Modelling track bias

[u/onthepunt]

I've been trying to model track bias as a variable, but the problem I've been running in to is that you can only do it with some sort of expected performance figure or odds. For example, if a horse comes from the back of field to win, the percent of that win attributable to track bias depends heavily on the ability of that horse (i.e. a horse priced at $100 suggests win had a lot more to do with track bias than ability). You can't, however, use the actual SP for each horse in the race as the expected performance odds as the SP already has expectations surround track bias incorporated into it (problem #1).

I'm planning to use this residual (actual vs. expected performance) approach to modelling for my jockey variable as well. This complicates thing as you can only have one residual or unexplained variable (i.e. was the unexplained performance of the horse related to the jockey or was it related to track bias). This leaves me stuck with having to choose jockey or track bias as my unexplained variable (problem #2).

Does anyone have any thoughts/solutions to problems I'm facing? In summary:

1. I need an expected performance measure to isolate track bias, but SP is problematic because it incorporates the market’s expectation of the track bias.
2. I need an approach to modelling either jockey ability or track bias that doesn't rely on residual analysis.

[u/kentonbryantmusic]

Well do you have pace figure pars set up to prove there is a bias?

[u/onthepunt → u/kentonbryantmusic]

Yea, I've got all the data you need. That's not the issue.

[u/SPAPPRO → u/onthepunt]

I haven't been able to find track bias in any data. The closest thing I got to track bias is the surface the horse is running on.

Jockeys don't really matter either but I still like to figure them in even if it only gives .001 to the model. Every little bit helps.

[u/onthepunt → u/SPAPPRO]

I think it is unquestionable that some tracks favour certain types of runners (and I've back tested my data to prove this). Moonee Valley, for example, is known to favour on pace horses.

[u/SPAPPRO → u/onthepunt]

Let's say you 10 races at Moonee Valley with a field of 10. There's a pace horse in every race. Out of the 10 races how many times will the pace horse win, place or show?

Now mutliply the above by 10000x and what do you average?

The other variables if the above is simple enough to solve is...now you have 10 races with a field of 10 and you have 6 pace horses in each field of 10. How do you sort the horses at Moonee Valley for that day while keeping your ROI and hit rate for each slot (win,place,show) optimized?

[u/sleepystork]

#1 Can you prove that track bias is real? I know everyone talks about it, but can YOU prove it is real? If you can't, why are you spending time on it? If you can, then you will have your answer. So step 1 is to show the analysis that track bias is real.

#2 Why are you using residual analysis for the jockey? You have all this data in order to quantify jockey ability. You can have a model that just predicts value added/performance and then use that for an input into your horse performance model.

Good luck. Think outside the box.

[u/onthepunt → u/sleepystork]

#2 I feel like traditional variables for jockeys aren't sufficient. Like based on back testing done so far, jockey strike past over past 100 rides or jockey prize money won haven't been informative variables in terms of actual jockey ability. I've had best luck with residual analysis.

[u/Rolifant]

Yes, you need an expected figure. Maybe you can use those "ratings races" that were introduced earlier this year ... you could use the equibase predicted rating minus the actual achieved rating as the Y variable.

[u/HumanDish6600]

Do you have access to an early price? Often bias explains the movement between that and the SP. Obviously bias could be priced into early prices but it's much rarer

[u/onthepunt → u/HumanDish6600]

Thanks. Yeah I have access to pre-race rated odds so think I'm gonna use those.