Opinion: Why Using Analytics in the NFL is Wrong.

Over the past decade, we’ve seen an analytics revolution in the world of sports. More stats and player data are kept than ever before. We know the fastest players down to the millisecond, we know how many yards on average a receiver runs in a route, we ‘know’ how many wins over a given player’s replacement a starter has.

Analytics based scouting originated in baseball, but has migrated to basketball, hockey, and football. Most teams now have an analytics department, and some make decisions largely based on number crunching. Analytics only recently however solidified itself as a part of the NFL when the Browns hired New York Mets analytic guru Paul DePodesta to build and run the team along with Sashi Brown. DePodesta’s prior experience with football entailed being an unpaid intern with the Canadian Football League’s Baltimore Stallions, where a he operated a T-Shirt cannon among other things that I can only assume were surely important.

DePodesta has spent his two years with the Browns so far amassing as many draft picks as humanly possible. The roster is definitely improving, and at least the Browns have a formula to pick players.

Image result for moneyball
Jonah Hill plays some Moneyball.

I don’t believe that there’s absolutely no place for analytics in the NFL. In a league where the littlest things can make or break a season, coaches and front office members should consult every resource available to help gain an edge. However, to use it as the main guiding compass to assemble a team of 53 players and 10 practice squadders will likely yield little results, and the reason why I think this is quite simple.

The regular season only lasts 16 games.

In baseball, seasons go 162 contests deep. Players will go through hot streaks, slumps, and median output of performance all within a month. A few games of great hitting or strikeouts will not greatly effect the overall success of the team in the grand scheme of things. The same can be said for basketball and hockey as well. Players will go through periods where they shoot from 50% beyond the arc one week, then 30% the next. A hockey player may record a point in 7 straight games, then go 3 more without even getting a mention in the game recap. In those sports, the 82 game seasons allow for hot and cold streaks.

In the NFL, a bad four games can equal a season gone by.

For example, Lions receiver Golden Tate finished the season with 91 receptions, 1,077 yards, and 4 touchdowns. It was the second best year of his six-year career so far, but he didn’t exactly go 6 catches for 70 yards every game to get there. In fact, Golden Tate had about the worst first quarter of the season out of any starting receiver in the NFL. Over the first four games, he had 95 total yards and 0 touchdowns. The Lions went 1-3 in that span.

Singular games matter too much in the NFL to wait around for a player to get out of his slump. Golden Tate was benched for the second half in the fourth game of that 1-3 start after a wrong route led to a pick. If the Lions had just went 2-2 in that first quarter of the year, they would’ve ended up winning the NFC North for the first time in team history and hosting a playoff game for the first time ever at Ford Field. That’s just how close things in this league are, and when jobs and careers are on the line coaches and front office big shots don’t have time to wait for your little math equation to save the day.

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