Raiform – A new rating
I have been adding new stuff to my bayesian system recently as well as adjusting criterias for ratings.
One new piece of information I have added I call Raiform. I need to call these something in my database and Racealyst AI Form or Raiform for short sounds fancy enough 🙂
Anyway, it is neural network derived rating which combines horses three last finish positions adjusted for number of runners and under the same code as todays run, days since last run and horses age together with information on if race is flat or jumps and if it is handicap race or not. Idea for the rating is from set of ratings Smartsig ran years back called AI form. That rating used also horses sex but for some reason I haven’t deemed that information important enough to include in my database so I have to live without it. I don’t know how people at Smartsig arrived at their ratings but I wanted to do something similar as I felt that just looking at the days since last run or days sincle last good run was not giving out relevant information.
Below is a chart which shows how rating would have performed in 2014. Line is strikerate and bars show return on turnover %. As I expected, ROT is all over the place but strikerate holds a nice upwards trend without plummeting at any point.
Interestingly rating range from 125 to 150 has a return on turnover of over 15% for over 16 thousand selections and strikerate of roughly 11%.