Getting from (golf) raw data to rating to prediction %

[Pompano]

Hi,

I've been spending some time on compiling a database over past results (US and European tours since 1995), Betfair historical data (all tournaments/markets the last two years to start with = ~12000 bets/month on average) as well as retrieving current odds via Betfair free API. Now I need to start working on actually doing something with all this data :)

So I have two requests:

1)

I'm looking for help and/or resources on how to creating a model for, I guess, normalizing different types of data so it can be compared player vs player. The result would be some sort of power rating.

(something like the Sagarin index http://www.golfweekrankings.com/template/default.asp?t=world which I guess I would rip if it had been published in its total, which AFAIK it hasn't)

I have this (partial) example mockup data:

Player 1

Avg scoring 69.3

Putting GIR 1.73

Top 10s 2

Player 2

Avg scoring 68.5

Putting GIR 1.81

Top 10s 4

Player 3

Avg scoring 71.5

Putting GIR 1.89

Top 10s 0

I've made a rough outline in Excel of a starting point on the weight of each data type (adjusted average scoring, driving total, course form etc iterated over categories all/last30/last10/last3/last). But how is the model/math from going from above data to:

Player 1

Rating 91/100

Player 2

Rating 93/100

Player 2

Rating 86/100

2)

Given that you have this rating, the next step is to translate this into probabilities. So how do I get from 91 vs. 93 rating to 65%/35% win probabilities in a head to head situation. (or in another case, 50 players ratings into outright win probabilities)

With this I intend to create a system for running the model many times, with different weight parameters, against historical odds and results to see if I could've found value in the past. If so I should be able to find +EV spots in the future (I hope) If not, at least I learned a ton of Office, C#, SOAP, SQL Server and LINQ programming :)

Any help on these matters would be appreciated. //pompano

[Lechero79]

Re: Getting from (golf) raw data to rating to prediction % This interests me a lot, as I love playing with numbers to try to create ratings. I've basically done a similar thing to what you're attempting in my football system thread... An example of how you'd get the raw statistics to a player rating could be as follows:- If, for example, the 3 relevant stats were average score/round, putting stats and top 10's, you could weight each statistic for it's usefulness and then combine them into a score of 100. For example - if you thought average score/round was most important, putting second and top 10's third, you could give each respective statistic a different weighting, such as 45/30/25. Then, you could have every golfer in different excel spreadsheets sorted by best score (for each area) and give them a rating for that statistic - e.g top 5 players 45, next 5 players 43, etc... As regards your second point, this is something that I am finding tough with my model. I get round it by comparing a long list of match ratings to a long list of prices and then picking out potential bets through rating/pricing discrepancies. If you read gingertipsters' thread in Horse Racing forum about creating a 100% book, this may help. But it's quite a difficult proposition and I think you will have to accept that you will get things wrong possibly to start with. Good luck, and if you want to know anything more, I'll help if I can!