Data analytics, research and professional sports.

Following week 8 blogging question relating to statistical literacy and the scorekeeping in baseball article, I thought I would blog about how statistics are used to evaluate player potential in sports. I have always been fascinated by how much data analysis and research goes into drafting/recruiting professional players, given the importance this process can have on a franchise's future. Granted unpredictable  and environmental factors can affect the career of a player, it is a fact that, certain teams consistently do a fantastic job of recruiting under the radar players that turn out to be gems and yet were acquired late in the draft process. I like to think that with all the available metrics and historical data, professional teams should be able to devise foolproof mechanisms to pre-determine a player's performance throughout his career provided reasonable work ethics and a favourable team environment.

Richardson Ray's article provides some insight into sports analytics and how advanced analytics have been used in the NBA for over a decade. Teams are already recording and analyzing player performance using information such as shooting percentages, number of dribbles taken, distance covered during a game, how fast a player moves on offense/defence, etc. All teams are obviously using these methods to various extents and there cannot be a simple mathematical formula for drafting and recruiting, however, going into my data analytics course next semester, I hope to develop a better understanding of the possibilities and limitations of advanced analytics and research in sports.

Richardson, R. (2013, Apr 19). Sports' new math: Timberwolves embrace use of analytics as a tool to evaluate players. Saint Paul Pioneer Press.