Following is a description of my analysis of results from the 2016 season. App1 was a mini "project" to answer a question I had for a long time: does how hard you hit the ball on average correlate to your batting average? The purpose of this program was more to familiarize myself with some of the csv import tools and reading in data. App2 is the larger and more detailed project.

Data is from right handed hitters vs right handed pitchers with min. 200 PA from the 2016 season.

• Does exit velocity correlate with other outcome statistics?
  • r_squared woba: 0.193797297198
  • r_squared xwoba: 0.436675012661
  • r_squared swings: 0.045913199041
  • r_squared spin_rate: 0.00196997773928
  • r_squared babip: 0.017611788824
  • r_squared velocity: 0.005777216046
  • r_squared whiffs: 0.163971763906
  • r_squared takes: 0.102800689171
  • r_squared ba: 0.0291123323927
  • r_squared iso: 0.298195416685
  • r_squared hits: 0.0641473647931
  • r_squared launch_speed: 1.0
  • r_squared launch_angle: 0.0125656268517
  • r_squared xba: 0.143350021382
  • r_squared effective_speed: 0.00905028893247
  • r_squared slg: 0.28470080813

Exit Velocity is weakly correlated with slugging and xba, which makes intuitive sense, interesting that it is not strongly correlated with any other stats.

• Use statcast data to find good hitting matchups.
  • Given a player, find the pitches he has the most succes with. (what stat to use? hit probability?)
  • Given the pitch with most succes, find a pitcher with pitch most similar to that. - Need to develop a pitch similarity score.
• Flip to find pitcher matchups.
  • Given a plater, find the type of pitch that player has the least success with.
  • Find a pitcher with the most similar type of pitch.