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Final Score: NIU 22-21
Vegas Spread: GT by 19
Model Prediction: GT by 12
Projected EPA (Offense and Defense) Margin of Victory: GT by 6.5
GT Win Probability (Based on Success Rate, Yards Per Play, and EPA): 75%
The Las Vegas consensus line had Georgia Tech as about a 90% favorite to beat Northern Illinois. The play by play numbers show that GT wins this game 75% of the time.
But in the opening game of the pivotal third season of the Geoff Collins era, Georgia Tech lost to Northern Illinois. From a high level, here’s how I’m thinking about it:
- A 75% win probability in a game with 90% win expectancy roughly falls on the players not playing as well as expected.
- Losing a game in which GT still had a 75% win probability falls firmly on the coaches.
GT was the better team and managed to lose the game. Let’s dig in.
Success Rate Comparisons
GT vs. NIU Success Rates
Success Rate | O | GT Offense | D | Opp Offense |
---|---|---|---|---|
Success Rate | O | GT Offense | D | Opp Offense |
Down | 1 | 53.10% | 1 | 34.60% |
2 | 33.30% | 2 | 40.00% | |
3 | 52.60% | 3 | 41.70% | |
4 | 50.00% | 4 | ||
Qtr | 1 | 36.80% | 1 | 31.30% |
2 | 57.10% | 2 | 57.10% | |
3 | 52.60% | 3 | 36.40% | |
4 | 40.00% | 4 | 29.40% | |
Pass | P | 40.00% | P | 44.40% |
Rush | R | 52.30% | R | 33.30% |
Overall | 46.80% | 37.90% |
Success rate is the baseline metric for efficiency. As a reminder, a successful play gains 50% of the needed yards on 1st down, 70% on second down, and 100% on third or fourth down.
A quick glance at the success rate breakdowns reveals a game that looks like it went how GT planned. Tech ran the ball very efficiently, and after a slow start, turned in just a slightly below average passing performance. NIU was not able to run the ball efficiently, and their passing game wasn’t enough to make up for it. But that doesn’t really tell the story very well, does it?
Let’s turn now to the full advanced box score to learn more about where the game was lost.
Advanced Stats Comparison and Positional Breakdowns
GT vs. NIU Advanced Box Score
Stat | GT Offense | NIU Offense | National Avg |
---|---|---|---|
Stat | GT Offense | NIU Offense | National Avg |
Snap Count | 79 | 59 | 71.5 |
# Pass Plays Called | 35 | 18 | 31 |
Avg Starting FP | 68.83 | 74.31 | 70.5 |
YPP | 5.18 | 4.39 | 5.7 |
YPA (incl. sacks, scrambles) | 5 | 7.89 | 7.39 |
% of Passes on 1st Down | 39% | 18% | 40.17% |
% of runs on 2nd and long | 50% | 67% | 39.80% |
Avg EPA/play | 0.08 | 0 | -0.01 |
Avg EPA/pass | -0.15 | 0.52 | 0 |
Total EPA | 6.59 | 0.07 | -0.96 |
Avg Air Yards / Completion | 7.67 | 9.7 | 6.14 |
Air Yards / Attempt | 12.35 | 13.53 | 8.89 |
CP | 57.69% | 58.82% | 62.54% |
CPOE | -0.84% | 5.45% | 1.90% |
AVG Line Yards | 3.31 | 2.78 | 2.55 |
Opportunity Rate | 55.81% | 42.11% | 42.42% |
Power Success Rate | 83.33% | 68.60% | |
Stuff Rate (Offense) | 13.64% | 17.95% | 19.17% |
Havoc Rate | 6% | 9% | 21.00% |
Pressure Rate | 22% | 20% | 27.00% |
Quarterback
GT QBs vs. NIU
Player | Success Rate | EPA/play | EPA/pass | CP | CPOE | CPOE10+ | CPOE20+ | EPAwPressure | EPAnoPressure |
---|---|---|---|---|---|---|---|---|---|
Player | Success Rate | EPA/play | EPA/pass | CP | CPOE | CPOE10+ | CPOE20+ | EPAwPressure | EPAnoPressure |
10 | 0.39 | -0.29 | -0.8 | 0.38 | -0.17 | -0.4 | -0.36 | -0.93 | -0.76 |
13 | 0.5 | 0.24 | 0.11 | 0.67 | 0.07 | 0.05 | 0.05 | -1.62 | 0.55 |
On called passing plays (remember, we include sacks and scrambles here), NIU averaged almost 3 yards more per play than GT. NIU held the advantage in passing EPA/play with a stunning 0.52 compared to -0.15 for GT. To get at the magnitude of that difference, all we have to do is multiple those figures by the number of passing plays each team called. That yields a total EPA difference of 14.6 points. That is, the relative strength that NIU held in this area was worth two touchdowns.
Remember what we talked about before the game. Last year, NIU was 124th in the country in defensive EPA/pass. They couldn’t stop anyone. And we lost overall value trying to throw the ball. When Jeff Sims was in the game, that figure was -0.80 EPA/called pass play.
