clock menu more-arrow no yes mobile

Filed under:

The Steelers ABCs: Coaches, cornerbacks, and comebacks

Pittsburgh’s 13-3 record last season was almost statistically impossible, Todd Haley isn’t that bad, and the cornerbacks are an exciting group.

NFL: Jacksonville Jaguars at Pittsburgh Steelers Charles LeClaire-USA TODAY Sports

Now that the NFL Draft, the zenith of the league’s off-season proceedings, has come and gone, we’re left looking ahead to training camp, which seems like a lifetime away. To keep you engaged during this slow period—a period in which no news is certainly good news—we’re taking an in-depth, alphabetized look at the Pittsburgh Steelers; what they’ve done, where they are now, and where they’re headed. Through these semi-weekly musings, we’ll uncover and unpack some of the interesting storylines from last season and apply them to 2018. You can read Parts A and B here and here.


That the 2017 Pittsburgh Steelers were 13-3—their best record since Ben Roethlisberger’s rookie season in 2004—is largely attributable to their handful of improbable come-from-behind victories: a 17-point comeback against Cincinnati, a 14-point comeback against Indianapolis, an 11-point comeback against Baltimore, and 7-point comeback against Green Bay.

In-game probability models are imperfect and inherently shoddy, but they’re useful for quantifying very quantifiable things—the current game score, the time remaining on the clock, the current possession holder, field-position, et cetera—and predicting an outcome. Of course, there’s no universal model for making these kinds of predictions (see above; imperfect, shoddy things), so for this exercise we’re going to look back at the low points on ESPN’s win-probability model for the games outlined in the aforementioned paragraph:

Steelers at Bengals, December 4th, 2017

Steelers win probability pre-game: 60.3%

Steelers lowest win probability: 7.1% (0:21 remaining in the second quarter, Steelers trailed 17-0)

Result: Steelers win 23-20

Steelers at Colts, November 12, 2017

Steelers win probability pre-game: 86.6%

Steelers lowest win probability: 19.5% (12:46 remaining in the third quarter, Steelers trailed 17-3)

Result: Steelers win 20-17

Steelers vs Ravens, December 10, 2017

Steelers win probability pre-game: 68.7%

Steelers lowest win probability: 8.8% (6:44 remaining in the fourth quarter, Steelers trailed 38-29)

Result: Steelers win 39-38

Steelers vs Packers, November 26, 2017

Steelers win probability pre-game: 83.6%

Steelers lowest win probability: 35.7% (1:33 remaining in the fourth quarter, Steelers tied 28-28)

Result: Steelers win 31-28

To identify just one context-free, baseline commonality: the Steelers played “poorly” against teams that they were supposed to beat. This should not strike you as particularly uncommon, especially if you subscribe to the Tawmlin sucks notion. But let’s dig a little further; based on Pro Football Reference’s Expected Win-Loss Formula, a derivation of Bill James’ Pythagorean Expectation formula that has been fine-tuned to determine football records, the Steelers should have finished somewhere in the ballpark of 10-6 last season. In other words, the Steelers were unquestionably a playoff-caliber team in 2017, but the fact that they legitimately stole a quartet of games despite digging their own grave and shoveling dirt on top made their record look better than it probably deserved to be (for context, Pittsburgh’s expected win-loss record in 2016 was also 10-6, whereas their actual record was 11-5; in 2015, their expected win-loss record of 10-6 matched their actual record).

It’s important to note, however, that in-game win probability models and expected win-loss theorems do not consider the distinctly unquantifiable Any Given Sunday metric. Indeed, grit and human error are both immeasurable variables. Neither model could have predicted that Ben Roethlisberger would rifle a pass to Antonio Brown with under thirty seconds remaining in the game against Green Bay, and neither model could have predicted that Brown, an actual football demigod, would snare that pass out of thin air by the pads of his fingertips and, with the precision and tact of a tightrope walker, drag his toenails on the lone, unsoiled blades of grass separating the playing surface from his home team’s sideline to put the Steelers on the precipice of scoring range. Likewise, neither model could’ve predicted that the Steelers would blow a 14-point lead to the Ravens, only to score twice with four minutes on the clock to surmount a two-possession gap. And neither model could’ve—though they certainly should’ve—predicted that the Bengals would somehow squander a 17-point lead to a Ryan Shazier-less Steelers by generally just being the daffiest group of mouth-breathers in league history.

What do we do with this information? In the spirit of math, let’s attempt to leverage a principle (albeit loosely) that many of us learned in high school pre-calculus: compound probability of independent events. To provide a more plain language explanation, this concept involves calculating the likelihood of one or more events occurring independently in given scenario—meaning that Event A has no impact whatsoever on the outcome of Event B. So, for example, if you flip a quarter, the odds of the coin landing heads-side up are 2-1, or 50%, same as the odds of the same coin landing on tails on a given flip. The probability of that coin landing tails-side up are ALWAYS 50% on a given flip, even if the first 50 flips in a row are all heads. The flip is an independent event.

