Northwestern

Profile vs. FBS, 2025

Farther out is better on every spoke. Dashed ring: the FBS median.

• EPA per play

  Expected points added on an average snap: how much each play moved the scoring odds.
  Offense+0.0735th
  Defense+0.1144th
• Success rate

  Share of snaps that stayed on schedule: half the yards needed on 1st down, 70% on 2nd, all of them on 3rd or 4th.
  Offense43.2%59th
  Defense45.3%14th
• Explosiveness

  Average EPA on the successful snaps: how big the good plays were.
  Offense+1.1720th
  Defense+1.1590th
• Rushing EPA

  EPA per designed run.
  Offense+0.1058th
  Defense+0.1325th
• Passing EPA

  EPA per pass play.
  Offense+0.1339th
  Defense+0.1748th
• Standard downs

  Success rate on downs where either a run or a pass makes sense, like 1st and 10 or 3rd and 2.
  Offense47.5%47th
  Defense49.7%26th
• Passing downs

  Success rate on downs that all but force a pass, like 2nd and 8 or longer, or 3rd and 5 or longer.
  Offense33.2%76th
  Defense34.0%11th
• Line yards

  Rushing yards per carry credited to the offensive line, weighting the first few yards most.
  Offense2.9753rd
  Defense3.1617th
• Stuff rate

  Share of runs stopped at or behind the line of scrimmage.
  Offense17.5%65th
  Defense15.3%13th
• Havoc

  Share of snaps with a tackle for loss, sack, forced fumble, interception or pass breakup.
  Offense16.7%30th
  Defense15.0%39th

Percentiles among the 136 FBS teams this season, where higher is better for the offense and the defense alike (a defense's numbers are what it allowed). The line in each bar is the FBS median. Garbage time excluded. Source: CollegeFootballData.

Drives vs. expectation, 2025

Every snap has an expected-points value: what a drive from that spot, down and distance is worth on average. A drive over expected beat its starting spot; defense counts what Northwestern allowed, so lower is better. The adjusted number fits every team against the opponents it actually played, so it leans toward average early in a season. Ranks are among FBS teams.

Game by game

1. L
   TULN
2. W
   WIU
3. L
   ORE
4. W
   UCLA
5. W
   ULM
6. W
   PSU
7. W
   PUR
8. L
   NEB
9. L
   USC
10. L
    MICH
11. W
    MINN
12. L
    ILL
13. W
    CMU

Bars above the line: better than expected for Northwestern.

Players, 2025

1. Preston StoneQB323 plays · +0.141 pts/play · 92nd of 231 QBs
   0.85WAR0.30 to 1.44
2. Caleb KomolafeRB175 plays · +0.101 pts/play · 32nd of 365 RBs
   0.33WAR0.22 to 0.43
3. Griffin WildeWR83 plays · +0.128 pts/play · 72nd of 451 WRs
   0.20WAR0.04 to 0.34
4. Hayden Eligon IIWR52 plays · +0.186 pts/play · 85th of 451 WRs
   0.18WAR0.09 to 0.28
5. Joseph Himon IIRB97 plays · +0.082 pts/play · 169th of 365 RBs
   0.15WAR0.10 to 0.20
6. Jack OlsenPK18 plays · +0.327 pts/play · 24th of 112 kickers
   0.11WAR0.07 to 0.15
7. Hunter WelcingTE35 plays · +0.114 pts/play · 52nd of 213 TEs
   0.07WAR0.02 to 0.13
8. Luke AkersP25 plays · +0.069 pts/play · 52nd of 100 punters
   0.03WAR0.00 to 0.07

By position group, against FBS

Linemen and defenders are valued as units, in points per game against the median FBS unit, because play-by-play doesn't say who was on the field. Players are valued against a replacement-level backup, so the two aren't added together.

Wins above replacement credits each play's expected points to the players involved, adjusted for the opponent, and compares Northwestern's players with a typical backup; 53 points make a win. Only snaps while the game was in doubt count, so a starter on a team that blows opponents out plays fewer of them: read value per play beside WAR. The line under each player (or the range on a phone) is the 90% interval. Ranks are among FBS teams and players. How this works

What it had and what it did, 2025

• Roster talent

  247Sports' talent composite: the recruiting ratings of every player on the roster, transfers included.
  67867857th of 134Roster talent: 678, 57th of 134 in FBS
• Recruiting

  Average 247Sports class score over this season's class and the three before it.
  18618659th of 134Recruiting: 186, 59th of 134 in FBS
• Returning production

  Share of last season's production (expected points added) by players still on the roster.
  20%20%95th of 132Returning production: 20%, 95th of 132 in FBS
• SP+ rating

  The result: Bill Connelly's opponent-adjusted rating, points per game better than an average FBS team.
  +5.8+5.850th of 134SP+ rating: +5.8, 50th of 134 in FBS

Ranks and bars among the 134 FBS teams with a talent rating this season, best first; the line in each bar is the FBS median.

