Baseball Scouting Reports via a Marked Point Process for Pitch Types

Statistics and baseball have always gone hand in hand. In baseball’s earliest days newspapers printed a summary of baseball games that showed the number of runs scored by each player and the number of runs each team scored in each inning (Schwarz, 2004). Over the years what we now know as a box score has evolved to include all of the various outcomes of every pitcher and batter that takes part in the game. Today box scores are just one set of statistical information that is kept in an attempt to summarize a game of baseball. In addition to box scores, fans can now find complete play by play data sets as well as data sets containing pitch trajectory data for every major league baseball game. This abundance of data is used by teams and fans alike in an attempt to explain what they see on ball field. In the past when individual pitch data was collected it was done by tracking each pitch by eye and marking it by hand in a scout’s notebook. Alternatively all of the pitches could be video taped and plotted by hand later. This type of data collection led to large amounts of measurement error for the individual pitch data. However a new age for baseball data collection is beginning thanks in part to the PITCHf/x system (Fast, 2010). This recently developed system uses cameras within every Major League ball park to track the speed, movement, and location of every pitch thrown and provides detailed data about pitch location. Until recently the use of spatial statistical techniques for baseball scouting reports has been fairly restricted. However with the PITCHf/x system providing vast amounts of detailed data regarding pitch location, statistical techniques for