Unable to understand which features to choose
Create a correlation plot and remove all highly correlated columns. Remove columns that are irrelevant to the prediction, such as home/away

If you're interested in feature selection you can use the methods in mlxtend library. It's likely that selecting the right features won't improve your results drastically. There can be other things that can be done to do so. 

Here are some suggestions to improve your results: 


Make sure you're treating the columns with continuous and categorical columns in appropriate ways - encoding only the categorical columns 
Normalize all columns that have continuous variables, perhaps using StandardScaler
Experiment with using feature extraction techniques like PCA 
Try using gradient boosting (LightGBM or CatBoost)  
There seems to be missing data. Make sure to deal with them correctly. If they are very less you can drop those rows.