher debut win strike rate compared to their descendants' second 2yo run.

 

This is a small but exclusive list and, I feel, one punters should be aware of.

Of course at the other end of the scale it is useful to see which damsires produce a much higher strike rate on their second 2yo start.

 

 

These 18 damsires combined would have only lost 4p in the £ at SP if you had backed every single juvenile runner on their second career start. That amounts to over 2100 runners; I estimate that using Best Odds Guaranteed / Early Prices / the exchanges you would have made a profit of between 10p and 30p in the £.

 

2yos – second career start

We have seen some comparisons above between debut performance and second career starts. Let us next consider the impact of damsire in terms of two-year-olds' second career race. Below are the top 25 damsires in terms of strike rate on their second run as a 2yo (80 runs or more to qualify).

 

There are some very healthy strike rates and, in some cases, a decent profit to SP combined with reassuring A/E figures. The other end of the spectrum looks like this:

 

In general I would suggest that bettors should be wary of backing horses who have damsires from this list on their second 2yo start.

  

2yos – third career start

We have already seen that 2yos on their third career start win at a slightly lower strike rate than on their second start, so here are the damsires whose SR% on their third career start is at least 1.5 times higher than their SR% on their second start. I have also included their debut SR%:

 

 

These are a handful of damsires to note when their progeny have their third career start as a 2yo. Looking at the likes of Montjeu, Azamour and High Chapparal - all Group 1 winners at a mile and a half - it is probable that their grandchildren may be benefiting from stretching out to more suitable trips.

 

Individual damsires in 2yo races

To close, let us focus on ten individual damsires with associated potentially useful angles:

Acclamation – similar SR% at 5, 6 and 7f (all around the 13% mark); this drops to 5.7% at distances of a mile or more. Male runners have been more than twice as successful as female runners (16.2% versus 7.4%). Excellent strike rate of over 16% for 2yos that are racing for the fourth or subsequent times.

Averti – females (fillies) have scored 15.1% of the time compared with 9.9% for male runners. Blind profit made on 2yo second career starts of nearly 35p in the £ (SR 17.5%).

Bertolini – poor overall SR% at 7%; just 1 win from 47 on soft or heavy going; just 1 win from 56 at 1 mile or more; in 2yo maidens the strike rate drops below 4%.

Cadeaux Genereux – much better over sprint trips (5-6f) with a SR% of 14.2%; at longer trips this drops to under 8%. Slightly better on the turf to all weather but not significant; likewise males slightly outperform females but again not too significant.

Cape Cross – male runners have made a blind profit and scored 14.5% of the time compared with females at 10.9%. Higher strike rate over sprint trips (5-6f) at 14.2%; at longer trips this drops to 10.5%. 2yos that have previously raced and finished 2nd, 3rd or 4th last time out have produced an impressive SR% of 23.1% from over 250 runners. They have secured a healthy profit to SP of 26p in the £.

Dansili – 2yos with Dansili as the damsire have made a blind profit of 21p in the £ on the all weather thanks to an excellent strike rate of 16.1%. 5 of the 6 all weather tracks have overall SR%s in excess of 15%, the exception being Wolverhampton whose figure stands at just under 10%. Seems effective at all distances.

Dubawi – males have a higher SR% than females but beware of horses that have been gelded as they have won less than 5% of races they have contested. It looks best to avoid 2yos contesting 5f contests with just 7 wins from 111 (SR 6.3%); compare this to races of 7f or more where the strike rate improves to 14.9%, with a close to break-even situation (a loss of just 4p in the £ to SP).

Exceed and Excel – the strongest stat here relates to going. On good or firmer ground the SR% has been 12.6%; on good to soft or softer this drops to under 8%. One other interesting stat is that when his runners race at the same distance as LTO the strike rate hits an impressive 17.6% (compared with the overall 2yo SR% of 11.8).

Giant's Causeway – backing all 2yos would have secured a profit which is unusual. Performs best over 5 to 7f (SR 17.9%); compare this with 1 mile or more (SR 12.4%). Looks slightly more effective on firmer ground – on good or firmer the strike rate stands at 17.7%; on good to soft or softer this drops to 13%.

Royal Applause – consistent across the board. Effective on turf and all weather and on all types of going (possibly marginally better on soft/heavy). The Hannon stable have a particularly impressive record with an overall strike rate of 21.1% (23 winners from 108 runners). Over 5f they had 10 winners from 32 producing a profit to SP of £31.53 (ROI +98.5%). It seems they understand how to get the best out of Royal applause progeny.

**

This article has hopefully highlighted some useful stats and angles in relation to the influence of damsires on juvenile flat performers. I also hope I have planted the seeds that encourage readers to do further research in this area. The Geegeez Query Tool includes a 'damsire' research parameter.

- DR

 

Punting Angles Using Sires & Damsires: Part 2

Last month I started a new series of articles looking at sires and damsires, writes Dave Renham. To recap, sires are the fathers of the respective horses and can have a significant influence on their offspring; damsires are the maternal grandfathers and can also bestow certain characteristics on their daughter's progeny.

In the first article, we saw that certain sires had strong traits; for example Casamento’s runners are better suited to longer distances with his offspring twice as likely to win at 11 furlongs or further than at sprint trips of five to six furlongs.

In this second article my focus will continue to be sires and I will be sharing some additional insights looking for positive or negative angles. I will also be concentrating on two-year-old races where sire stats can be extremely useful as we have limited, or often no, horse form to go on.

This piece is not completely ‘time sensitive’ because there are some sires who have had runners in ten or more seasons and I want to analyse individuals in more detail if I can.

