You need machine learning to help you figure out what's really happening
Are you going to help me get started on that?
Instead of going overboard, maybe a relatively simple* approach could already improve this analysis.
For example using a logistic regression with win vs lose as a binary outcome variable. Then as predictors you can use a few "baseline" predictors like win% in past 5 games, past 10 games, whether it's home vs away, % salary difference between teams, opponent teams win % in past 5 and 10 games. "After" this you can add chosen tactic as a predictor and see what remaining predictive power exists for each tactic and what their influence on win likelihood is.
90% of the work is getting the dataset together correctly. Runnnig the regression is a few lines of code.
Context: What this analysis does is try to take away the other factors that also relate to winning likelihood and try to isolate what effect remains of purely the chosen tactic.
* DS/ML folks please keep the simple part in mind before commenting what all wrong about this
Crunchy! If you eat fast enough