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Track Tracts
Handicapping With Trainer Stats
by Gordon Pine
I spent a year in the 1980s handicapping with pretty much nothing but
trainer stats. I came out of that year a little poorer and a little wiser, as is often
the case with horseplayers. I still use trainer stats in a supporting role. And there are a few things I learned during that year-long losing streak.
Handicapping with trainer stats is rife with contradictory
subcategories. Here’s a case in point from the first race at Hollywood Park
on Wednesday, July 11: John Sadler, the trainer of Asking Bid, has won 16 of 55 or 29% of his races with horses in the second race after a layoff, for a 1.77 ROI. Good positive stat, huh? All you’ve got to see is that 77 cents profit - sign me up! But if you look further, you see that John Sadler and Chance Rollins, the rider on Asking Bid, have an abysmal 1/17, 6%, 0.21 ROI record.
What to do? You’ve got contradictory subcategories. It’s amazing how many
treatises you can read about trainer stats without hearing a peep about them. That brings me to my second point:
As Ron Ambrose used to say, positives outweigh negatives. All else
being equal, if you’ve got a negative subcategory and a positive subcategory on the same horse, discount the negative and pay attention to the positive. Why is this true? The random chance of a horse winning is about 12%, given an average field size of about 8 horses. A low win% trainer stat like Sadler and Rollins 1/17, 6% record fits much more easily under the bell curve of normal performance than the 16/55, 29% positive trainer stat. The positive trainer stat is much more statistically significant. By pure happenstance, this brings me to my third point.
Small negative trainer stats are almost meaningless. I remember going to seminars where guys would quote stats like, "this horse is 0 for 7 the second time off a layoff," as if that was a justification for throwing him out. Frankly, it don’t mean a thing. Going 0 for 7 or 1 for 17 is well within the normal range of outcomes. Maybe one of Sadler/Rollins losing horses came in second by a nose - if their head bobs had gone the other way, they’d have a perfectly normal 2/17, 11% stat. Never throw out a horse because of a bad stat when the sample size is less than 20. I don’t give negative stats much credence until there are at least 30 races in the sample, and even then I take them with a large grain of salt.
I’ll continue with some more points about handicapping with trainer
stats next week. There are several cappers posting on The
Grandstand who use trainer stats as a major part of their handicapping, in, no doubt, a profitable way. I’m sure we could learn some things from them, and I hope they’ll share a few nuggets.
NC
Copyright ©2001 NetCapper Inc. All rights reserved
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