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Trainer Pace Ratings
Is there a link to more successful trainers using past “in running” data?
by David Renham
In this article I am going to look to see if there is a link between more successful trainers and early pace shown in a race. The data has been taken from March 29th 2007 - May 31st 2010 and I have concentrated on 2yo non handicaps.
I have created pace averages for each trainer. Pace averages have been calculated by using “in running” comments from the Racing Press. Horses that “made all”; “led” early in the race get a maximum of 5 points; horses that raced at the back early or are held up nearer the back of the field than the front score 1.5. Other comments that suggest the horses tracked the pace or chased leaders etc score between 1.5 and 5. There are so many different comments that I won’t bore you with what all different comments score. Suffice to say that all of the trainers’ runners have been averaged to give each trainer a “pace average”. My theory is that trainers with the highest pace averages will prove the most successful in terms of strike rate and returns than those with lower ones.
I have listed the trainers in order of pace average with the left column showing the top half of the trainers and the right column showing the bottom half. I have only considered trainers that have had at least 60 runners in 2yo non handicaps during the period of study (see fig 1).
As you can see Mark Johnston tops the list which probably will come as no surprise to most punters. He likes to see most of his runners race up with, or close to the pace. Indeed Mark Johnston’s horses that have led early in 2yo non handicaps have gone onto win the race around 31% of the time. “In running” punters should take note, although of course it is not an exact science picking which of his 2yo runners will lead! However, I certainly would consider backing any of his runners that lead early “in running” assuming the price I get is close enough to Betfair SP. If the price has contracted too much early in the race then it is arguably best to leave alone.
My next task was to group the trainers by pace average to see if those with the higher pace averages produced a better strike rate. Here is the data (fig 2):
Essentially the pattern is as I had expected/hoped – those trainers with the highest pace averages have been the most successful, scoring in 14.4% of races. Compare this to the bottom two groups (pace average 2.59 and below) where their win% is only half that at just over 7%.
So far so good. I now moved on to look at returns to see if the returns correlated with the strike rates:
I am pleased to say that the returns data correlates with the strike rate data. The higher the pace average the better the returns. It definitely seems that trainers with pace averages of 2.59 and below look worth avoiding.
Next I decided to rate individual races to see if a real edge can be gained. With the main data having been taken up to the end of May 2020, I decided to look at 100 races in June 2010 and simply rated them by using the trainer pace averages. The highest trainer pace average in the race would simply be top rated; the second highest trainer average would be second top rated and so on. This is what I found:
The -11.6% ROI figure for the top three rated is very similar to the ‘3.00 and above’ average pace figure of -11.8%.
These results were encouraging for such a ‘basic’ rating system using trainer pace averages. Indeed, the results to Betfair SP saw an 11.6% loss turned into a 7.6% profit.
Is this an area that requires further research? I certainly believe so and hence I will be working hard to improve these trainer pace ratings in the future.
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