Record of sires in 2yo races

Below is a table of the top 20 sires of 2yos, in terms of strike rate, between 2016 and 2020 in the UK (minimum 200 runs):

Sharmadal is the only sire in profit and, sadly, he passed away last year. He should have a crop of 2yos for the 2021 season and possibly a small one for 2022. However, the first sire I wish to look at in more depth is Kodiac.

Kodiac

Kodiac, a son of Danehill, was a decent handicapper as a racehorse and went to stud in 2007 with his first runners hitting the racecourse in 2010. He holds the record for the most 2yo wins in one season and his progeny include Campanelle, Best Solution and Hello Youmzain.

I want to share Kodiac's record with juveniles in the UK going back to his first crop in 2010, firstly breaking it down by individual years:

Looking at the yearly strike rates, Kodiac has been relatively consistent with rates ranging from 10% to just over 16%. Losses overall are around 14p in the £ but, using best odds guaranteed or the exchanges would get this loss down to probably about 2-3p in the £. I now want to break the data down by level of experience (2010-2020):

Kodiac’s strike rate with his runners on debut is solid at nearly 13%. The average strike rate (SR%) on debut for all sires stands at just 7.74%, hence Kodiac progeny seem fairly well primed and ready for their first outing on a racecourse.

Horses normally improve considerably between that first career run (debut) and their second start. Kodiac’s runners are no exception, and have won over 17% of races on their second starts as a 2yo and actually made a blind profit, which is unusual. Comparing again with all sires it should be noted that backing all sires blind on their second start would lose you around 26p in the £.

My next port of call was to look at trainer records and compare their 2yo performances with Kodiac-bred runners. I have only included trainers who have had 45 or more runs:

There is a real mix here, ranging from John Gosden's 29.17% to Tim Easterby at just 2.04%. However, Clive Cox is the most interesting one for me – his overall strike rate of 1 win in 4 (25%) is impressive and he has had 16 different 2yos sired by Kodiac, 12 of which won at least once as a 2yo. That equates to 75% of these horses winning a 2yo race. Compare this to Charles Hills who has had 23 different 2yos sired by Kodiac, but only six of those proved successful in their first season (26%). To give you more context, 44.26% of Kodiac 2yos have won at least one race as a 2yo, well above the Hills figure of 26% but well below the 75% Cox figure.

We noted when looking at the yearly breakdowns that Kodiac juveniles are consistent. Indeed this consistency can be seen to best effect when examining performance on different underfoot conditions. The graph below shows the strike rate on specific goings:

The percentages range from 13% to 14.89%. So if you are backing a Kodiac two-year-old, it seems you do not need to worry about whether it will be effective on the going.

 

Kingman

I now want to move onto a new sire on the block, Kingman. Kingman was a four-time Group 1 winner when racing, winning seven of his eight career races. His only defeat came in the 2014 2000 Guineas when he finished second. It perhaps comes as no surprise, then, that as a sire he has started with a bit of bang. His stud fee in 2015 was £55,000 and, six years later, that fee has nearly tripled to £150,000.

He tops the 2016 to 2020 2yo strike rates (see first table above) and I want to examine his juvenile progeny data in more detail. While it is still relatively early days, and he does not have the large data set of a Kodiac, there are still some trends that seem to have emerged already.

Let us look first at distance. Kingman 2yos have so far displayed a distance bias to 7f more as the graph shows:

There also seems a bias in terms of male runners outperforming female runners at this early stage: we are working with quite a small data set (164 runs for males and 150 runs for females) which is why I have included each way (win and placed) stats, too, in the graph below.

 

The win figures correlate extremely well with the each way stats – at least so far.

One area where the male dominance can be seen is when we compare the record of male horses making their 2yo debut compared to females. Males seem much more mature and ready to run from the ‘get go’. There have been 72 colts or geldings sired by Kingman making their debut at two thus far, of which 20 have won (SR 27.78%) showing a profit to SP of £54.94 (ROI +76.31%). In contrast the 65 fillies making their racecourse debut as two-year-olds recorded just six wins (SR 9.23%) for a hefty SP loss of £43.33 (ROI -66.66%). The each way SR%s correlate once again with males winning/placing 64% of the time whereas the percentage for females winning/placing is under 25%.

I now want to move away from individual sires back to general observations.

Comparing 2yo debut run to 2yo second career start

When looking at Kodiac earlier in the piece, I broke his progeny performance data down by career start number. Now I am going to expand this review to all sires that appeared in the initial table by comparing strike rates with their progeny on debuts against their second runs (as a juvenile). For this I have looked at data going back to 2010:

In the final column I have divided the 2nd run strike rate by the debut run strike rate to give us a type of Impact Value. It is not a ‘true’ IV so I’ll call it a Comparison Strike Rate (CSR). The higher this figure the more improvement the runners show on their second run compared to their debut.

As we can see by looking at that final column there is quite a difference in the CSR figures in some of the sires. Frankel’s runners for example have a CSR figure of just 1.10 – of course this is partly due to his exceptional strike rate of over 21% on debut.

The sires of most interest in this table are probably those with CSR figures above 2.00, namely Acclamation, Clodovil, Due Diligence, Gutaifan, Mehmas, Muhaarar, Requinto and Toronado. You can really expect their runners to improve considerably from their juvenile debut run to their next start as a 2yo, an angle which should help in establishing value and potentially throwing up some decent betting opportunities.

