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California Golden Bears

ACC·1-1·
Elo
1349#107
SP+
-3.4#77
FPI
-3.0
AP
NR
Nextvs Wagner · Wk 3
Talent #33 (751.9)Recruiting class #5658% production returning

Roster · 112 players

FR 34SO 28JR 24SR 26
#PlayerPosClHtWt
2EJ CaminongQBSO6'2"220
3Jaron-Keawe SagapoluteleQBSO6'3"225
11Jackson BrousseauQBJR6'4"225
14Dominic IngrassiaQBSO6'4"215
17Alonzo EsparzaQBFR6'0"190
18Nainoa LopesQBFR6'3"185
1Carter VargasRBSO5'11"205
13Victor SantinoRBFR5'11"200
20Ashten EmoryRBSO5'11"210
21Carson Perry-SmithRBSO5'11"195
24Adam MohammedRBJR6'0"220
25Anthony LeagueRBFR6'0"215
33Dean-Taylor ChapmanRBJR5'9"185
4Jordan KingWRSR6'2"215
5QuaRon AdamsWRSR5'7"165
6Kyion GrayesWRJR6'0"190
7Chase HendricksWRSR6'0"195
9Ian StrongWRSR6'4"215
10Cooper PerryWRSO6'1"200
15Mark HamperWRJR6'2"205
16Kai MezaWRFR6'1"190
19Trevor RogersWRSO6'3"195
80EJ MorganWRFR6'0"160
81Tyree SamsWRFR5'8"180
82Cole BosciaWRSR6'3"215
87Meyer SwinneyWRFR6'3"205
0Dorian ThomasTEJR6'4"255
8Rico WalkerTESR6'4"250
22Taimane PurcellTEFR6'4"245
39Michael CooleyTEJR6'7"230
44John Tofi Jr.TEFR6'5"240
85Mason MiniTEJR6'4"245
88Sosaia NoaTEFR6'3"225
90Jack OlyphantTESO6'4"240
51Kahlee TafaiOLJR6'5"340
52Elisha FaamatuainuOLFR6'4"335
54Frederick Williams IIIOLJR6'5"335
55Daniel McMorrisOLFR6'6"265
56Tyson RuffinsOLJR6'2"310
58Ashton RiveraOLJR6'2"315
60Roger VanderhoefOLFR6'7"385
65Justin HasenhuetlOLFR6'5"290
66Sam BjerkeOLSO6'5"310
68Jojo GenovaOLFR6'5"285
70Mykeal RabessOLJR6'6"320
71Sioape VatikaniOLSR6'4"330
72Ben HowardOLFR6'4"325
73Kamo'I Huihui-WhiteOLFR6'5"330
74Michael KlisiewiczOLFR6'6"310
75Jacob AropOLSO6'6"330
76Bastian SwinneyOLSR6'6"315
77Jimothy Lewis Jr.OLSO6'6"315
78Lamar RobinsonOLSR6'3"290
79Esaiah WongOLFR6'5"310
43Lucky SchirmerDLFR6'2"290
44Jericho JohnsonDLSO6'4"345
51Jayden WilliamsDLJR6'2"315
55BJ CanadyDLSO6'5"280
56Legend JourneyDLSO6'2"275
59Nemyah TelonaDLFR6'1"310
61Frank Fanua Jr.DLFR6'3"220
91Dabe NwudeDLFR6'2"260
92LeBron WilliamsDLFR6'2"285
93R.J. StephensDLJR6'1"285
94Stanley Saole-McKenzieDLSR6'2"350
96Derek WilkinsDLSR6'5"310
97Michael-Anthony OkwuraDLSO6'3"310
98Nate BurrellDLSR6'2"285
99Ashun ShepphardDLSR6'3"290
0Solomon WilliamsLBSO6'2"245
3Kamar MothudiLBSO6'3"245
4Justin BeadlesLBSR6'5"275
6Emmanuel OkoyeLBSO6'5"245
9AJ TuiteleLBFR6'2"220
10Jayden WayneLBSR6'5"255
15Joshua PierceLBJR6'4"265
18Serigne TounkaraLBSO6'3"245
19Odera OkakaLBSR6'4"230
21Aaron HamptonLBJR6'1"235
32Tristan JerniganLBSO6'0"230
33JD McKinleyLBFR6'2"250
36Jude McLellanLBSO6'3"240
41Jaxon PyattLBFR6'2"230
45Beckham BarneyLBFR6'1"225
57BJ JonesLBJR6'2"230
1Ricky FletcherDBSR6'3"210
2Kingston LopaDBSO6'5"210
5Marquis Groves-KillebrewDBSR6'0"190
7Daniel HarrisDBSR6'3"200
8Jasiah WagonerDBJR5'11"175
11Dayday AupiuDBSO6'2"170
13Jae'on YoungDBFR5'11"175
14Aiden ManutaiDBSO5'11"205
16Michael Hurst Jr.DBSR6'0"200
17Jordan SanfordDBSR6'0"195
20Cam SidneyDBSR5'11"185
22Tristan DunnDBSR6'5"210
23Isaiah CrosbyDBJR5'10"190
24Quimari ShemwellDBJR5'11"175
25Khamani HudsonDBFR6'0"185
26Niles DavisDBFR5'11"190
28Tre' HarrisonDBFR6'0"190
34Tobey WeydemullerDBSO5'10"185
38Nate EscaladaDBJR6'0"195
33Towns McGoughPKSO6'0"200
37Erik PetersPKFR6'1"195
91Chase MeyerPKSR5'10"185
27Jacob JohnsonPJR6'4"250
29Angus DaviesPSR6'1"210
50David BirdLSSR6'0"205
53Jordan FrankeLSJR5'10"205
59Ewan ArechaederraLSSO5'11"210

