I am doing a sports analytics (Sabermetrics) project and wish to investigate the effect of jetlag on MLB players. Currently I am performing analysis on the individual player level rather than the team level. I have a set of players and their stats in non-jetlag games, and I also have their stats with 1 hour jetlag, 2 hours, etc. For each player I performed a t-test per statistic to determine if the average (for any chosen) metric significantly changed with jetlag (compared to no jetlag).
I would like to know the most correct way to present my results. Here is what I've tried:
- % of players who statistically significantly improved or got worse (p < 0.05 in either direction)
- % of players who improved or got worse (regardless of p-values)
- An average of all the averages with and without jetlag, showing that the stats get worse overall when players are jetlagged
- Heatmaps of players with significant improvement or degredation using k-means clustering