UNLV

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+0.0526th
  Defense+0.1717th
• 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.
  Offense40.9%29th
  Defense47.9%10th
• Explosiveness

  Average EPA on the successful snaps: how big the good plays were.
  Offense+1.2676th
  Defense+1.1757th
• Rushing EPA

  EPA per designed run.
  Offense+0.0439th
  Defense+0.178th
• Passing EPA

  EPA per pass play.
  Offense+0.0832nd
  Defense+0.1840th
• Standard downs

  Success rate on downs where either a run or a pass makes sense, like 1st and 10 or 3rd and 2.
  Offense44.3%17th
  Defense54.0%6th
• Passing downs

  Success rate on downs that all but force a pass, like 2nd and 8 or longer, or 3rd and 5 or longer.
  Offense34.1%51st
  Defense33.6%45th
• Line yards

  Rushing yards per carry credited to the offensive line, weighting the first few yards most.
  Offense2.7430th
  Defense3.1913th
• Stuff rate

  Share of runs stopped at or behind the line of scrimmage.
  Offense21.1%31st
  Defense19.2%41st
• Havoc

  Share of snaps with a tackle for loss, sack, forced fumble, interception or pass breakup.
  Offense1.9%56th
  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 UNLV 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
   NIU
2. L
   UCLA
3. L
   MICH
4. W
   IDST
5. W
   NEV
6. L
   SJSU
7. L
   FRES
8. L
   BOIS
9. W
   HAW
10. L
    CSU
11. L
    SDSU
12. L
    WYO

Bars above the line: better than expected for UNLV.

Players, 2015

1. Blake DeckerQB200 plays · +0.250 pts/play · 99th of 205 QBs
   0.93WAR0.63 to 1.26
2. Kurt PalandechQB166 plays · +0.211 pts/play · 117th of 205 QBs
   0.65WAR0.35 to 0.98
3. Devonte BoydWR72 plays · +0.225 pts/play · 24th of 411 WRs
   0.30WAR0.18 to 0.44
4. Logan YunkerP48 plays · +0.223 pts/play · 7th of 92 punters
   0.20WAR0.10 to 0.30
5. Keith WhitelyRB129 plays · +0.080 pts/play · 130th of 333 RBs
   0.19WAR0.09 to 0.28
6. Lexington ThomasRB64 plays · +0.118 pts/play · 167th of 333 RBs
   0.14WAR0.10 to 0.19
7. Kendal KeysWR49 plays · +0.119 pts/play · 187th of 411 WRs
   0.11WAR0.04 to 0.18
8. Xzaviar CampbellRB62 plays · +0.094 pts/play · 195th of 333 RBs
   0.11WAR0.06 to 0.15

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 UNLV'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.
  333333113th of 128Roster talent: 333, 113th of 128 in FBS
• Recruiting

  Average 247Sports class score over this season's class and the three before it.
  105105112th of 128Recruiting: 105, 112th of 128 in FBS
• Returning production

  Share of last season's production (expected points added) by players still on the roster.
  74%74%41st of 127Returning production: 74%, 41st of 127 in FBS
• SP+ rating

  The result: Bill Connelly's opponent-adjusted rating, points per game better than an average FBS team.
  −16.2−16.2116th of 128SP+ rating: −16.2, 116th 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 UNLV'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 0.13 of the 0.22 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 FRESQ4 1:27 4th & 6 at FRES 32, down 3Went for it; the numbers favored a field goal−6.0 pts
2. vs HAWQ3 3:53 4th & 1 at UNLV 30, up 10Punted; the numbers favored going for it−2.5 pts
3. vs BOISQ3 12:32 4th & 1 at UNLV 19, down 7Punted; the numbers favored going for it−1.6 pts
4. at FRESQ3 0:54 4th & 1 at UNLV 34, up 11Punted; the numbers favored going for it−1.4 pts
5. at NIUQ3 9:05 4th & 2 at NIU 16, tiedKicked a field goal; the numbers favored going for it−1.1 pts
6. at WYOQ4 2:20 4th & 23 at UNLV 1, down 7Went for it; the numbers favored punting (close call)−1.0 pts
7. vs HAWQ2 14:56 4th & 1 at UNLV 43, up 7Punted; the numbers favored going for it (close call)−0.8 pts
8. at NEVQ3 6:50 4th & 4 at NEV 48, up 10Punted; the numbers favored going for it (close call)−0.8 pts

Record vs. expectation, 2015

101st of 128 FBS teams at beating the model's pregame expectations

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

1. L

   NIU
2. L

   UCLA
3. L

   MICH
4. W

   IDST
5. W

   NEV
6. L

   SJSU
7. L

   FRES
8. L

   BOIS
9. W

   HAW
10. L

    CSU
11. L

    SDSU
12. L

    WYO

What moved it, 2015

Every game starts at UNLV'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−1.13
• Clock+0.15
• Timeouts−0.22
• Less the pregame edge, counted before kickoff+0.23

Game by game

• NIUL 30-38 at NIU14% → 4%Before kickoff −36 · On the field −10: Scoreboard −19, Possession & field position −1
• UCLAL 3-37 vs UCLA3% → 0%Before kickoff −47 · On the field −3: Scoreboard −7
• MICHL 7-28 at MICH2% → 0%Before kickoff −48 · On the field −2: Scoreboard −4
• IDSTW 80-8 vs IDST84% → 100%Before kickoff +34 · On the field +16: Scoreboard +19
• NEVW 23-17 at NEV24% → 94%Before kickoff −26 · On the field +70: Scoreboard +55, Clock +3
• SJSUL 27-33 vs SJSU36% → 10%Before kickoff −14 · On the field −26: Scoreboard −38, Timeouts −16
• FRESL 28-31 at FRES64% → 8%Before kickoff +14 · On the field −57: Scoreboard −37, Timeouts −3
• BOISL 27-55 vs BOIS10% → 0%Before kickoff −40 · On the field −9: Scoreboard −14
• HAWW 41-21 vs HAW66% → 100%Before kickoff +16 · On the field +34: Scoreboard +34, Timeouts +1
• CSUL 35-49 at CSU34% → 1%Before kickoff −16 · On the field −33: Scoreboard −33, Timeouts −2
• SDSUL 14-52 vs SDSU21% → 0%Before kickoff −29 · On the field −21: Scoreboard −27, Clock −1
• WYOL 28-35 at WYO59% → 3%Before kickoff +9 · On the field −56: Scoreboard −40, Timeouts −3

Points of win probability, from UNLV's side.

Closest call

UNM 20-31 UNLV (2022) - UNLV dropped to a 0.6% win probability before pulling it out.