Talent conversion

Conversion by season

Fourth-down calls vs. the numbers, 2025

Each real fourth down is valued three ways (go for it, kick, punt) from the score, clock and field position before the snap, using league-wide odds rather than Northwestern's own. A call that differs gives up the gap to the best option; gaps under one point are close calls, and the 5 clear-cut ones account for 0.09 of the 0.12 expected wins. The model sees the situation, not the injury report, so a call it disagrees with can still be right. Ranks are among FBS teams; 1st gave up the least.

Costliest calls against the numbers

1. vs UCLAQ4 3:23 4th & 4 at NU 49, tiedPunted; the numbers favored going for it−3.6 pts
2. vs UCLAQ4 7:50 4th & 2 at UCLA 2, up 8Kicked a field goal; the numbers favored going for it−1.7 pts
3. at USCQ3 12:08 4th & 3 at USC 44, down 7Punted; the numbers favored going for it−1.3 pts
4. at USCQ2 3:32 4th & 1 at NU 30, tiedPunted; the numbers favored going for it−1.2 pts
5. vs MICHQ3 9:17 4th & 7 at NU 28, down 8Went for it; the numbers favored punting−1.2 pts
6. at TULNQ1 0:40 4th & 3 at TULN 3, down 7Kicked a field goal; the numbers favored going for it (close call)−0.5 pts
7. vs MINNQ4 0:53 4th & 2 at MINN 15, tiedKicked a field goal; the numbers favored going for it (close call)−0.4 pts
8. vs CMUQ2 0:28 4th & 20 at CMU 42, up 21Punted; the numbers favored a field goal (close call)−0.4 pts

Record vs. expectation, 2025

40th of 136 FBS teams at beating the model's pregame expectations

Expected wins adds up Northwestern's chance of winning each game as the model saw it at kickoff - a 70% favorite counts 0.7.

1. L

   TULN
2. W

   WIU
3. L

   ORE
4. W

   UCLA
5. W

   ULM
6. W

   PSU
7. W

   PUR
8. L

   NEB
9. L

   USC
10. L

    MICH
11. W

    MINN
12. L

    ILL
13. W

    CMU

What moved it, 2025

Every game starts at Northwestern's pregame chance; everything after that is the field. The model's own breakdown of each game's final play splits the on-field part by what drove it, and the parts add up exactly. How it works →

• Scoreboard−0.20
• Clock−0.02
• Timeouts−0.17
• Other−0.01
• Less the pregame edge, counted before kickoff+0.57

Game by game

• TULNL 3-23 at TULN37% → 0%Before kickoff −13 · On the field −36: Scoreboard −36, Timeouts −1
• WIUW 42-7 vs WIU98% → 100%Before kickoff +48 · On the field +2: Scoreboard +4
• OREL 14-34 vs ORE5% → 0%Before kickoff −45 · On the field −4: Scoreboard −9
• UCLAW 17-14 vs UCLA68% → 19%Before kickoff +18 · On the field −49: Timeouts −39, Clock −3
• ULMW 42-7 vs ULM81% → 100%Before kickoff +31 · On the field +19: Scoreboard +27, Timeouts −4
• PSUW 22-21 at PSU7% → 93%Before kickoff −43 · On the field +86: Timeouts +28, Scoreboard +19
• PURW 19-0 vs PUR61% → 99%Before kickoff +11 · On the field +38: Scoreboard +37, Timeouts +2
• NEBL 21-28 at NEB26% → 3%Before kickoff −24 · On the field −23: Scoreboard −26, Timeouts −2
• USCL 17-38 at USC14% → 0%Before kickoff −36 · On the field −14: Scoreboard −18
• MICHL 22-24 vs MICH20% → 3%Before kickoff −30 · On the field −18: Scoreboard −30, Clock −1
• MINNW 38-35 vs MINN60% → 84%Before kickoff +10 · On the field +24: Scoreboard +21, Timeouts +1
• ILLL 13-20 at ILL28% → 3%Before kickoff −22 · On the field −25: Scoreboard −27, Timeouts −2
• CMUW 34-7 vs CMU83% → 100%Before kickoff +33 · On the field +17: Scoreboard +20

Points of win probability, from Northwestern's side.

Closest call

MINN 34-37 NU (2023) - Northwestern dropped to a 3.2% win probability before pulling it out.