 

Comparing 2yo turf runs with 2yo all weather runs

In the next table I wanted to compare turf strike rate with all weather strike rate. Again I have produced a C.S.R. figure by dividing the turf SR% by the all weather SR%.

A CSR figure of 1.00 indicates the sire is equally effective on both surfaces. Figures well above 1.00 give the edge to turf performance; figures below 1.00 suggest progeny of those sires are more effective on all weather surfaces, purely in terms of juvenile win strike rate.

Looking at either end of the spectrum will isolate differences which are significant enough to be potentially interested in. For example, Frankel’s progeny at two are clearly far better on turf than on the all weather, scoring nearly twice as often on the former. There is a logic here in that such expensive acquisitions will rarely be tried on artificial footing until they have suggested that they fare poorly on grass. Likewise, New Approach seems to be a strong influence for turf over sand. But the reverse is true when we look to the bottom of the table, at Toronado and Sea The Stars: their juvenile offspring are currently showing a clear preference to all weather surfaces.

Finally I wanted to look at some sires you might wish to consider avoiding in terms of 2yos, generally at least. Below is a list of those sires whose strike rate in the last 5 years (2016-2020) has been below 8%. Clearly it is as important to be aware of negative angles as it is of potentially positive ones.

As the first two articles in this series have hopefully shown, sire research can unearth some very useful stats and angles. Geegeez will assist any curious subscriber via both the Profiler and Query Tool.

Good luck!

- DR

Punting Angles using Sires & Damsires: Part 1

After spending the past three years on geegeez almost exclusively looking at pace angles, I am branching out into a different ‘sphere’ today, namely sires / damsires, writes Dave Renham. The plan is to write a series of articles on this topic in an attempt to give geegeez punters an edge over the general betting fraternity.

First off, a quick 101: sires are the fathers of the respective horses, and they can have a significant influence on their offspring. Damsires are the fathers of the respective mothers of the horse – maternal grandfather, if you will – and these, too, can have a bearing, though it is generally considered that this further generation influence is less strong. In this series of articles we will examine whether this is true or not and, if it is, where we ought to focus our attention.

The cost of buying a racehorse can vary greatly, from thousands of pounds to millions. Age, equine conformation (physicality) and, most importantly, pedigree (horses’ lineage / ancestry) influence the price. Normally the better the pedigree the more expensive the horse.

Let me share a human example where lineage / ancestry seems to be having a strong influence. The young American golf sisters, Nelly and Jessica Korda, are taking the LPGA tour by storm. Their father is Petr Korda, a Grand Slam tennis champion in the 90s, while their mother is Regina Rajchrtova, a top 30 tennis player back in the same era. Good ‘stock’ certainly counts there.

Returning to racing, and for this first article I will be concentrating solely on sires. The data is taken from the period 1st January 2016 through to 31st December 2020 (five full years) and all profit/loss has been calculated to Industry Starting Price. For the vast majority of the article I have used the Geegeez Query Tool.

Firstly, let us look at the sires with the highest strike rates in all races during the period of study (minimum 400 runs). I am only including sires that are likely to have a significant number of runners this season:

 

As the table clearly shows, backing sires ‘blind’ is not a great option (duh). Just one sire, Farrh, has made a profit to SP with all his runners in the past five full seasons. Obviously we should be able to beat Starting Price returns in the real world, but it does show that we have to dig a lot deeper when analysing sires. And all those of us who like to get our hands dirty in the data say amen to that!

In order to try and profit from sire data, one sound strategy is to look at individual sires in more detail to try and spot patterns, strengths and weaknesses. I am going to look at a few in that context where I have unearthed some hopefully useful angles.

Teofilo

Teofilo, a son of Galileo, won at Group 1 level twice as a 2yo and was unbeaten in that first season racing (5 from 5). Unfortunately, he got injured and never raced again. However, he has been successful as a sire and has passed on some strong traits of which we should be aware.

Unsurprisingly, perhaps, he has a good record with 2yo runners, boasting a strike rate of 16.84% during the study period. However, we can break the data down further to give us interesting comparisons, as the graph below shows:

As can be seen, male juveniles comfortably outperform females, runners win more often at 7f or more than over shorter distances, and Teofilo-sired runners much prefer the turf to the sand. Combining those factors - male 2yos over 7f or more on the turf (2016-2020) - saw 65 runners qualify with 17 winning (SR 26.15%) for a very healthy profit of £66.53 (ROI +102.35).

No Nay Never

No Nay Never is a relatively new kid on the block with 2021 being only his fourth season as a sire. As a racehorse, No Nay Never was a Group 1 winning sprinter and hence it may come as no surprise that his progeny are showing a liking for shorter distances.

Horses sired by No Nay Never win about 3 times more often over 5-6f than they do when racing over a mile or further.

Casamento

Casamento proved as a two-year-old in 2010 he was one of the best colts of his generation when finishing second in the Group 1 National Stakes before going onto win the Group 2Beresford Stakes and finally in that year the Group 1 Racing Post Trophy over a mile. As a sire his runners are typically far better suited to longer distances: his runners are twice as likely to win at 1 mile 3 furlongs or more, as compared to sprint trips of 5f to 6f. The graph below shows this neatly:

Sadly, we'll not be seeing many more of Casamento's progeny as he passed away in February 2020.

Big Bad Bob

The sire Big Bad Bob caught my eye due to some relatively unusual findings. I noticed that his record as a sire was superior when racing left-handed compared to when racing right-handed. Famously Desert Orchid was far better going right-handed than left, and we often hear trainers allude to a directional preference, so I know certain horses do have this type of trait; maybe some sires do, too. Essentially, Big Bad Bob’s strike rate when racing left-handed (around at least one bend in a race) is 1.5 times greater than when racing right-handed.

