Dr. Tim Chartier is a professor of mathematics and computer science at Davidson College, where he leads a 100-member sports analytics group that supplies analytics to the college's coaches in various sports. The team also provides analytics to organizations all around the sports world to show them how sports analytics can improve their teams’ performance. In this segment, Dr. Chartier shows how his team used JMP to predict which players would be become MLB All-Stars and which teams would participate in the annual college basketball tournament known as March Madness. Using partition analysis in JMP, Chartier and his team determined the best predictor for becoming an MLB All-Star was total bases, with RBI being a secondary predictive statistic. But that wasn’t all, his team also determined that Twitter followers was a strong predictor as well – specifically, if you have over 100,000 Twitter followers, you’re likely to be an All-Star, even if your statistics fall slightly short of the mark! In the second half of his talk, Chartier shows how his team was able to use four years of game logs, JMP and partition analysis to explain the perfect storm of factors that allowed an underdog of historic proportions, #16 seed UMBC, to defeat #1 seed ,University of Virginia, in the 2018 NCAA tournament.