Share to FacebookShare to TwitterShare by Email

PLEASE NOTE: Access to items in this collection is restricted to the BU community. Clicking on any item in this collection will prompt a request to sign in with your Kerberos credentials.

This course covered the theory and the fundamentals of the emerging science of Sabermetrics. We discussed the game of baseball, not through consensus or a fan’s conventional wisdom, but by searching for objective knowledge in baseball performance.. These and other areas of sabermetrics were analyzed and better understood with current and historical baseball data.

The course also served as applied introduction to the basics of data science, an emerging field of scholarship, that requires skills in computation, statistics, and communicating results of analyses. Using baseball data, the basics of statistical regression, the R Language, and SQL were covered.

This course was successfully taught on the edX platform as a MOOC in 2014; the present OpenBU collection archives videos from that iteration of the course. This course has also been successfully taught at the Experimental College at Tufts University since 2004. Many of its former students have gone on to careers writing about baseball and working in various MLB baseball operations and analytics departments.