In addition to this I analysed all of his runners in more detail and found that of those that raced left-handed, 41% of them managed to win at least one race going in that direction. For all his runners that raced right handed only 19% of these managed to win a race going that way round. Now these stats may have happened by chance, but 41% versus 19% is too big a gap for me to believe that it was entirely down to luck.

Big Bad Bob also displays a distance bias similar to Casamento. The bias is not quite as strong towards longer distances but it is still significant. Horses over racing at 1m 1f or more have by far the best record.

Swiss Spirit

Swiss Spirit is a relatively new sire with 2017 seeing his first runners on the racecourse. He was a decent sprinter when he raced winning at Group 3 level and twice finishing runner up in Group 2 events. It is interesting to note, though, that as a sire his sprinters have performed no better than his 7f to 1 mile runners. In fact, in strike rate terms they have been slightly inferior. However, there is one huge deviation that is extremely interesting. That is his record with male runners compared to female runners. I think this is best illustrated in a table rather than a graph:

As you can see there is a significant disparity in strike rates and naturally this impacts the profit/loss returns. Backing all male runners blind would have lost you just under 16p in the £ to SP compared with 59p in the £ if you backed all of his female runners. The A/E values show a strong correlation, too.

 

Dawn Approach

Dawn Approach was a top notch miler during his career and as a 3yo won the 2000 Guineas and the St James’s Palace Stakes. Unbeaten as a 2yo he ended up winning 8 of his 12 career starts.

Like Swiss Spirit, Dawn Approach sired his first crop of runners to race in 2017. Also like Swiss Spirit his male runners have to date outperformed his female runners by nearly double in terms of strike rate (male win SR% 11.76%; female win SR% 6.56%). However, it is the pace angle I find most interesting.

Below is a graph comparing the win strike rate of Dawn Approach against the strike rate of all sires when looking at different run styles: front runners (leaders); horses that track the pace (prominent); and horses that race mid-division or towards the back (Mid Div / Held Up).

The progeny of Dawn Approach have been very successful when taking an early lead, but really struggle when racing from off the pace (Mid Div / Held Up). To illustrate this further I have looked at all the horses that have taken an early lead and examined their record in more detail. 65 horses have led early in at least one race and 25 of them have gone on to win at least once (38.46%). Compare this to all horses that have showed the running style of racing off the pace. Of these horses, 112 displayed this running style at least once and only 13 managed to win when racing in this way (11.60%).

Horses do have preferred running styles due to a variety of factors (some don’t like crowding for example, while others seem to thrive when racing in a pack), and hence it could make sense that certain pace traits may be passed on by individual sires.

I hope this piece has whetted your appetite for this new phase of my geegeez research sharing. In my second article I will reveal another collection of interesting data and stats. In the meantime, if you're interested in doing your own digging, both the geegeez Query Tool and the Profiler tab within the racecards offer a treasure trove of insights and are very easy to use.

- DR

Past Pace as a Predictor of Future Performance, Part 2

This is a follow up piece to the article I shared with readers earlier this month, writes Dave Renham. In that article I highlighted any horse aged four or older, that in the 2019 flat season ran at least ten times in sprint handicaps (5-6f). This gave me 303 individual horses to review from which I started to examine their individual run style data for each race they ran in 2019. This included all their races, both handicap and non-handicap, and over any distance; and it accounted for over 4,000 races.

Run style (pace) data on Geegeez is available for every single race, both flat and National Hunt, and is split into four sections:

Led – the horse or horses that take the early lead;

Prominent – horses that lay up close to the pace just behind the leader(s);

Mid Division – horses that race between the middle of the pack but in front of the rear ‘quarter’;

Held up – horses that are held up at or near the back of the field.

Points are assigned to each running style with leaders getting 4, prominent 3, mid division 2, and hold up horses 1.

My aim for the first article was to try and determine whether recent pace data was a good predictor of future run style. I think the numbers in part one proved that beyond reasonable doubt. In this article I am going to dig still deeper and share more pace stats with you.

 

Last four starts

Geegeez pace maps provide pace / running style data for each horse for up to their last four UK/Irish runs. Full career run style records can be found in the Full Form section of the cards. As I have chosen to examine horses aged four or older that have raced numerous times already in their career, the data collected always contains their pace scores from all of their previous four runs, thus the pace score totals for each horse can vary from 16 (four races where they have led early) to 4 (four races where they were held up).

Let us first look at how likely a horse was to lead if they had led early in at least one of their last four starts; comparing this with horses that didn’t lead in any of their last four starts.

 

As the graph shows there is a huge difference between the figures. Horses that have led early at least once in their last four starts, went onto lead 26.7% of the time next time out; those horses that had not led in any of their last four starts took the lead just 6.3% of the time on their next start.

It is clear therefore that a horse that has not led in any of its recent races is unlikely to lead early in its next race: approximately one horse in 16; whereas horses that have led at least once in their four previous races have a slightly better than 1-in-4 chance of leading early next time.

Let us now analyse how likely horses are to lead on their next start when we compare how frequently they led in their most recent four races.

 

I have tilted the graph horizontally just to mix things up a bit! There is essentially good correlation here – the ‘led in all 4’ percentage is slightly lower than the ‘led in 3 of last 4’, but that is probably down to the fact that the ‘all 4’ sample was relatively small and possibly slightly skewed.

