Predict the next player's option for betting based on playing history? I have a project which is to predict in next time, which option player will select for betting. This prediction based on his history. For example, the player have time series data, the last options they selected, how much money they spend, did they loose or win...ect. There are many options for one bet, around 300. Based on that data, I want to predict next time which option (or possibility of options) they will choose for betting.

I don't know which kind of problem it is. Is it kind of product recommendation, multi-class classification or multi-label classification? Any keyword, or suggestion to solve this kind of problem? Thanks.
this is a multi class classification problem.

There are many approaches you can use to solve this problem. 

You can first try Gradient Boosted Trees with libraries like xgboost or lightgbm. Both of those can be used in R or Python.

You can also use neural networks for multi class classification problems.

But there are many ways to solve a multi classification problem.

You can turn it into a multi binary classification problem. Since you have 300 options, you can train 300 binary classification algorithms on your data.

You can also try K nearest neighbours.