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I too have considered this [0]. You don't really need to scrape, old data is there via retrosheet and current data is available as XML and JSON via gdx.mlb.com
by kodablah 9y ago
I too have considered this [0]. You don't really need to scrape, old data is there via retrosheet and current data is available as XML and JSON via gdx.mlb.com (e.g. for 2017 [1]). Of course, beware the terms of use, but if it's just for yourself, I'd say no prob.
As for predictive analytics themselves, you can dig into all the metrics you want, but training/backcasting is how I'd approach it.
0 - https://github.com/cretz/software-ideas/issues/43 https://github.com/cretz/software-ideas/issues/43
1 - http://gdx.mlb.com/components/game/mlb/year_2017/ http://gdx.mlb.com/components/game/mlb/year_2017/
- billysbeanes 9y agoWorth noting that this field is reaching diminishing returns due to analyses. You might be 2% better than a stock analysis, but that's usually not a sufficient edge to exploit profitably unless you're talking HUGE numbers. Finding a problem someone has, solving it with analysis, and offering to license/sell it to them (once it's proven to work) is probably more lucrative. Unless you're chasing the variable rewards skinner box. In that case, I'd probably just take up a cocaine habit -- it'll be cheaper.
- kodablah 9y agoLate response, but figured I'd mention that we have new variables now that we didn't always. Pitch FX, fielder location, etc. Not that it makes a huge different, but playing daily and averaging out over time, it can really affect matchups (again, over a large enough sample size).