All in all, horses that have led consistently in their most recent runs will lead more often than horses who have led less regularly, who in turn will lead more than horses that have not led recently.

 

Those that had led exactly once LTO

Before moving on I want to take a quick look at horses that led in just one of their last four starts, the reason being that I wanted to see if the position of that run made a difference. Here are my findings this time in tabular form:

This was a slightly disappointing set of results in truth as I was hoping to see a greater difference between the top percentage in the table and the bottom. However, there is still reasonable correlation, with those who led most recently more likely – relatively, at least – to lead again this time.

 

Horses with pace scores totalling 13 or 14 in their last four runs

When discussing running styles / pace and, in particular, when looking at the last four runs for a particular horse, it is perhaps easier to think of it in numerical terms following the 4, 3, 2, 1 points system allocated by Geegeez. I looked at horses gaining 15 or 16 points in their most recent four starts in the first article, and below are data for horses that have scored either 13 or 14 points in total. These are the possible combinations that produce 13 or 14 points.

Each set of four pace scores do not necessarily occur in the order shown above: a 4,4,4,2 pace combination, for instance, could occur in four different ways in terms of the order of pace styles in the last four races:

There is nothing mind-blowingly significant about this, I just felt it important to clarify that there are different orders of the same combination.

I wanted to understand how likely a horse with 13 or 14 points was to lead on its next start when we compare the number of 4s (number of times it led early) in its last four runs.

Horses that have led just once in their last four starts (one 4) would have any combination  of 4,3,3,3; those who have led twice (two 4s) could have either the 4,4,3,3 combination or the 4,4,3,2 combination. Different combinations of 4,4,4,2 and 4,4,4,1 would have seen a horse lead three times in their last four races (three 4s).

 

This graph illustrates what one would hope – the more 4s (early leads) in their last four runs, the more likely they are to lead in their next race. Roughly 45% of horses that had different combinations of 4,4,4,2 or 4,4,4,1 led in their next race.

 

Horses with pace scores totalling 11 or 12 in their last four runs

Next, using the same idea, we will look at total pace scores of 11 or 12 achieved in the last four races.

To save time I am not going to go through all the possible combinations of 11 and 12, although it is possible to create these totals with no 4s (e.g. 3,3,3,3), one 4 (e.g. 4,3,3,2) or two 4s (e.g. 4,4,2,2).

Again, I am looking to see how likely a horse with these points totals was to lead on their next start when comparing the number of 4s in their last four runs. First let us look at the data simply comparing zero 4s in the last four runs to at least one 4:

There is a significant difference here for horses with an 11 or 12 points pace total. Horses that had led at least once are far more likely to lead next time when compared with horses that have failed to lead in any of their last four starts. Now let’s compare zero 4s with one 4 and with two 4s:

 

Horses with 11 or 12 points go on to lead next time 27.7% of the time if they have led in 2 of those last four starts (two 4s). In turn those who led once (one 4) go onto lead 17.7% of the time. As we know from the previous table those who have not led in any of their last four starts (zero 4s) have gone onto lead 11.4%.

This is yet another clear example that more 4s in recent runs really does positively impact the chances of a horse leading next time.

 

Horses with pace scores totalling 9 or 10 in their last four runs

Here is a table comparing zero 4s versus one or more 4s for horses with pace totals or 9 or 10. For the record there is only one combination where two 4s would occur with a score of 10 (4,4,1,1), and it is not possible with a score of 9.

Once again the number of 4s in the last four starts does make a difference in terms of the chance of the horse leading next time out. The more 4s, the more likely they will lead again.

 

Last six runs

To finish I wanted to dig a little bit deeper still and look at the last six runs rather than the last four. What I have done is to create pace averages over those six runs. Again the maximum average would be 4 (six 4s) and the minimum average 1 (six 1s). I have split the averages into groups to see if the horses with higher averages are more likely to lead next time than lower ones. Here are my findings:

This table shows perfectly what I had hoped it would: horses with the highest pace averages over the last six runs lead more often than the rest, with excellent correlation between the decreasing averages and the decreasing percentages.

I further calculated the average pace figure for each group on their next start. In other words I added up all their pace scores on the next start and divided by the number of races/runs. Again we have excellent correlation as this graph shows:

Horses that have a pace average of 3.50 to 4.00 for their last six starts have produced a pace average of 3.26 on their next start. Those averaging 1.00 to 1.49 yield a much lower next time out average of just 1.53. Again, there is excellent correlation between the latest six-run pace average and running/pace style next time out.

 

Summary

In this article I have focused on the pre-race prospects of finding the percentage chance of horses that will lead early. The rationale is, I hope, obvious: we already know that such horses have the potential to secure us a profit if we can consistently predict which one is going to take the early lead in a sprint handicap. However, the final table, below, looks at the chance of being held up next time using our last six race pace averages, just to prove this approach helps us to predict hold up horses, too!

The table again correlates beautifully, this time in reverse, with the lowest six race pace averages having by far the highest percentage of hold up horses next time.

As we know, Geegeez provides the last four pace figures with a last four race average; for those keen to dig further, using the last six races (found in a horse’s Full Form) seems to work equally well.

As a final note, below is a 'cut out and keep' reference to the four-race data in these two articles which should prove very useful for those who bet in older horse sprint handicaps.

And finally finally, the percentage chance of each run style based on a horse's last four pace scores and the number of times it led:

I hope you'll find that useful.