Everything we talked about this offseason, every prediction leading up to this game rested on seeing improvement from the second year starting quarterback. Jordan Yates came in and did an admirable job filling in, but for this team to get where the fanbase (and according to Ken Seguira, several prominent donors, expect to go this year), neither the performance we saw from Sims nor relying on Yates will make that possible.
Rushing
GT Rushing vs. NIU
Runner | Carries | Rushing Success Rate | Highlight Yards |
---|---|---|---|
Runner | Carries | Rushing Success Rate | Highlight Yards |
13 | 3 | 0.67 | 2.5 |
1 | 20 | 0.45 | 37.5 |
4 | 1 | 1 | 10.5 |
10 | 4 | 0.5 | 29 |
27 | 15 | 0.6 | 40 |
The running game lived up to its billing, contributing 12 total EPA for GT and putting up a 52% success rate on called runs. Everyone who was involved contributed effectively. Jordan Mason had a jaw-dropping 60% success rate and added 40 highlight yards on just 15 carries. Sims and Yates both picked up crucial first downs on read option plays. Gibbs didn’t break a long one, but he consistently picked up extra yards after contact. With how the game flow played out, the mystery, of course, is why the play calling balance did not shift much more heavily towards runs. GT called pass plays on 35 of its 79 snaps; that number probably should have been closer to 25.
Receiving
GT Receiving vs. NIU
Receivers | Receiving Success Rate | Avg Target Air Yards | Targets | % of Team Air Yards | YACatch |
---|---|---|---|---|---|
Receivers | Receiving Success Rate | Avg Target Air Yards | Targets | % of Team Air Yards | YACatch |
2 | 0.33 | 12.33 | 6 | 13.43% | 0 |
7 | 0.56 | 11.78 | 9 | 19.24% | 32 |
12 | 0.67 | 12.67 | 3 | 6.90% | 0 |
1 | 0.4 | 10 | 5 | 9.07% | 9 |
8 | 0 | 38 | 1 | 6.90% | 0 |
Early in the game, Coach Patenaude was able to scheme guys open for potential chunk plays. Unfortunately, none of them hit. Later in the game, the passing game turned almost exclusively into quick game - stick routes, hitch routes, anything to help Yates get rid of it quickly and with the expectation of a target being open. Malachi Carter, despite an egregious drop in the first half, did quite well Saturday night. Of course, he caught the lone explosive ball Tech completed all night, but he also put up a 56% receiving success rate and added 32 yards after the catch. None of the other receivers did much to help out, struggling to get separation, and the tight ends were once again nonexistent in the passing game (though Dylan Leonard did block well).
Offensive Line
GT OL vs. NIU
Player | # of FLOPS |
---|---|
Player | # of FLOPS |
55 | 1 |
57 | 0 |
70 | 2 |
74 | 0 |
77 | 0 |
I saw a lot of postgame chatter about the failings of the offensive line. I don’t think it was that bad. GT allowed only 14% of runs to be stuffed, which is well below the national average. The pressure and havoc rates allowed were even further below national average. Our new offensive line stat - FLOPS (failure of line or penalty) - shows us that there was not an egregious number of complete failures. The right guard was the lowest graded lineman according to this metric.
Defensive Disruption
GT Disruption vs. NIU
Player Defending | Havoc Plays | # of Pressures | # of Run Stuffs |
---|---|---|---|
Player Defending | Havoc Plays | # of Pressures | # of Run Stuffs |
1 | 0 | 0 | 1 |
3 | 1 | 1 | 0 |
4 | 0 | 0 | 1 |
13 | 2 | 0 | 3 |
15 | 0 | 1 | 0 |
25 | 0 | 0 | 1 |
42 | 1 | 1 | 0 |
Here’s where things get quite ugly. Far and away the most disruptive player on the defense Saturday night was Wesley Walker. He played outstanding. But your nickel back should not be leading the defense in run stuffs, not to mention havoc plays as well. Jordan Domineck had a pressure and a TFL on the first drive of the game - and then nothing else the rest of the night. The sheer number of guys who aren’t anywhere on this list - including no defensive tackles - doomed the defense last night. The 6% havoc rate that GT posted is the lowest I remember seeing. For comparison, the defense posted an 8% havoc rate - the lowest last year - in the demolition at the hands of Boston College. An NIU offense that couldn’t handle getting pressured or put off schedule didn’t have to deal with either of those issues. GT missed a golden opportunity to try and create some chaos - no matter how many times the coaches use the word.
Pass Coverage
GT Coverage vs. NIU
Player in Primary Coverage | Targets | CPOE Allowed | YAC Allowed |
---|---|---|---|
Player in Primary Coverage | Targets | CPOE Allowed | YAC Allowed |
1 | 1 | -41.00% | 0 |
2 | 1 | -37.00% | 0 |
3 | 4 | -0.90% | 7 |
4 | 1 | -75.00% | 0 |
7 | 1 | 61.40% | 16 |
10 | 2 | 32.67% | 12 |
13 | 1 | 66.60% | 0 |
14 | 1 | -31.00% | 0 |
20 | 1 | -48.00% | 0 |
25 | 1 | 25.00% | 1 |
The coverage was…fine. The guys up front certainly didn’t make things easier for the guys on the backend. The most damaging plays came at the expense of Eley and Walton, giving up a couple of completions that turned into bug gains after missed tackles. On the other hand, no one on the backend made the kind of play that could have changed the game.
