The first month of football is a wrap for the Cleveland Browns. It’s hard to believe that nearly a quarter of the season has passed. Personally, it has felt like half a season since the Steelers game. The game-time decision by Deshaun Watson to sit on Sunday has only added to the feeling of the interminable dredge of the offense. A month is long enough for season-long trends to become more evident when examining data.
Football is a difficult sport for data analytics as the sport has the least amount of games compared to other sports. Trends become extremely explicit over 38, 82, and 162 games in one season. Four games over a seventeen-game season does a good job of outlining the picture, even if it doesn’t paint it in detail.
It’s important to remember that the Browns have suffered a lot of blows on offense over the first four weeks. Deshaun Watson looked good in his only game without inclement weather or the morale hit of witnessing a devastating injury to a team leader. I don’t want to make excuses for the Browns’ lackluster start on offense. I want to properly contextualize the offense.
Without further ado, here is the monthly data drop.