- DR

Past Pace as a Predictor of Future Performance

As regular readers will be fully aware, I have a huge interest in pace and the potential biases they can create, writes Dave Renham. Hence 2021 kicks off with another article examining this pivotal aspect. The research for this piece has been a bit of a labour of love which began with me collating a huge amount of data while looking for predictive patterns around run style.

Firstly, I highlighted any horse aged four or older, that in the 2019 flat season ran at least ten times in sprint handicaps (5-6f). I wanted to avoid younger horses as they were less likely to have developed a running / pace style. That gave me 303 horses from which to analyse individually. I then took these horses and gathered their individual pace data for each race in which they competed in 2019. This included all of their races, both handicap and non-handicap, and at any distance. Having said that, over 91% of all races were still 5f or 6f sprints with the vast majority handicaps. This totalled roughly 4300 individual pace scores (!) which is a decent sample to study.

To recap, you can get run style data on Geegeez, and this is split into four sections - Led, Prominent, Mid Division and Held Up. Here is a quick explanation of which type of horse fits which type of pace profile:

Led – horses that lead early, usually within the first furlong or so; or horses that dispute or vie for the early lead;

Prominent – horses that lay up close to the pace just behind the leader(s);

Mid Division – horses that race in the middle of the pack but in front of the rear ‘quarter’;

Held up – horses that are held up at, or near, the back of the field.

Geegeez also assigns points in regard to which position they took up early in the race. Leaders get 4, prominent runners 3, horses that ran mid-division 2, and those held up score 1.

My aim with this data crunching was to see how relevant recent pace data is in terms of predicting future pace. I have touched upon this in a couple of previous articles, but I wanted to go into far more detail here. The reason pace prediction interests me so much is that I know that front runners have such a huge edge in sprint handicaps. Indeed, in 2019, if you had been able to predict pre-race the early leader or leaders in 5-6f handicaps in the UK you would made a profit to SP of £5700 to £10 level stakes. That equates to around 35p profit in the £.

At this point it is important to say that we have to be careful how we compare, for instance, last time out (LTO) hold up performances with LTO front running performances; the problem is that in each race there are always more hold up horses than early leaders, so we need to account for that in any comparisons made. Having said that, hopefully how I present the data will make sense and, more importantly, be ‘fair’.

 

Horses that led early last time out

My first port of call was to look at horses that had led early LTO and to see what running style they showed in their next race. There are two columns in the bar chart which I will explain underneath.

 

 

The orange columns show the percentage of horses to show that particular running/pace style in all of the races in this study. Hence leaders accounted for 14% of all runners, prominent racers for around 39% and so on. This is our ‘control group’ data if you like.

The blue columns in the bar chart show the percentage of horses that displayed that particular running/pace style after having led early LTO.

As the blue columns show, LTO leaders are much more likely to lead next time compared with the ‘norm’ (control group data). Just under 35% of LTO leaders led again in their next race. This figure is around two and a half times larger than the overall base figure of 14%, and implies that a LTO running style can be highly significant. In addition, it was noted that more than three quarters, 77%, of last day leaders either led or raced prominently next time compared with only 23% that raced in midfield or in rear.

 

Horses that were held up early last time out

It is always best to look at the extremes, so I’m moving from LTO front runners to LTO hold up horses.

This next graph is set up in the same way with the orange columns showing the percentage of horses which displayed that particular running/pace style in all races (our control group). The blue columns this time show the percentage of horses that showed that particular running/pace style after been held up LTO.

 

 

This picture is almost a complete reverse of our first graph, as one might hope. Over 45% of horses that were held up LTO showed that same running style in their next race. As you can also see it is very rare for LTO hold up horses to lead early next time. Just 4.8%, less than one in twenty, of hold up horses in this exposed handicapper sample have gone on to lead next time out.

I think it is useful to compare the two sets of figures now without the control group data (orange column). So the graph below compares early leaders LTO (in green) with hold up horses LTO (in red), and their subsequent run in terms of pace / running style. It shows the massive difference between the two:

 

 

Clearly LTO running style, whether it be a front-running preference or a hold up one, clearly does influence the next run. Indeed, this graph shows us that it is seven times more likely that a horse will lead if it led LTO compared with one that was held up LTO. Likewise, it is around 4.5 times more likely that a horse will be held up if was held up LTO as opposed to one which led last time.

 

Horses that raced prominently last time out

Moving on to those that raced close to the pace LTO and their subsequent next run. Again I have reinstated the overall ‘control group’ data (orange) as our comparison.

 

 

There is a more even looking graph this time, although LTO prominent racers are more likely to race front half of the pack rather than back half in their next race. (Led/Prominent running styles occurred 62.3% in their next race versus Mid Div/Held Up on 37.7%).

 

Horses that raced mid division last time out

With last day midfield run styles, we also see a more even looking percentage comparison. However, only 9% of horses that raced mid division LTO went onto to lead next time compared with our base figure of 14.1% for all races. This is worth noting on what can be considered a meaningful sample size.

 

 

Comparison of LTO data for horses that took the early lead

I’d now like to combine the data for all horses that led early and compare the chance of it occurring in relation to their most recent run style. We have seen this individually on the four orange/blue graphs, but it is useful to see the comparison on just one graph. The figures on the left axis are, as previously, percentage chances of leading.

 

 

This neatly shows the importance of the LTO running style in relation to the next race, especially as there is a lovely correlating sliding scale. LTO leaders (LL) led next time more than twice as often as those who raced prominently (PL) last time; and they in turn led nearly twice as often as those that race mid division (ML) last time; and last day midfielders led almost twice as often as those held up (HL) last time.