A professional football game isn’t quite as black-and-white as a coin flip, but I don’t think it’s a stretch to say that, for the most part, each game can be considered ”independent” in and of itself. With that in mind, I applied the compound probability model to Pittsburgh’s four come-from-behind victories—specifically, to the low points I identified in NFL’s model. In order to make the fractions nice and neat, I bumped their denominators up to 1000 (so that 8.8%, for example, was now 88/1000). After determining the numerator and denominator for each event, it was just a matter of multiplying and simplifying to determine the probability that all four of these independent events (each one being a Steelers win) will actually occur. The result: 0.043%.

In conclusion, the Steelers should probably just start handling inferior teams instead of bending the rules of probability and statistics to their will.


Todd Haley is gone. He packed his Corvette full of baggy cargo shorts and matte Oakley Gascans and headed out O-hi-yah way, endeavoring to coach Cleveland’s offense back to relevancy.

Will Tequila Cowboy miss their best customer? They will. Will the Steelers miss Haley, too? Probably they will. In each of the past four seasons, Pittsburgh’s offense has ranked in the top 10 in the NFL in both total offense and scoring offense, which is a testament to the Steelers’ volcanic arsenal of firepower, but also to Haley’s oft-criticized game plan.

And the “oft-criticized” remark isn’t tongue-in-cheek, by the way; Haley made a number of inadvisable calls during his tenure—indefensible ones, even. Here is perhaps his looniest coaching decision, which occurred, fittingly, in his final game with the Steelers:

Please watch that video. Remember the pain you felt. I was at this game, and I’m pretty sure I heard an 8-year-old say the F-word after this play.

Aside from his proclivity for calling overly-complex or outright back-assward plays in situations that could not have been more inopportune, Haley was also known for being fundamentally opposed to operating Pittsburgh’s wildly successful and impossible-to-defend no-huddle offense. Randy Fichtner, who was promoted to Haley’s departed post after spending seven seasons as the Steelers’ quarterback coach, can instantly become the most beloved man in the city simply by allowing Roethlisberger to call his own plays for 16-19 consecutive games.

But Haley deserves credit for promoting the transformation of the Steelers’ offense from a plodding, ineffective unit that supplemented bubble screens for running plays, to a prolific, scoreboard-igniting, tell-you-grandchildren-about-their-exploits outfit that still sometimes supplemented bubble screens for running plays. Fichtner will have some big Air Monarchs to fill.


Last season, from Week 1 until Week 8, the Steelers boasted the league’s best secondary, which, while outstanding, was never something that sat quite right with Pittsburgh’s ever-skeptical (and, frankly, ever-discerning) fanbase. Allowing fewer than 180 passing yards per game—which the Steelers accomplished during this stretch—is a remarkable feat in the modern NFL, but it’s the kind of peculiarity that warrants further inspection. In this case, even a cursory glimpse of Pittsburgh’s early-season schedule should’ve revealed that their hot start was fueled by playing games against DeShone Kizer (in his first career start for the Browns, no less), Case Keenum (then Minnesota’s backup), Mike Glennon (lol), Joe Flacco, Blake Bortles (who has three more playoff victories in his career than Andy Dalton), Alex Smith, and hey, Andy Dalton. Then, in Week 8, Matthew Stafford torched the Steelers for 400-something yards (though, to Pittsburgh’s credit, he didn’t throw any touchdowns), and in Week 10, Joe Haden, the Steelers’ best cornerback, broke his leg in a game in which a person named Jacoby Brissett threw a pair of 60-yard bombs—and that was that.

I don’t want to pin this decline all on the cornerbacks, though. Most of the issues that plagued the secondary originated with Mike Mitchell and Sean Davis, neither of whom could tackle a department store mannequin, let alone a professional football athlete. Artie Burns undoubtedly regressed last season, which is a troubling development, but not necessarily a harbinger of any forthcoming doom (Burns just recently turned 23, after all). Haden, in an abbreviated season, played well enough to quell any concerns about his general health (broken leg notwithstanding, of course) and Mike Hilton, cut by both Jacksonville (as an aside, thank God Jacksonville cut him, because I could not even imagine how formidable a secondary featuring him, Jalen Ramsey, and A.J. Bouye would be) and New England, emerged as one of the league’s most effective, multi-talented slot cornerbacks. Cameron Sutton, a third-round pick last season, spent most of the 2017 season on the sidelines, so (if he’s healthy) he should have a more pronounced role this season.

I like our cornerbacks. This is a talented group! I am most interested in seeing how Burns responds to a his iffy 2017 campaign, because this is a person who in his rookie season looked like a future shutdown cornerback. Burns, like most of Pittsburgh’s secondary, missed a bunch of tackles and made a ton of mental mistakes last year, but he also made a number of spectacular plays that displayed his top-tier athleticism and solid ball skills. I expect a big season from Artie Burns.