SMU

Profile vs. FBS, 2016

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+0.0833rd
  Defense+0.0861st
• 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.
  Offense40.1%15th
  Defense44.0%44th
• Explosiveness

  Average EPA on the successful snaps: how big the good plays were.
  Offense+1.1844th
  Defense+1.1945th
• Rushing EPA

  EPA per designed run.
  Offense+0.0231st
  Defense+0.1620th
• Passing EPA

  EPA per pass play.
  Offense+0.1648th
  Defense+0.0187th
• Standard downs

  Success rate on downs where either a run or a pass makes sense, like 1st and 10 or 3rd and 2.
  Offense44.6%17th
  Defense49.3%38th
• Passing downs

  Success rate on downs that all but force a pass, like 2nd and 8 or longer, or 3rd and 5 or longer.
  Offense31.9%34th
  Defense32.8%55th
• Line yards

  Rushing yards per carry credited to the offensive line, weighting the first few yards most.
  Offense2.9347th
  Defense3.2012th
• Stuff rate

  Share of runs stopped at or behind the line of scrimmage.
  Offense18.9%50th
  Defense16.6%21st
• Havoc

  Share of snaps with a tackle for loss, sack, forced fumble, interception or pass breakup.
  Offense16.2%47th
  Defense15.3%33rd

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, 2016

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 SMU 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
   UNT
2. L
   BAY
3. W
   LIB
4. L
   TCU
5. L
   TEM
6. L
   TLSA
7. W
   HOU
8. W
   TULN
9. L
   MEM
10. W
    ECU
11. L
    USF
12. L
    NAVY

Bars above the line: better than expected for SMU.

Players, 2016

1. Ben HicksQB384 plays · +0.164 pts/play · 70th of 218 QBs
   1.18WAR0.51 to 1.89
2. Ke'Mon FreemanRB145 plays · +0.174 pts/play · 59th of 347 RBs
   0.47WAR0.33 to 0.63
3. Courtland SuttonWR107 plays · +0.230 pts/play · 5th of 417 WRs
   0.46WAR0.30 to 0.62
4. Braeden WestRB201 plays · +0.096 pts/play · 94th of 347 RBs
   0.36WAR0.15 to 0.54
5. James ProcheWR76 plays · +0.105 pts/play · 135th of 417 WRs
   0.15WAR0.04 to 0.26
6. Xavier CastilleWR49 plays · +0.156 pts/play · 146th of 417 WRs
   0.14WAR0.08 to 0.21
7. Matt DavisQB31 plays · +0.199 pts/play · 187th of 218 QBs
   0.12WAR0.04 to 0.18
8. Jamie SackvilleP55 plays · +0.100 pts/play · 58th of 82 punters
   0.10WAR0.02 to 0.17

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 SMU'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, 2016

• Roster talent

  247Sports' talent composite: the recruiting ratings of every player on the roster, transfers included.
  47447475th of 128Roster talent: 474, 75th of 128 in FBS
• Recruiting

  Average 247Sports class score over this season's class and the three before it.
  14114178th of 128Recruiting: 141, 78th of 128 in FBS
• Returning production

  Share of last season's production (expected points added) by players still on the roster.
  90%90%18th of 128Returning production: 90%, 18th of 128 in FBS
• SP+ rating

  The result: Bill Connelly's opponent-adjusted rating, points per game better than an average FBS team.
  −10.8−10.8104th of 128SP+ rating: −10.8, 104th 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, 2016

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 SMU's own. A call that differs gives up the gap to the best option; gaps under one point are close calls, and the 7 clear-cut ones account for 0.17 of the 0.27 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 TLSAQ4 4:17 4th & 1 at SMU 44, down 3Punted; the numbers favored going for it−7.3 pts
2. vs HOUQ3 6:55 4th & 9 at SMU 26, up 14Went for it; the numbers favored punting−3.1 pts
3. at TLSAQ2 2:13 4th & 1 at SMU 34, up 4Punted; the numbers favored going for it−1.8 pts
4. vs HOUQ3 5:23 4th & 6 at HOU 40, up 14Punted; the numbers favored going for it−1.5 pts
5. vs MEMQ2 3:41 4th & 1 at SMU 45, down 24Punted; the numbers favored going for it−1.3 pts
6. vs MEMQ2 9:08 4th & 5 at MEM 32, down 24Punted; the numbers favored going for it−1.2 pts
7. vs TCUQ2 7:07 4th & 3 at TCU 36, tiedPunted; the numbers favored going for it−1.1 pts
8. at UNTQ4 2:05 4th & 4 at UNT 37, up 13Punted; the numbers favored going for it (close call)−0.8 pts

Record vs. expectation, 2016

44th of 128 FBS teams at beating the model's pregame expectations

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

1. W

   UNT
2. L

   BAY
3. W

   LIB
4. L

   TCU
5. L

   TEM
6. L

   TLSA
7. W

   HOU
8. W

   TULN
9. L

   MEM
10. W

    ECU
11. L

    USF
12. L

    NAVY

What moved it, 2016

Every game starts at SMU'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+0.88
• Possession & field position−0.01
• Timeouts+0.19
• Less the pregame edge, counted before kickoff+0.55

Game by game

• UNTW 34-21 at UNT85% → 98%Before kickoff +35 · On the field +13: Scoreboard +25, Clock +1
• BAYL 13-40 at BAY4% → 0%Before kickoff −46 · On the field −4: Scoreboard −7
• LIBW 29-14 vs LIB87% → 99%Before kickoff +37 · On the field +12: Scoreboard +17
• TCUL 3-33 vs TCU8% → 0%Before kickoff −42 · On the field −8: Scoreboard −13
• TEML 20-45 at TEM19% → 98%Before kickoff −31 · On the field +78: Scoreboard +61, Clock +2
• TLSAL 40-43 at TLSA26% → 15%Before kickoff −24 · On the field −11: Scoreboard −31, Timeouts +18
• HOUW 38-16 vs HOU7% → 100%Before kickoff −43 · On the field +93: Scoreboard +58, Timeouts +2
• TULNW 35-31 at TULN54% → 79%Before kickoff +4 · On the field +25: Scoreboard +38, Clock +4
• MEML 7-51 vs MEM39% → 0%Before kickoff −11 · On the field −39: Scoreboard −43
• ECUW 55-31 at ECU41% → 99%Before kickoff −9 · On the field +58: Scoreboard +57, Clock +2
• USFL 27-35 vs USF21% → 4%Before kickoff −29 · On the field −17: Scoreboard −32, Clock −2
• NAVYL 31-75 vs NAVY40% → 0%Before kickoff −10 · On the field −39: Scoreboard −44, Clock −1

Points of win probability, from SMU's side.

Closest call

HOU 16-38 SMU (2016) - SMU dropped to a 6.8% win probability before pulling it out.