I've a golf website that pulls a load of statistical data and makes forecasts for upcoming events.

I'm trying to improve the algorithm and have been looking into Azure's ML Studio. I've lots of data about previous events and stats the competing golfers had and the time of the event so I'm confident I need to be using some sort of regression based algorithm but I'm not sure which one, there's a few that look appropriate?

Any advice would be greatly appreciated! Thanks

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  • $\begingroup$ I don't know the first thing about golf so I don't want to recommend a generic recipe, but here's the Economist's approach (update). I'd use that as a starting point. What about the upcoming event exactly do you want to forecast? $\endgroup$
    – Emre
    Jun 29, 2017 at 3:04
  • $\begingroup$ Where the players are likely to finish! $\endgroup$
    – Jimmy
    Jun 29, 2017 at 3:14
  • $\begingroup$ Damn it economist get off my turf! lol $\endgroup$
    – Jimmy
    Jun 29, 2017 at 3:18

1 Answer 1


If I had to choose, it would be one of the last three as they are more sophisticated. If you have some time, try them all out, sweep the hyperparameters, and compare the results. This free EdX course has a segment where you do that comparison of different models in Azure ML:



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