Team Statistics · per game, with national FBS rank

Points / game
22.5
scoring offense
Points allowed
31.5
scoring defense
Differential
-9.0
per game
Offense
Total yards / game
329.5#108
Yards / play
4.5#121
Passing yards / game
236.5#65
Rushing yards / game
93.0#120
First downs / game
19.5#85
3rd down %
42.4%#74
4th down %
0.0%#108
Time of possession
30:20#71
Defense
Yards allowed / game
448.5#121
Yards / play allowed
6.4#114
Pass yards allowed / game
251.0#111
Rush yards allowed / game
197.5#120
3rd down % allowed
46.4%#110
Sacks
5#29
Tackles for loss
7#77
Turnovers & Discipline
Turnover margin
+1#36
Takeaways
4#14
Giveaways
3#95
Penalties / game
7.5#92
Penalty yards / game
73.0#111

Rank is national among all FBS teams (#1 = best), oriented so higher rank = better even for defensive and discipline metrics. Bars show percentile.

Scouting Report · 2 games in

California is in year 1 under Tosh Lupoi. The strengths are defensive, led by 34th at keeping opponents off schedule through the air. The way in is 134th at stuffing runs at the line, and they are 133rd at defending the run.

California has played 2 games against an average slate, adjusted for here. That football carries about 26% of what is below; the rest is still the preseason projection.

Strengths

  • Defensestaying on schedule through the air
    33%
    #34 of 138

Soft spots

  • Defensegetting stopped at the line
    12.9%
    #134 of 138
  • Defenserunning it
    +0.32
    #133 of 138
  • Offenserunning it
    -0.11
    #130 of 138

Each bar is where this team sits in the country. Before the season has produced enough football these are PROJECTIONS — last season regressed to the mean, plus talent, returning production, recruiting and whether the staff is the same one — and the season replaces them as it is played. Head coaches only — there is no free feed for coordinators, so on a program where the head coach does not call the offense this describes the staff he hired. Play-calling identity is a style, not a grade: throwing more than the situations warrant is not better than throwing less than they warrant.

