Every year much of the nation becomes engulfed in the NCAA basketball postseason tournament more affectionately known as “March Madness.” The tournament has received the name because of the ability for any team to win a single game and advance to the next round. The purpose of this study is to determine whether concrete statistical measures can be used to predict the final outcome of the tournament. The data collected in the study include 13 independent variables ranging from the 2003-2004 season up until the current 2009-2010 season. Different tests were run in an attempt to achieve the most accurate predictive model. First, the data were input into Excel and ordinary least squares regressions were run for each year. Then the data were compiled into one file and an ordinary least squares regression was run on that collection of data in Excel. Next, the data were input into Minitab and a stepwise regression was run in order to keep only the significant independent variables. Following that, a regression analysis was run in Minitab. The coefficients from that regression analysis were input into a file with the 2009-2010 data in an attempt to test the model’s results against the actual results. All of the models developed, except one for the year 2005-2006, were determined to be significant. There were 6 significant independent variables determined. The final results showed that although the model developed through the study was significant, the ability to accurately predict the outcomes is very difficult.
Recommended CitationWitkos, Raymond, "Determining the Success of NCAA Basketball Teams through Team Characteristics" (2010). Honors Projects in Mathematics. Paper 5.