Personnel-Adjusted Home Run Park Factors in Major League Baseball

The Sports Analytics Intelligence Lab (SAIL) welcomes Jason Osborne, a statistics professor from NCSU, to discuss his recent research in baseball analytics.
 
In this talk, Jason demonstrates how he used generalized linear models to reimagine home run totals allowing for a fairer evaluation of batters in Major League Baseball. 
 
Bio of Jason:
Jason Osborne is Professor in the Department of Statistics, at North Carolina State University, which he joined in 2001. Most of that time he held the position of consulting faculty, designing experiments and analyzing data for faculty and students in the Life Sciences, leading to over 100 coauthored publications. He now focuses on applications in Sports Analytics. Recent projects include field goal kicking in the NFL, regional effects on scheduling in the NBA and NHL, causal inference for the effect of the intentional walk and a shiny app to inform decision-making in baseball.
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Additional Information can be found at: https://heellife.unc.edu/event/11879844