2026 Season Projection

model win prob · 9 to play
5.45.6
projected final record (now 11)
Exp. wins left
4.4
of 9 games
Bowl odds
48%
reach 6 wins
Best odds
79%
vs Stanford
Toughest
13%
vs Virginia

How the season could finish · 2026 · chance of each final win total · 9 games left

Every remaining game simulated from the model's win probability for it. Tallest bar is the single likeliest finish, not a prediction that it happens.

12345678910
final winstallest bar = 27% chance
Likeliest finish 5-6 (27%)Bowl eligible 48% · marked on the axis at 6

Player Value

EPA contribution by position group + estimated NIL market value (derived from position rates and on-field production — not actual deal figures).

Unit Value — Total EPA
QBJackson Brousseau, Jaron-Keawe Sagapolutele
+12.6 EPA
TEMason Mini, Taimane Purcell
+7.4 EPA
WRKyion Grayes, Jordan King +4
+5.7 EPA
RBAdam Mohammed, Carter Vargas +2
+0.1 EPA

Total EPA produced by each positional group this season. OL value is captured via the rush/pass efficiency of skill players; OL-specific EPA isn't separately reported.

Estimated NIL Market Value
ESTIMATED
EPA +13.60.169/play80 snaps
EPA +4.30.073/play58 snaps

Estimated from position-group market rates and on-field EPA contribution. Actual NIL valuations depend on social media following, brand fit, and market negotiations — these figures are directional only.

The Five Factors

ranked vs. FBS · bar = better
Efficiency (PPA)
Off0.0617th#115
Def0.1732nd#94
Explosiveness
Off1.3365th#49
Def1.3431st#95
Field position
Off73.980th#29
Def66.992nd#12
Finishing (pts/opp)
Off3.4531st#95
Def3.6334th#91
Turnovers
Won 4Lost 3
Margin +1

Opponent-adjusted efficiency

EPA/play vs. schedule
Offense
Defense
Off · pass
0.1928th#100
Off · rush
-0.1112th#121

Pass vs. rush (PPA)

Rushing
Off-0.1111th#123
Def0.326th#130
Passing
Off0.1926th#103
Def0.1265th#49

Trenches & disruption

Line yards (off)
2.41#116
2nd-level / open-field
0.83 / 0.27
Power / stuff (off)
71.4% / 25.0%
Havoc — total (def)
15.0%#85
Havoc — front 7 / DB
6.4% / 8.6%

Standard vs. passing downs

Pro
Std downs
Off-0.02
Def0.16
Pass downs
Off0.19
Def0.19

PPA on each down type (off vs. def).

Opponent-adjusted by down

Pro
1st2nd3rd
Offense-0.06#107-0.15#1160.62#66
Defense0.09#102-0.03#440.49#87

Elo Trajectory

UCLAFinal
Elo rating 14061353-53 over season

Team Fingerprint · 2026 · 43 opponent-adjusted metrics · percentile vs 138 FBS teams

Plot these →
worst in FBSbest

Efficiency

  • Offense EPA/play0.1334th
  • Defense EPA/play allowed0.429th
  • Offense success rate34%14th
  • Defense success rate allowed57%3rd

Downs

  • Offense success — standard downs34%7th
  • Offense success — passing downs33%52nd
  • Defense success allowed — standard downs67%1st
  • Defense success allowed — passing downs18%78th

Explosiveness

  • Offense explosiveness1.584th
  • Defense explosiveness allowed1.343rd
  • Offense explosiveness — standard downs1.169th
  • Offense explosiveness — passing downs2.162nd

Trenches

  • Offense line yards2.520th
  • Defense line yards allowed4.81st
  • Offense highlight yards0.3322nd
  • Defense highlight yards allowed3.71st
  • Offense power success0.6738th
  • Defense power success allowed1.023rd
  • Offense stuff rate0.2129th
  • Defense stuff rate0.031st

Third down

  • Third down conversion60%85th
  • Third down distance faced7.720th
  • Third down conversion allowed45%29th
  • Third down distance forced7.248th

