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Analytics and the NFL

Analytics is slowly making its way into the NFL and college football, but has been met with resistance by large, prominent members of the football community due to its challenging of their long-held beliefs. In the past few years, there is clearly a gap between the teams that use analytics to help their decision making and those who don’t.

There are many ways to integrate analytics into American football due to the nuance of the statistics gathered during a single game as opposed to a sport like baseball or basketball, where there are many data points at which to collect statistics (at-bats, shots, etc.). Companies like Pro Football Focus look to isolate player production in the best way possible, and other companies like Sharp Football Analysis look to define successes and failures on particular plays and collect data to be able to identify trends.

These companies apply similar techniques to what we’ve learned in my Data Analytics class, and those who utilize these techniques can reap the benefits. For example, Warren Sharp from Sharp Football Analysis, was able to find out how inefficient the Indianapolis Colts’ play-calling in the fourth quarter of games was in 2017. Through simply picking out situational data to spot how egregiously predictable the 2017 Colts were in the fourth quarter. This reminded me a lot of how we used SQL queries in my Data Analytics class: isolating situations to see if the data presents any trends. A lot of the skill involved in this is asking the right questions, which was the most important part of SQL assignments and exercises. Warren Sharp was able to do this with the Colts to notice that they were using their most inefficient plays during the fourth quarter, and any time they didn’t call one of these plays, it was one of their most efficient plays.

Lack of awareness and looking at the data caused the 2017 Colts to lose more games in the fourth quarter than any team in decades. Scenarios like this will hopefully inspire other teams to use analytics to their advantage and use similar skills to what I’ve learned in my Data Analytics class in order to win more games. Resisting analytics creates unnecessary obstacles to winning.

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