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It's not necessary to apply sophisticated models like random forest/neural nets to cricket. It's a sports for which humongous amount of data is kept meticulousl
by maverick_iceman 9y ago
It's not necessary to apply sophisticated models like random forest/neural nets to cricket. It's a sports for which humongous amount of data is kept meticulously; also we're trying to predict pretty standard stuff like who'll win the next match. Standard regression should be able to perform very well (and it does).
- praneshp 9y agoI agree. Just cricinfo statusguru is a huge treasure trove, in addition to several ball by ball datasets from games. Any links to something interesting to read that you suggest?
- maverick_iceman 9y agoieeexplore.ieee.org/document/7489605
- msaharia 9y agoWho will win the match? Sure. But I think the prognostic value (monetary?) will be in ball-by-ball prediction/over prediction/no. of runs scored by a particular batsman, in which we will need a model that can be updated and the ability to ingest and make sense of voluminous amount of data. Some kind of data assimilation component too, maybe?
- Faizann20 9y agoSo I did try simple models but the results with sophisticated models have come out to be better than simpler ones.