Advanced Stats Preview: GT vs. Pitt

Georgia Tech takes on Pitt this Thursday night, in a game that has been twice rescheduled from November 14 to December 12 and finally to December 10. The matchup against Pitt has been a frustrating one for GT fans; it’s a game that many of us peg as a likely win entering the season, but Pitt has won four of the last five after GT won the first two games upon the Panthers’ entry to the ACC Coastal. Before the season, GT had about a 42% win probability in this game; as of this writing, SP+ gives GT a 43% chance, while the Vegas consensus spread has Pitt as a 6.5 point favorite with a 65% chance of winning. Let’s look at the stats matchup and relative advantages each team should expect to have:

*GT numbers come from my play by play charting. Opponent numbers come from @CFB_Data and cfb-graphs.com

They are some striking polarities between these two teams. GT leads in every offensive category except for yards per pass attempt, and Pitt leads in every defensive category except for a tie in yards per pass attempt allowed. That might look like a pretty even matchup, but the GT offense is slightly better than Pitt’s offense, while Pitt’s defense is significantly better than Tech’s.

When GT Has the Ball

Pitt is very good in success rate allowed and yards per play allowed. They are elite in defensive stuff rate and defensive havoc rate. This means GT should expect quite a few plays to go for no gain or losses this week. With the expected absence of Jahmyr Gibbs and his playmaking ability, the prospects dim even further. One important note and caveat: Rashad Weaver has been Pittsburgh’s best and most disruptive defender up front, and he opted out of the season yesterday to go pro. Pitt is still strong up front, but this will take some pressure off of the GT offensive line.

The Pitt defense is statistically closer to the Clemson and ND defenses that bottled up the GT offense than any other opposing defense on our schedule. My hypothesis is that there is a breaking point where the opposing defensive front becomes so physically superior to GT’s offensive line that we become unable to do much of anything on offense. The fear here is that Pitt meets that threshold.

The one glimmer of hope is that Pitt is slightly worse than average on yards allowed per pass attempt, so Jeff Sims may be able to hit some bigger throws on the occasions where he has protection or can escape pressure. Paris Ford, Pitt’s best defensive back, opted out of the season right before our originally scheduled game. But the absence of Gibbs and Ahmarean Brown would greatly diminish those prospects. This is a game where GT is very unlikely to be able to piece together long drives; big plays, and particularly being able to score on big plays, are the best path to putting points on the board for this developing Georgia Tech offense. Connecting on a few deep shots to Camp, Carter, or the rapidly improving Adonicas Sanders will be necessary for GT to stay in this game.

The chart below helps highlight that this GT offense really struggles against very good to elite defenses. The numbers below project a very similar offensive efficiency output to what we saw against Notre Dame, a game in which we scored only one offensive touchdown.

*Efficiency Score is Success Rate Allowed * Yards Per Play Allowed (From a GT offensive perspective, higher is better)

*GT’s offensive efficiency score and offensive EPA/play are projected based on opponent-adjusted performance in the previous games compared to Pitt’s season long statistics.

When Pitt Has the Ball

This is a subpar offense that GT should be able to hold in check. Pitt’s season-long offensive efficiency score is 1.83, which is the third worst mark that GT has faced this year (better than only Syracuse and Duke. They are well below average in offensive EPA/play. However, the starting quarterback Kenny Pickett missed all of the Notre Dame and Miami games; against ND, Pitt managed only a 23% success rate and was well below zero in EPA/play. Against Miami, it was a 32% success rate with an EPA/play well below zero. Without those two games, Pitt starts to look closer to an average offense. Expectations will change depending on which defenders GT ends up having available, but this unit should be able to hold Pitt to an average offensive performance.

*Efficiency Score is Success Rate Allowed * Yards Per Play Allowed (From a GT defensive perspective, lower is better)

*GT’s defensive efficiency score and defensive EPA/play are projected based on opponent-adjusted performance in the previous games compared to Pitt’s season long statistics.

Prediction

I don’t like the matchup. The front 7 for Pitt is a nightmare for the struggling GT offensive line. The havoc wreaking Pitt defense is almost certain to cause some of those turnovers that have fundamentally altered some of GT’s lesser offensive performances this year. Jeff Sims has made some huge throws facing pressure. He has also committed some catastrophic turnovers. Without an outlet for reliable explosive plays, the GT offense is likely to struggle. Given the relative strength of the Pitt D up front and the GT struggle to block, I foresee a few more catastrophic plays for GT than positive explosive ones. The FTRS Model favors Pittsburg by 11 points. I’ll call it 28-17 Pitt.

Year to Date Against the Spread: 1-1

Average Absolute Error: 14.0 points per game