For a while now I have been planning to add a new kind of rating to my bayesian system. Something that I have now named suitability score.
Previously I have calculated strike rate for class, course and distance. Similarly to what is presented in the Instant Expert portion of the race cards at Geegeez. But I have had a feeling that it is a bit harsh and haven’t added it as one of the factors calculated into my odds.
After reading Peter Mays forecasting book I realized that I wanted to create something to measure if run was successfull regardless if the horse won or not. From May’s book I ripped the concept of distance beaten in pounds (and conversion from lengths lost to pounds).
I looked through the races ran in 2013 and decided on a bit different parameters on what to consider a good run and what constitutes a bad run. I ended up with values where roughly 40% of runs are deemed good, 50% ok and 10% bad.
While figuring that out I was also bouncing out ideas on how to use these as a factor in my system. First and easiest would be to just calculate strikerates but I wasn’t happy with that when I effectively had three possbile outcomes for a race, good, ok and bad. In the end as a first version I decided steal a concept of Net Promoter Score, or NPS.
I will calculate suitability score as follows:
((Good runs / All runs) – (Bad runs / All runs)) * 100
This gives me a score between -100 and 100.
Once I have calculated bunch of these and done some analysis I will post a followup.