 

Comparison of LTO data for horses that were held up

Comparing the hold up horses’ data in the same way, we see the same type of correlation, but in reverse, if you like.

 

 

The LTO running style is a key marker yet again. Horses are far more likely to be held up if they were held up LTO (HH). Likewise, horses that raced mid division LTO are more likely to be held up than those that raced prominently LTO. Finally, only about one in ten of LTO leaders are held up in their next race (LH), quite often when they inadvertently miss the break.

 

Horses that led early in both of their last two starts

I wanted to go a step further and review those horses that had led in both of their previous two races to see which running style they assumed on their next run. Again I will show the comparison with the overall pace data for all races (our control group in orange):

 

 

As the graphs indicate (blue bar on the far right), nearly 45% of horses that led in both of their previous two starts led again next time. In fact, fully 86% of them led or raced prominently in that follow up race.

We have already seen that one LTO run in terms of running style/pace is a good indicator of what will happen next time out. This data seems to show that the last two runs combined are an even better indicator (which is what would be hoped, of course). This is hugely significant and shows why you should start to take note of race pace data here on geegeez.co.uk if you haven’t already.

 

Horses that were held up in both of their last two starts

To the other extreme, and horses that were held up on both of their last two starts. The hypothesis is the reverse of the previous graph with the highest blue bar on left (highest percentage for hold up horses) and the lowest on the right (for leaders). Here are the data:

 

 

We see precisely the type of result that we had forecast. Over 57% of horses that were held up off the pace in both of their last two runs were held up again. Just 2.7% of them went onto lead next time out. Again it is useful to compare each individual blue bar with its orange neighbour (the control group). It helps to show that even though more horses raced prominently next time than raced mid division (21% v 19%), in reality prominent racers were well down on their overall figure of 38.7%.

 

Performance based on pace score of last four runs

For each race on the geegeez.co.uk pace maps, we are presented with the pace figures/running styles for up to the last four UK/Irish races (users may look at the longer-term run styles via the ‘RS’ column in Full Form. The racecard also provides a total of those last four runs. The maximum score is 16 (last four races saw the horse lead each time) while the minimum is 4 (last four races saw the horse held up each time).

In my study I have over 3000 sets of 4 consecutive races for individual horses. Hence this is a huge sample under analysis. In the table below I have collated the percentage chance of a specific running style occurring in conjunction with all of the last 4 race pace totals between 4 and 16 inclusive. Hence we are expecting to see horses that have a pace total of 4 being far more likely to be held up in their next race as compared with hold up horses, for example.

Similarly, horses scoring 16 points in their last 4 runs, we are hoping to see many more leaders next time as compared with hold up horses.

Here is the output:

 

 

The figures in the table correlate strongly.

For example, a total pace score of 4 (held up in the last four races) has seen almost two-thirds of these horses being held up again next time. Compare that with a paltry 1.4% of horses that have gone on to lead next time.

At the other end of the scale, horses with a total pace score of 15 or 16 went on to lead in their next race almost 45% of the time, with only one in twenty of them being held up.

This table is a powerful recommendation for using past run style data for the basis of your pace prediction. It is impossible to accurately predict what running style every horse will show in every race but using the Geegeez data gives you a huge advantage over the wagering crowd. If you carefully choose specific races, such as older horse sprint handicaps, this will also increase your chances of successful prediction.

 

An Example: Pace Edge in Action

To finish, here is the type of race we really want to be looking for:

 

 

This was a 6f handicap race at Catterick in October. Only one horse had a pace total in double figures, Dirchill, with a decent score of 14 as well as leading in both of his last two starts.

He was five points clear of the next runner, which is a huge margin, and when examining the last four races of his eight rivals, 27 of those 32 races had seen them display either a hold up style or a midfield one. Also the historical Catterick 6f stats strongly favour pace setters over mid div/hold up types (see the green and red blobs at the top of the image).

 

The result is shown below:

 

Dirchill made all the running to score at the tasty odds of 15/2.

Running Well Against a Pace Bias, Part 2

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

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

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

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

 

RACE 6 - 4th July – 4:55 Epsom

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

 

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

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

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

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

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

 

RACE 7 - 5th July – 3:15 Haydock

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

 

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

 

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

 

RACE 8 - 8th July – 8:40 Newbury

Newbury next and a long distance handicap.

 

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

 

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

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

 

RACE 9 - 17th July – 12:35 Beverley

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

 

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

 

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

 

RACE 10 - 17th July – 3:40 Beverley

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

 

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

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

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

 

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

**

Putting ‘Negative Pace Bias’ to work for you

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

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

 

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

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

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

Running Well Against a Pace Bias, Part 1

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

RACE 2 - 16th June – 4:40 Ascot

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

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

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

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

RACE 3 - 17th June – 2:25 Ascot

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

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

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

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

 

RACE 4 - 18th June – 2:25 Ascot

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

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

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

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

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

RACE 5 - 20th June – 4:10 Ascot

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

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

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

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

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

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

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

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

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

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

*

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

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

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

- DR

 

Pace Analysis in Action: A See-Saw Day

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

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

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

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

 

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

 

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

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

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

 

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

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

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

What happened in the actual race?

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

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

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

 

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

 

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

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

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

What happened in the actual race?

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

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

 

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

 

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

What happened in the actual race?

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

Conclusion

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

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

 

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

 

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

 

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

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

What happened in the actual race?

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

Conclusion

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

*

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

- DR

Hexham Racecourse Pace Bias

In this third instalment looking at pace biases at National Hunt courses, we will look at the picturesque Northumberland track at Hexham, writes Dave Renham.

