By Harrison Chase and Kurt Bullard
Last month, we tried to assess the probability that front offices from each team would fire their coach at the end of a season. While the methodology is laid out in the last post, we can quick summarize here: we found 14 quantitative variables related to team performance—including wins, career win percentage of the coach, and whether or not he made the playoffs that year—that significantly influenced the probability that a coach would lose his job in the upcoming offseason.
Parameter | Estimate | P-Value |
Intercept | 3.656 | <.0001 |
Win Percentage | -8.1205 | <.0001 |
First Year Coach | -2.532 | <.0001 |
Second Year Coach | -1.257 | <.0001 |
Z-Score of Career Win % | -.427 | .0003 |
Defensive Rank of Points | -.0664 | .0009 |
Change in Defensive SRS | -.1106 | .0019 |
Strength of Schedule | -.2069 | .0037 |
Playoff Appearance | .1836 | .0144 |
Change in Offensive Yards | .0314 | .0145 |
Playoff Wins | -2.4111 | .0166 |
Change in Turnover Rank | -.0243 | .0194 |
Third Year Coach | -.7235 | .0219 |
Career Super Bowl Wins | -.5462 | .0397 |
A limitation of our model is that it takes year-end figures as inputs, which makes it hard to predict midseason coaching changes. In this post, we worked around this shortcoming by downloading Neil Paine’s Week 11 ELO scores and using 538’s formula that converts two teams’ ELO scores to their respective win probabilities. With a reasonable estimate of the outcome of each game from now until the end of the season, we ran a Monte Carlo simulation that outputs the distribution of each team’s 2014 win totals. We ran 1,000 trials and using the 0.025 and 0.975 quantiles found a 95% confidence interval for each team’s win totals. Plugging in the bounds of this confidence interval into our firing model, we translated this 95% confidence interval for wins into one for the firing probabilities for each team’s head coach.
Coach | Team | Probability Mean
(95% Confidence Interval) |
Gus Bradley | Jacksonville Jaguars | .551 (.238, .803) |
Rex Ryan | New York Jets | .524 (.218, .803) |
Marvin Lewis | Cincinnati Bengals | .481 (.091,.646) |
Ron Rivera | Carolina Panthers | .420 (.126,.728) |
Mike Smith | Atlanta Falcons | .330 (.105, .713) |
Bradley still holds the greatest chance of getting fired when the end of Week 17 rolls around. However, his chance of getting fired has dropped from 64% to 56%, probability due to the fact that the Jags were able to squeak out one win against the Browns after our initial post. Ryan’s choice to go with Vick got the team a win over the Steelers in Week 10, but did not do much in terms of dropping his chance of getting fired; in fact, it has increased since October, going from 40% to 52%.
After a  hot start, the Bengals having gone 3-3-1 in their last seven games, reducing Marvin Lewis’ chances at retaining his job to a 50-50 proposition. Ron Rivera has led his teams to just three wins in a weak division, but may yet dig himself out of the hole as his Panthers are just one game out of the division lead.
Two notable movers are Lovie Smith and Marc Trestman. Smith has a 32% chance of getting fired, which is pretty high considering the grace period first year coaches receive, but a 2-8 record hardly inspires confidence in the Bucs brass. Marc Trestman has a 6.2% chance of leaving Chicago this winter, which is really small, given their embarrassing performances against New England and Green Bay. The number is so low because the Bears, despite the two blowout losses, have actually improved on defense – going from -7.1 on DSRS to -4.1.
With only six weeks left in the season, these coaches might want to implement some new strategies (like the ones Jeff Fisher used against Seattle in Week 7, or make some drastic personnel changes lest they spend the winter looking for new jobs.
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