Like games - matching routine

This post deals with how to identify the set of games most like today’s game. I have written a routine that will do that. When first encountered for a sport, the history files for that sport are read and an internal table is built. The internal table contains the expected scores for each team (computed from the spread and total) and the final score for the game. (Note: these are big tables, 2,854 games for the NFL and 7,823 games for CFB.)

The calling code supplies 3 variables, the 2 expected scores for today’s game and the minimum number of games desired. The routine then passes every entry in the table computing the distance between today’s game and the past game for that entry. Remember, consider each pair of expected scores can be considered a point on a X/Y graph. The distance is computed as the square root of the sum of the respective difference in the scores squared.  If this is reminiscent of the Pythagorean theory, there is a good reason for that.

These distances are saved in another array, which is sorted by increasing distance from today’s game. Finally, the minimum number of desired games (plus distance ties) are returned to the calling code. Then for any potential wager, these set of actual scores can be counted, percentages calculated, and expected return computed.

I hope this is a clear explanation of what occurs. If not, feel free to ask a question on this blog, Email at ole44bill.gmail.com, or in the “Handicapper Think Tank” forum of www.sportsbookreview.com under the topic “Like game system”. My next post will deal with the question of how to determine what a good minimum number of games is. I’ll tweet on Twitter, ole44bill, when I post it.