A couple years ago it came to my attention just how many historians of psychology were interested in baseball. It occurred to me that, given my interest in Frank and Lillian Gilbreth (who performed a micromotion analysis of the New York Giants baseball team in 1913), I might dabble in the analysis of baseball statistics myself.
Below is a video of a digital history project from my 2012 Multivariate Psychology graduate course. I performed statistical and digital history analyses to visualize batter and pitcher statistics for two baseball teams who experienced very early analysis by psychologists: The New York Giants by Frank and Lillian Gilbreth in 1913, and the Chicago Cubs with Coleman Griffith in 1938. I also included a control team, the Boston Red Sox. Here is a link to the original paper: Belliveau Baseball Digital History Paper.
To briefly summarize the analysis: First, I performed repeated measures and mixed models multivariate analysis of variance (MANOVA) to discover if player statistics improved after the psychological interventions. I also created 2D and 3D HE plots and spaghetti plots to visualize this data.
Next, and this is the part that will be of interest to aspiring digital historians, I generated a dynamic bubble chart to visualize trends in player statistics over time. That part of the analysis begins at the 6:11 mark.
To make a long story short, the complete lack of any significant effect on pitching and batting statistics for the intervention teams convinced me not to pursue this line of research. It is, however, an interesting piece of digital history and points to some neat things that we can do to visualize psychological data using the programming language R.
Film and music materials for this project were obtained from the Critical Past and Archive.org websites. The project is narrated by Arlie Belliveau. The accompanying paper is available here: Belliveau Baseball Digital History Paper.