San José State

Profile vs. FBS, 2019

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+0.1664th
  Defense+0.1340th
• 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.
  Offense45.3%65th
  Defense47.0%13th
• Explosiveness

  Average EPA on the successful snaps: how big the good plays were.
  Offense+1.2049th
  Defense+1.1185th
• Rushing EPA

  EPA per designed run.
  Offense−0.089th
  Defense+0.1614th
• Passing EPA

  EPA per pass play.
  Offense+0.3286th
  Defense+0.0970th
• Standard downs

  Success rate on downs where either a run or a pass makes sense, like 1st and 10 or 3rd and 2.
  Offense48.7%60th
  Defense51.3%18th
• Passing downs

  Success rate on downs that all but force a pass, like 2nd and 8 or longer, or 3rd and 5 or longer.
  Offense38.3%84th
  Defense35.7%26th
• Line yards

  Rushing yards per carry credited to the offensive line, weighting the first few yards most.
  Offense2.444th
  Defense3.2212th
• Stuff rate

  Share of runs stopped at or behind the line of scrimmage.
  Offense26.0%2nd
  Defense15.1%5th
• Havoc

  Share of snaps with a tackle for loss, sack, forced fumble, interception or pass breakup.
  Offense22.0%24th
  Defense18.5%33rd

Percentiles among the 130 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, 2019

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 San José State 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
   UNCO
2. L
   TLSA
3. W
   ARK
4. L
   AF
5. W
   UNM
6. L
   NEV
7. L
   SDSU
8. W
   ARMY
9. L
   BOIS
10. L
    HAW
11. L
    UNLV
12. W
    FRES

Bars above the line: better than expected for San José State.

Players, 2019

1. Josh LoveQB445 plays · +0.241 pts/play · 15th of 228 QBs
   2.01WAR1.25 to 2.79
2. Tre WalkerWR110 plays · +0.206 pts/play · 2nd of 439 WRs
   0.42WAR0.28 to 0.56
3. DeJon PackerRB133 plays · +0.132 pts/play · 134th of 349 RBs
   0.33WAR0.22 to 0.43
4. Matt MercurioPK22 plays · +0.482 pts/play · 13th of 114 kickers
   0.20WAR0.15 to 0.25
5. Bailey GaitherWR77 plays · +0.130 pts/play · 80th of 439 WRs
   0.19WAR0.08 to 0.28
6. Isaiah HamiltonWR51 plays · +0.173 pts/play · 97th of 439 WRs
   0.17WAR0.10 to 0.23
7. Tyler NevensRB30 plays · +0.135 pts/play · 277th of 349 RBs
   0.08WAR0.05 to 0.10
8. Nick NashWR20 plays · +0.151 pts/play · 343rd of 439 WRs
   0.06WAR0.03 to 0.08

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 San José State'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, 2019

• Roster talent

  247Sports' talent composite: the recruiting ratings of every player on the roster, transfers included.
  43343395th of 130Roster talent: 433, 95th of 130 in FBS
• Recruiting

  Average 247Sports class score over this season's class and the three before it.
  13213295th of 130Recruiting: 132, 95th of 130 in FBS
• Returning production

  Share of last season's production (expected points added) by players still on the roster.
  55%55%80th of 130Returning production: 55%, 80th of 130 in FBS
• SP+ rating

  The result: Bill Connelly's opponent-adjusted rating, points per game better than an average FBS team.
  −7.2−7.299th of 130SP+ rating: −7.2, 99th of 130 in FBS

Ranks and bars among the 130 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, 2019

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 San José State'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 0.07 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. at UNLVQ3 7:05 4th & 4 at UNLV 41, tiedPunted; the numbers favored going for it−2.0 pts
2. at ARKQ4 7:34 4th & 8 at ARK 34, up 7Punted; the numbers favored going for it−1.8 pts
3. vs TLSAQ3 14:55 4th & 2 at SJSU 46, down 7Punted; the numbers favored going for it−1.5 pts
4. vs BOISQ3 10:27 4th & 2 at BOIS 17, up 7Kicked a field goal; the numbers favored going for it−1.2 pts
5. vs UNCOQ4 10:55 4th & 2 at UNCO 44, up 10Punted; the numbers favored going for it−1.0 pts
6. vs FRESQ3 5:17 4th & 3 at SJSU 43, down 6Punted; the numbers favored going for it (close call)−0.6 pts
7. vs UNMQ3 12:28 4th & 2 at SJSU 37, up 19Punted; the numbers favored going for it (close call)−0.5 pts
8. vs UNMQ4 6:16 4th & 2 at UNM 7, up 15Kicked a field goal; the numbers favored going for it (close call)−0.5 pts

Record vs. expectation, 2019

56th of 130 FBS teams at beating the model's pregame expectations

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

1. W

   UNCO
2. L

   TLSA
3. W

   ARK
4. L

   AF
5. W

   UNM
6. L

   NEV
7. L

   SDSU
8. W

   ARMY
9. L

   BOIS
10. L

    HAW
11. L

    UNLV
12. W

    FRES

What moved it, 2019

Every game starts at San José State'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+0.07
• Possession & field position+0.07
• Clock+0.06
• Timeouts−0.01
• Less the pregame edge, counted before kickoff+0.82

Game by game

• UNCOW 35-18 vs UNCO89% → 99%Before kickoff +39 · On the field +10: Scoreboard +16
• TLSAL 16-34 vs TLSA33% → 1%Before kickoff −17 · On the field −32: Scoreboard −41, Clock −2
• ARKW 31-24 at ARK9% → 94%Before kickoff −41 · On the field +85: Scoreboard +52, Clock +3
• AFL 24-41 at AF10% → 1%Before kickoff −40 · On the field −9: Scoreboard −16, Timeouts −1
• UNMW 32-21 vs UNM67% → 96%Before kickoff +17 · On the field +29: Scoreboard +30, Timeouts +2
• NEVL 38-41 at NEV41% → 6%Before kickoff −9 · On the field −36: Scoreboard −35, Possession & field position +1
• SDSUL 17-27 vs SDSU29% → 5%Before kickoff −21 · On the field −24: Scoreboard −37, Clock −1
• ARMYW 34-29 at ARMY26% → 95%Before kickoff −24 · On the field +69: Scoreboard +54, Clock +4
• BOISL 42-52 vs BOIS14% → 33%Before kickoff −36 · On the field +18: Scoreboard −20, Possession & field position +2
• HAWL 40-42 at HAW28% → 18%Before kickoff −22 · On the field −11: Scoreboard −19, Timeouts −2
• UNLVL 35-38 at UNLV65% → 43%Before kickoff +15 · On the field −22: Clock +2, Scoreboard +2
• FRESW 17-16 vs FRES58% → 82%Before kickoff +8 · On the field +24: Scoreboard +20, Timeouts +2

Points of win probability, from San José State's side.

Closest call

SJSU 38-21 UNM (2020) - San José State dropped to a 0.9% win probability before pulling it out.