Neural Network Diary #3: Thoughts about inputs and ratings

Recently I have been thinking about inputs that would use in the neural network and as mentioned earlier, most will come from Racing Dossier-service. I don’t wan’t to include too many but then again not too few either. Currently I am planning to include following list of ratings.

  • Shorpro – Projected speed rating in todays race
  • SpdfigLR – Speed rating in last race
  • SHorAvD – Average speed rating at todays race distance
  • PFP – Current form class level of horse, this rating starts at 1500
  • MClSLr – Money Class Shift From Last Race. Prize money of todays race divided by prize money of last race. Anything greater than 1.07 is a shift up in class, anything less than .93 is a drop in class.
  • Raiform – Rating assessing last three races
  • Course, Distance or Course/Distance winner

I am still thinking that I might add something measuring how succesfull horse has been when it comes to pricemoney.

Originally I was planning on normalising ratings but that was before I came up with that list and now that I think of it, I might just as well use them as they are and dividing with suitably big number to bring them to less than one. Money Class shift and Course/Distance winner I am putting in as boolean values.

Only problem with that is the fact that speed figures above can be less than zero, I need to find a way to handle that.