Hey guys, my company is running an open data science competition for the Cricket World Cup and I’m trying to have a go myself. I’ve done some research on some possible approaches but wondered if anyone else could think of another approach.

The approach I’ve tried (paper linked below):

– I created new attributes for things like form and consistency (as described in the paper)
– Then I’ve had a go at using Naïve bayes, random forest, multiclass SVM and decision tree classifiers to predict if a ball is a wicket. (but made a hash of it so far)
https://www.researchgate.net/publication/323611656_Predicting_Players’_Performance_in_One_Day_International_Cricket_Matches_Using_Machine_Learning)
The dataset is about 1m points, 29 factors and about 4000 matches (recorded ball by ball), if people want to see I can post a link to the competition.