Baylor

Profile vs. FBS, 2015

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+0.3096th
  Defense+0.1046th
• 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.
  Offense51.0%97th
  Defense42.3%54th
• Explosiveness

  Average EPA on the successful snaps: how big the good plays were.
  Offense+1.2680th
  Defense+1.2232nd
• Rushing EPA

  EPA per designed run.
  Offense+0.2595th
  Defense−0.0176th
• Passing EPA

  EPA per pass play.
  Offense+0.4097th
  Defense+0.2424th
• Standard downs

  Success rate on downs where either a run or a pass makes sense, like 1st and 10 or 3rd and 2.
  Offense57.6%99th
  Defense46.4%56th
• Passing downs

  Success rate on downs that all but force a pass, like 2nd and 8 or longer, or 3rd and 5 or longer.
  Offense32.1%40th
  Defense34.4%39th
• Line yards

  Rushing yards per carry credited to the offensive line, weighting the first few yards most.
  Offense3.4798th
  Defense2.7857th
• Stuff rate

  Share of runs stopped at or behind the line of scrimmage.
  Offense12.4%99th
  Defense22.4%70th
• Havoc

  Share of snaps with a tackle for loss, sack, forced fumble, interception or pass breakup.
  Offense1.7%72nd
  Defense1.8%40th

Percentiles among the 128 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, 2015

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 Baylor 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. W
   SMU
2. W
   LAM
3. W
   RICE
4. W
   TTU
5. W
   KU
6. W
   WVU
7. W
   ISU
8. W
   KSU
9. L
   OU
10. W
    OKST
11. L
    TCU
12. L
    TEX
13. W
    UNC

Bars above the line: better than expected for Baylor.

Players, 2015

1. Seth RussellQB87 plays · +0.337 pts/play · 130th of 205 QBs
   0.55WAR0.40 to 0.69
2. Jarrett StidhamQB91 plays · +0.246 pts/play · 140th of 205 QBs
   0.42WAR0.28 to 0.56
3. Devin ChafinRB94 plays · +0.159 pts/play · 87th of 333 RBs
   0.28WAR0.20 to 0.36
4. Corey ColemanWR74 plays · +0.176 pts/play · 45th of 411 WRs
   0.24WAR0.15 to 0.34
5. Johnny JeffersonRB68 plays · +0.168 pts/play · 116th of 333 RBs
   0.21WAR0.14 to 0.28
6. Shock LinwoodRB109 plays · +0.080 pts/play · 150th of 333 RBs
   0.16WAR0.06 to 0.27
7. Jay LeeWR30 plays · +0.221 pts/play · 161st of 411 WRs
   0.12WAR0.07 to 0.17
8. KD CannonWR53 plays · +0.115 pts/play · 172nd of 411 WRs
   0.11WAR0.03 to 0.20

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 Baylor'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, 2015

• Roster talent

  247Sports' talent composite: the recruiting ratings of every player on the roster, transfers included.
  66066031st of 128Roster talent: 660, 31st of 128 in FBS
• Recruiting

  Average 247Sports class score over this season's class and the three before it.
  20720732nd of 128Recruiting: 207, 32nd of 128 in FBS
• Returning production

  Share of last season's production (expected points added) by players still on the roster.
  61%61%65th of 127Returning production: 61%, 65th of 127 in FBS
• SP+ rating

  The result: Bill Connelly's opponent-adjusted rating, points per game better than an average FBS team.
  +19.5+19.512th of 128SP+ rating: +19.5, 12th of 128 in FBS

Ranks and bars among the 128 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, 2015

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 Baylor's own. A call that differs gives up the gap to the best option; gaps under one point are close calls, and the 2 clear-cut ones account for 0.03 of the 0.07 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. at TCUQ4 7:09 4th & 5 at TCU 45, tiedPunted; the numbers favored going for it−1.6 pts
2. vs OUQ2 7:21 4th & 1 at BAY 34, down 7Punted; the numbers favored going for it−1.2 pts
3. vs TTUQ2 8:22 4th & 16 at TTU 16, up 21Went for it; the numbers favored a field goal (close call)−0.9 pts
4. vs ISUQ4 5:31 4th & 1 at ISU 17, up 15Kicked a field goal; the numbers favored going for it (close call)−0.6 pts
5. at TCUQ4 10:16 4th & 6 at TCU 46, tiedPunted; the numbers favored going for it (close call)−0.6 pts
6. vs OUQ3 3:12 4th & 8 at OU 28, down 14Went for it; the numbers favored a field goal (close call)−0.5 pts
7. vs OUQ3 6:49 4th & 2 at BAY 24, down 14Punted; the numbers favored going for it (close call)−0.4 pts
8. at TCUQ2 11:24 4th & 2 at BAY 34, tiedPunted; the numbers favored going for it (close call)−0.3 pts

Record vs. expectation, 2015

84th of 128 FBS teams at beating the model's pregame expectations

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

1. W

   SMU
2. W

   LAM
3. W

   RICE
4. W

   TTU
5. W

   KU
6. W

   WVU
7. W

   ISU
8. W

   KSU
9. L

   OU
10. W

    OKST
11. L

    TCU
12. L

    TEX
13. W

    UNC

What moved it, 2015

Every game starts at Baylor'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+0.34
• Possession & field position−0.02
• Clock−0.19
• Timeouts+0.22
• Less the pregame edge, counted before kickoff−0.88

Game by game

• SMUW 56-21 at SMU89% → 100%Before kickoff +39 · On the field +11: Scoreboard +16
• LAMW 66-31 vs LAM100% → 100%Before kickoff +50 · On the field 0: Scoreboard +1
• RICEW 70-17 vs RICE98% → 100%Before kickoff +48 · On the field +2: Scoreboard +4
• TTUW 63-35 vs TTU84% → 100%Before kickoff +34 · On the field +16: Scoreboard +19
• KUW 66-7 at KU99% → 100%Before kickoff +49 · On the field +1: Scoreboard +3
• WVUW 62-38 vs WVU89% → 100%Before kickoff +39 · On the field +11: Scoreboard +15
• ISUW 45-27 vs ISU98% → 99%Before kickoff +48 · On the field +1: Scoreboard +5
• KSUW 31-24 at KSU91% → 95%Before kickoff +41 · On the field +4: Scoreboard +21, Clock +1
• OUL 34-44 vs OU61% → 3%Before kickoff +11 · On the field −57: Scoreboard −56, Clock −3
• OKSTW 45-35 at OKST58% → 96%Before kickoff +8 · On the field +38: Scoreboard +45, Clock +3
• TCUL 21-28 at TCU52% → 12%Before kickoff +2 · On the field −40: Scoreboard −32, Timeouts +19
• TEXL 17-23 vs TEX90% → 10%Before kickoff +40 · On the field −81: Scoreboard −43, Clock −4
• UNCW 49-38 vs UNC56% → 98%Before kickoff +6 · On the field +41: Scoreboard +37, Timeouts +2

Points of win probability, from Baylor's side.

Closest call

BAY 36-35 UCF (2023) - Baylor dropped to a 0.7% win probability before pulling it out.