When discussing the word pace my main focus is the initial pace in a race and position the horses take up early on. Some pundits talk about the running style of a horse: this is essentially the same thing.

The Pace Analyser and Query Tool on geegeez.co.uk are places where you can research pace / running styles to your heart’s content.

Pace data on the site is split into four – Led (4), Prominent (3), Mid Division (2) and Held Up (1). The numbers in brackets are the pace scores that are assigned to each section.

For this article I am again concentrating on data going back to 2009 with races of eight or more runners. My main focus when looking at pace will as always be handicap races, but for National Hunt racing if the non-handicap data indicates any biases I will share those data also. Hexham is the course in focus today.

The course is left-handed and a mile and a half in circumference and is considered to be severe and undulating. The hurdle course is shown below:

 

 

As can be seen there are six flights in total, three each in both the back straight and the home straight. The chase course has ten fences in its circuit and a separate home straight with a single fence to navigate.

 

 

Hexham Hurdle Pace Bias

They run over three main distances in hurdles races at Hexham, namely 2m, 2m 4f, and 2m 7½f.

Hexham 2m Hurdle Pace Bias

Here is the handicap hurdle breakdown (8+ runners):

 

There is a marginal advantage for front runners but in general this is a fairly even playing field in terms of early pace. The each way placed percentages are often an area I look at, and the graph below helps demonstrate how even the splits are here. The held up figure is lower but not significantly so.

That said, front runners have an Impact Value of 1.47 which implies they are almost one-and-a-half times as likely to win.

It is also worth sharing the non-handicap data at this trip as there does seem to be a pace bias:

 

There has been a definite advantage to those horses that have led or raced close to the pace (prominent). Quite often the reason for this is the fact that some non-handicap races can be rather uncompetitive, especially novice events. Having said that, these stats are strong and with good correlation between strike rates (both win and each way).

 

Hexham 2m4f Hurdle Pace Bias

In the past few years they often move the rail so the distance here can change a little from the advertised two and a half miles. The handicap hurdle breakdown with eight or more runners over this trip looks thus:

 

If there is an advantage, it is towards prominent racers but, unlike the shorter trip, there seems little in it from a pace perspective.

However, when we dig deeper into ground conditions it looks as if there could be a pace bias against front runners as the going eases. On good to soft or softer, front runners have secured just one win from 35 runners: this equates to a very low win strike rate of under 3% and poor A/E and IV values of 0.35 and 0.31 respectively.

 

Hexham 3m Hurdle Pace Bias

The handicap hurdle data over this longer trip looks like this:

 

We see that front runners and prominent racers have a clearly superior record here with a good correlation across all stats. If you had managed to predict the front runner in each three-mile handicap hurdle here since 2009 you would have been rewarded with excellent profits both for win and each way wagers. Easier said than done, of course!

Below is a graphical representation comparing strike rates (win & ew) for each pace figure over this trip which emphasises the positive correlation:

 

Before moving onto chases, it should be noted that this front-running edge seems to strengthen on better ground, whereas prominent runners fare much the best when it is more testing.

On good ground or firmer, front runners have won nine races from 43 (SR 20.9%) with a strong A/E value of 1.89 (IV 2.43).

Whereas on good to soft or softer, those close up but off the lead won 16 races from 102 runners (SR 15.7%) with an IV of 1.56 and a level stakes profit of +25.64.

 *

Hexham Chase Pace Bias

Over the bigger obstacles at Hexham they primarily race at the following three trips - 2m , 2m 4f and 3m. There is one race each year over the marathon four-mile trip, too.

Hexham 2m Chase Pace Bias

Up until 2015, they officially raced over 2 miles ½ furlong so I have grouped the data together. There have been 40 qualifying races (8+ runner handicap chases):

 

Wow!

This is one of the strongest National Hunt pace biases in the country; not only do front runners enjoy a huge edge, but horses that race in the second half of the field early have a quite dreadful record. The pie chart below gives a powerful pictorial representation of the bias (it shows % of races won by each pace section):

 

Good luck if you're backing a patiently-ridden horse in a Hexham two-mile handicap chase!

When the going is on the soft side, the message is even more stark, as if that was even possible:

 

Hexham 2m4f Chase Pace Bias

There have been a decent number of handicap chases with eight or more runners over this trip (59 races in total). Here are the stats:

 

Another very solid bias to front runners who again show a clear edge. It is not as strong as the shorter distance but still extremely significant. Prominent runners also have a reasonable record while hold up horses have at least been more competitive than they were over the shorter trip.

 

Hexham 3m Chase Pace Bias

Up until 2015 they officially raced over 3m1f as well and I have incorporated those stats with the three-mile figures. The handicap pace splits are as follows (8 + runners):

 

This longer trip still readily favours pace horses but the strength of bias against those that are waited with is not as strong as over the two shorter distances.

 

Hexham 4m Chase Pace Bias

There have been only eight handicap races over four miles and the data is far too limited to dig into.

**

Hexham National Hunt Pace Bias Summary

In conclusion, the running style bias towards those leading and/or racing prominently at Hexham is far stronger in handicap chases than it is in handicap hurdles. Here is one final graph comparing win and each way strike rates between front-runners and hold up horses in handicap chases over the three different distances:

 

The graph beautifully illustrates that

a) the front-running bias is strong across the board,

b) the pace bias does diminish a little as the distance increases; and,

c) front-runners have a significant edge over hold up horses regardless of distance.

Hexham is definitely a course to keep an eye on from a pace perspective.

 

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