Well, amazingly, here we are. In just his first season as an NFL head coach, Chip Kelly has proved all naysayers wrong. When Jeff Lurie announced Kelly as the next Eagles head coach last year, there was primarily hope and optimism, and scattered pessimism peppered with tempered expectations. But, here we are, sixteen regular season games and ten wins later, hosting the New Orleans Saints as NFC East division champs. Relish the feeling and enjoy the ride, everyone. This season is already a success, but this team, certainly capable of a deep playoff run (shhh… if not more!), is only going to get better.
In our way stand Drew Brees, the quickest gunslinger in the South, and his primary weapon, Jimmy Graham. The duo has been nearly unstoppable, yet must be stopped in order for the Eagles to emerge victorious. Brees has operated the Saints’ offense at a 73.6% rate of efficiency, slightly higher that the Eagles’ 73.2% rate. This is a tremendous achievement given how little the Saints run the ball compared to the Eagles (the Eagles have 109 more rushing attempts on the season). Which brings us to the theme of this week’s simulation: home field advantage.
This season Drew Brees is a different player outside of the Superdome. At home, he has a QB rating of 126.3; away he has a rating of 84.8 and when playing on grass he has an 85.8 rating. If the game were played in New Orleans, the Saints would have a 63.2% win probability, winning by an average of four points (and this, if both offenses performed at or better than their season averages). Good thing the game is in Philadelphia.
Despite their (slightly) lesser offensive efficiency mark, the Eagles playing at home have a 64.3% chance of winning by an average of 2.5 points, a 6.5 point swing (again, this assumes both offenses perform well). As always, turnovers will play a huge role in the outcome. Regardless, let us bear witness to the power of home field advantage.
Interact with the viz below to see more on the Eagles/Saints.
Note: NFL simulations are far from an exact science. They attempt to mathematically project the future based on history and past performance, but they can’t account for everything. A stiff breeze, a tipped ball, a freak injury, a rolling fog bank, an ol’ coach’s return, or simply a change in player attitude can alter results in a large way. Instead, simulations give us a blurry view of a series of possibilities among an infinite number of potential realities. But they’re fun. If you believe in parallel or multiple universes, then one of these simulated results could possibly occur.
The simulation is based on my home field advantage (HFA) research, which shows how there have been small but distinct and different offensive efficiency behaviors between home teams and away teams in the NFL. And not surprisingly, turnovers play a large role in equalizing the playing field. Offensive performances throughout the season were entered into a logistic regression formula born from the HFA research, and randomized according to standard error values and turnover differential.
Step 1: Calculate Offensive Efficiency (OE). I used Chip Kelly’s definition for this:
(Rushes + Completions) / (Total Off Plays + Offensive Penalties)
If you check out the HFA research, there’s a really strong correlation between offensive efficiency and team success.
Step 2: Calculate Win Probabilities using the logistic regression formula that correlated OE to team success. Here’s the formula:
Win Probability = 1 / (1 + e^-((A*OE+error value) + (B*Turnover Diff + error value) + C)), where A, B, and C are constants.
Step 3: Convert the results from Step 2 into points using a linear formula:
Points = A*(Win Probability for Eagles) + B*(Win probability for Opponent) + C, where A, B, and C are constants.
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