The Tough Questions
Initially, when I first began my research, I was curious as to how far data analytics could actually influence sports, and particularly coaching. Predominantly, I questioned if technology would ever reach a point where coaches in professional sports would rely on computers or software to make real-time decisions. However, my findings did not necessarily prove that to be likely, whereas the majority of data analytic components of sports are focused on the facets of player and team evaluation methods behind the scenes.
See, each play or sequence in a game involves complicated data that no model or analyst can understand in the moment. In brief, I think this concept is best worded in the Interactive Sports Analytics journal, which depicts “…due to the complexity of plays in continuous sports, these data points often lack the specificity and context to enable meaningful retrieval and analytics.” (Sha, Lucey, Yue, Wei, Hobbs, Rohlf, Sridharan, 2018). In simple terms, due to the enormous scale of subsequent data in high pace sports, extracting the important statistics under time constraints isn’t realistic. Additionally, coaches have to make countless situational decisions, which encompasses complicated scenarios that are too thorough to interpret instantaneously. Although, data can still play a significant role in games, as the knowledge gained through off-the-field studies can assist game planning and strategy based on statistical analysis to gain a competitive advantage. This is where the application of data is expanding rapidly. Many leagues are building staffs centered around the topic, and organizations are creating new positions to emphasize the value of collecting and reading advanced statistics. Ultimately, if organizations can effectively integrate analytics into their teams, they will have a competitive advantage that can enable them to win more games. And in turn, winning more games usually equates to making more money, a sometimes forgotten goal of professional sports teams.
Sha, L., Lucey, P., Yue, Y., Wei, X., Hobbs, J., Rohlf, C., & Sridharan, S. (2018). Interactive Sports Analytics. ACM Transactions on Computer-Human Interaction, 25(2), 1–32. doi:10.1145/3185596
