With Ben Roethlisberger’s future continuing to be up in the air, it is fair that many are looking at the other quarterbacks on the roster, those entering free agency, to trade situations, and even to the collegiate ranks in the chance that the Pittsburgh Steelers trade up to snag the quarterback of the future.
That said, as it currently stands, the Steelers will have Dwayne Haskins and Mason Rudolph on the quarterback depth chart if Roethlisberger were to announce his departure.
Steelers faithful generally knows what to expect with Rudolph under center. Haskins is a bigger question mark.
Regardless, entertaining the thought of how each would hypothetically do as a season-long starter for the Steelers could be an interesting exercise.
Thankfully, because of the incredible work of Lee Sharpe (@LeeSharpeNFL) and Sebastian Carl (@mrcaseb), we advanced analytics lovers now have access to nflseedR and the power to explore such hypothetical situations.
In short, nflseedR is a package based in the R-programming language that allows those interested to run thousands – or tens-of-thousands – of simulations across various NFL seasons. Moreover, it allows for the development of unique models for input into the simulation.
In this case, I wanted to explore how a 2020 Steelers’ season would end up with both Rudolph and Haskins under center instead of Roethlisberger.
To do so, you first have to determine how to calculate Roethlisberger’s impact on the team versus the other two. For this simulation, I opted to go with 538’s quarterback-adjusted ELO score. The metric is designed to “account for changes in performance – and personnel – at quarterback, the game’s most important position.”
However, inputting the season-beginning ELO metric for each quarterback is just one piece of the puzzle. In this case, we also want the data to update through each week of the simulation. Using a model pre-developed by the creators of nflseedR, we are able to pass the dynamically-changed ELO metric from week to week to allow for an even more definitive final result.
With that sorted, the process is as simple as swapping out Roethlisberger’s ELO metric for both Rudolph’s and Haskins’.
After that, nflseedR does all the heavy lifting (and heavy math) to determine game outcomes based on ELO, with a quarterback’s ELO evolving and changing throughout the simulation.
Before diving into hypothetical scenarios, let’s establish a baseline by simulating the 2020 NFL season 10,000 times with Roethlisberger as the quarterback.
Ben Roethlisberger: 10,000 Simulations
Over 10,000 simulations of the 2020 NFL season, the Steelers – with Roethlisberger as the starting quarterback – averaged roughly 9 wins per season. While that is three-games less than the 12 victories this past season, I believe it is a rather accurate depiction as there were certainly a few games that Pittsburgh was extremely lucky to win.
Moreover, with Roethlisberger as the quarterback, the Steelers made the playoffs in 61% of the simulations, won the AFC North in just under 30% of the simulations, and won the conference and Super Bowl 9% and 4% of the time, respectively.
The simulation results for Roethlisberger seem in line with what should be expected. Personally, I am a bit surprised at the low AFC North winner percentage but, once you take Lamar Jackson’s ELO score into consideration, it does make sense that the Baltimore Ravens were the beneficiary of the model’s inner workings.
Next, let’s move onto 10,000 simulations with Haskins as the quarterback.
Dwayne Haskins: 10,000 Simulations
If you are a Steelers fan, the results are not optimal after 10,000 simulations with Haskins as the starting quarterback.
After the 10,000 simulations, the Steelers averaged just 6.2 wins. They made the playoffs in just 19% of the sims, managed to win the division in just 600 of the simulations, and basically never secured a first-round bye, a conference championship, or Super Bowl victory.
It is not depicted in the above chart, but the Steelers received the top draft pick in the NFL Draft 8% of the time and received a top-five pick nearly 40% of the time.
The Haskins-led Steelers went 0-16 in 46 of the 10,000 simulations but, on the other hand, did go 16-0 twice (which is a 0.0002% chance, if you are doing the math yourself).
The biggest shock to me with Haskins under center is not the three-game drop in total wins, but the 42% drop in the amount of time the Steelers made the playoffs. With Roethlisberger as the quarterback, the simulation felt Pittsburgh – while not a virtual playoff lock – was an incredibly strong contender to make the playoffs each and every run through the season. With Haskins, the Steelers plummeted to the worst odds in the AFC North at making the playoffs.
Mason Rudolph: 10,000 Simulations
The numbers are no better – worse, in fact – with Rudolph under center. Compared to Haskins starting as the quarterback, the Steelers averaged one less win per season in the 10,000 simulations. As well, there is very little chance (just 11% of the simulations) of the Steelers making the playoffs. The odds of getting a first-round bye, winning the conference championship, or the Super Bowl are about as close to zero as you can get.
While it is again not depicted in the chart, with Rudolph as the starting quarterback, the Steelers received the first-overall draft pick in roughly 15% of the simulations and got a top-five selection in just a hair under 50% of the simulations.
Final Thoughts: 10,000 Simulations
Given the results of the simulation, the best choice – obviously – is for Roethlisberger to return.
But that was not the point of running through these scenarios 10,000 times. The point was to determine if either Haskins or Rudolph could seriously be considered the “next man up” if Roethlisberger were to ride off into the sunset in the comings weeks or months.
Given that Haskins and Rudolph, over the course of 10,000 simulations, rarely led the Steelers to the playoffs, I believe the answer is a pretty solid no. Neither Haskins nor Rudolph, based on the simulations, should be considered the quarterback of the future. They are both stopgaps, at best, until the front office determines the future of the quarterback position in Pittsburgh.
But I think we all knew that to begin with.
What I do think is the most interesting part of the simulations is that Haskins provides marginally better chances of the Steelers making the playoffs, winning the division, etc. if he were to be the stopgap starter versus Rudolph.