EPA Highlights
EPA calculates the expected number of points added (or lost in the case of a negative number) on a particular play based on the down and the location on they field.
The EPA totals for this game leave us with a 6 point projected win for GT. Let me explain that a little bit more though. When I give an EPA total for a game, I include only offensive and defensive plays, as special teams are generally so random from game to game and year to year. However, as you’ll see below, GT’s special teams are once again looking like a significant weakness. As always, we’ll take a look at the most helpful and hurtful plays for GT.
Most Helpful Plays
- Dontae Smith’s 16 yard touchdown run on 4th and 2 to tie up the game. Smith got one carry, and he gave reason to get a few more. This was a great play call and a great run in a big spot. 4.28 EPA.
- Jordan Yates’s 54 yard completion to Malachi Carter to start a crucial 4th quarter drive that ended with Smith’s touchdown run. This was GT’s only explosive pass play of the game. 3.45 EPA.
- Wesley Walker’s forced fumble that gave GT the ball back at the NIU 25 yard line, resulting in GT taking the lead. 3.35 EPA.
- Jordan Yates’s 22 yard touchdown pass to Kyric McGowan on 1st and 10 from the NIU 22 to open the scoring for GT. 2.55 EPA .
GT had only three plays that generated 3 or more EPA; that’s not enough. Again, the offense wasn’t explosive, and the defense wasn’t disruptive.
Most Hurtful Plays
- Jeff Sims’s fumble on 1st and 10 from GT’s 41, giving NIU the ball at the 43 and removing GT’s QB from the game. -5.53 EPA
- Brent Cimaglia’s missed 43 yard FG on GT’s second possession. -3.47 EPA
- Brent Cimaglia’s missed 51 yard FG. -3.40 EPA
- Jeff Sims’s incomplete pass on 4th and 3 on GT’s opening possession. -3.28 EPA.
- Jordan Yates’s (barely) incomplete pass to McGowan on 4th and goal from the NIU 2. -3.19 EPA.
- NIU’s 35 yard touchdown run to open the game’s scoring. -3.15 EPA.
One turnover, two missed field goals, two incomplete passes on 4th down, and a defensive bust. Those are the plays that cost GT the game.
Tracking Season Goals
*I set these goals for the 2021 season in some of my offseason preview work. We will be tracking them as we go this year.
GT Season Goals after NIU
Metric | Season Goal | This Week | Season Long |
---|---|---|---|
Metric | Season Goal | This Week | Season Long |
GT CPOE | >= 2% | -1% | -1% |
Pressure Rate Allowed | <=26% | 20% | 20% |
Pass Rate on 1st Down | >=50% | 39% | 39% |
Defensive Passing EPA/plau | <= -0.06 | 0.52 | 0.52 |
Defensive Havoc Rate | >=21% | 6% | 6% |
Defensive Pressure Rate | >= 27% | 22% | 22% |
This was not a good start, as headlined by the passing offense and passing defense. GT will likely face 9-10 teams who are better than NIU in both of those areas. It doesn’t look good, but we shouldn’t draw sweeping conclusions off of 1 game.
Takeaways
- Figuring out the quarterback position remains the most important issue facing this team. Jeff Sims performed poorly but also left the game with an undisclosed arm injury. Will he be able available to play? If he is, should he? I don’t have answers to either of those questions right now, and I don’t think Collins or Patenaude do either.
- The coaching staff struggles with game management. They chose to try a 61 yard field goal (that had literally 0% chance of even making it over the LOS) instead of a relatively short Hail Mary. GT missed three field goals and had a hilariously clumsy sequence that required burning an important timeout before failing to convert anyway. Substitutions on defense were either late or illegal on multiple occasions when NIU went tempo. Mr. Collins needs someone to help him with basic game management tasks.
- The transfer impact was entirely overblown. I won’t go through individuals here, but anyone hoping that the GT roster was fundamentally changed by an infusion of transfers this offseason was sorely disappointed.
- The defense is not living up to its potential. There is enough talent on defense that we should never see a 6% havoc rate combined with a 17% run stuff rate against a below average MAC offense. The scheme is doing nothing to help guys up front gain an advantage. There are arguments happening consistently in the secondary. The whole is less than the sum of its parts.
You can’t sugarcoat this one. The offense came out flailing, the defense couldn’t make a play, and the coaching staff didn’t know how to situate its guys to succeed. GT lost its 2nd or 3rd easiest game of the season. The offensive line is the only position group that looked improved to me, and with the roster now consisting almost entirely of Collins’s players, that isn’t acceptable. The GT fan base is mad, and I don’t blame anyone for that. The numbers reveal a team that simply could not utilize its talent advantage against an overmatched opponent.
What do you expect the rest of the season to yield?