In his New York Times post this week, Brian Burke from Advanced NFL Stats gave the Philadelphia Eagles a 69% chance of defeating the Dallas Cowboys Sunday night. This could be good news for Eagles’ fans, since he gave the Eagles a 64% chance of beating the Chicago Bears last week. Then again, Burke also projected that the Arizona Cardinals had a 22% chance of beating the Seahawks in Seattle… so go figure. Therein lies the danger of projection.
Ultimately, Burke’s win probabilities are not unlike weather forecasting. For example, if you look at Dallas’ ten day forecast, you’ll see a 10% chance of precipitation on Sunday. That rate represents the possibility of rain under the most probable of conditions based on the latest known data. But that percentage doesn’t tell you the environmental conditions under which rain is more, or most probable. Those cagey meteorologists know what those conditions are but leave them out of the forecast. Bastards.
Last week I projected a more conservative win probability for the Eagles, 51%. But what were the conditions that produced the Eagles’ 54-11 victory? Well, the Eagles’ offense operated at an insanely efficient 93% rate, while the Bears’ operated at a 70% rate. The Eagles also had a +1 turnover differential. After plugging these values into the simulation formulas, the Eagles’ win probability increased from 51% to 99.6% and they won by an average score of 30 – 14. If only we knew those conditions ahead of time! Isn’t hindsight the greatest?
Similar to last week, this week’s overall win probability is conservative, but it’s based on an accumulation of factors. After 10,000 simulated contests, the Eagles win 51.7% of the time. But since Kyle Orton will be playing for the injured Tony Romo and linebacker Sean Lee is out, perhaps the Dallas offense will perform less and the Eagles offense will perform better than season efficiency averages dictate. Perhaps we can better define ideal conditions…
If the Eagles’ offense performs at or better than their 74% efficiency rate, the Cowboys perform at or below their 70% season average, and turnovers are equal, then the Eagles have a 63% win probability and actually win 92% of the simulated contests. These are the ideal conditions under which Nick Foles can make it rain in Dallas.
Interact with the viz below to see more on the Eagles/Cowboys.
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.