Halves

  • Net success rate — first half-0.277th
  • Net success rate — second half-0.1513th

Drives

  • Points per drive1.435th
  • Points per drive allowed3.524th
  • Average starting field position225th
  • Opponent starting field position408th
  • Available yards gained39%26th
  • Available yards allowed59%27th
  • Scoring opportunities per drive50%7th
  • Scoring opportunities allowed92%22nd
  • Points per scoring opportunity2.855th
  • Points allowed per opportunity3.821st
  • Three-and-out rate25%49th
  • Three-and-outs forced33%70th

Roster

  • Returning usage53%64th
  • Returning EPA18975th
  • Team talent composite75277th
  • Recruiting class rank56.060th
  • Recruiting class points20360th

Every metric is opponent-adjusted and ranked so that higher is always better — a defensive rate that is good when low is ranked accordingly. Sack and tackle-for-loss composition are deliberately absent: their relationship to team quality is a measured null, so they carry a style rather than a rank, and they appear in the pressure signature instead.

Intelligence Report

Offensive DNA

Pass-dominant offense — below average EPA/play nationally
EPA/play
+0.057#115 · bottom 20%
Pass EPA/play
+0.185#103
Rush EPA/play
-0.112#123
Explosiveness
1.328#49
Pts/opportunity
3.45#95
Success rate
34.2%

Pass efficiency edge: 0.297 EPA/play

🛡

Defensive Identity

Disruptive defense — allowing above-average EPA/play
EPA/play allowed
+0.169#94 · below avg
Havoc rate (total)
15.0%#85
Front-7 havoc
6.4%
DB havoc
8.6%
Big play rate allowed
1.341#95
Success rate allowed
41.4%

Disruption comes primarily from the secondary.

📊

Season Signature

22.5 PPG offense, 31.5 allowed — -9.0 margin/game
Points per game
22.5
Points allowed/game
31.5
Scoring margin/game
-9.0
Turnover margin
+1won 4 · lost 3
Production returning
58%
Talent rank (247)
#33

1-1 record through 2 games.

Team Shape · percentile vs. FBS · dashed = 50th

OFFENSE17thEXPLOSIVENESS65thFINISHING31thFIELD POS80thDEFENSE32thHAVOC39th50th100th
Offense
17th
Explosiveness
65th
Finishing
31th
Field Pos
80th
Defense
32th
Havoc
39th

Each axis = national percentile rank. 100th = best in FBS, 0th = worst. Defense and Havoc are oriented so higher = better.

CORE efficiency · situation and opponent removed

Points per 100 plays above average, after the game state is regressed out of every snap and the schedule is solved out across the whole league. The version of this team’s efficiency that can be compared to a team it never played.

Overall
-9.4
#106
Offense
-3.3
#96
Defense
+6.1
#123
Full CORE ratings →

What a possession is worth · 12 drives

MeasureOffenseDefense
Points per drive1.423.50
Starting field positionown 21.7own 39.8
Available yards39.1%59.2%
Scoring opportunities50.0%91.7%
Points per opportunity2.833.82
Three-and-out rate25.0%33.3%
Every team’s drive efficiency →

Play-calling identity

Against what the league calls from the same down, distance, field position, score and clock — so this is the staff, not the game script.

Pass rate
54.9%
Expected, given the spots
54.9%
Over expected
-0.0
Fourth down vs peers
+8
Fourth down vs the model
+67
All play-calling tendencies →

National Landscape · 2026 FBS · offense vs. defense EPA/play

Each dot = one FBS team. California is highlighted. Tap or hover a dot for details.

ELITEDEF. FORTRESSOFF. POWERHOUSEREBUILDING-0.100.00+0.10+0.20+0.30-0.050.00+0.10+0.20Offensive EPA/play← worsebetter →Defensive EPA allowed/play← worsebetter →

Similar Programs

Teams with the closest offense + defense efficiency profile to California in 2026

by EPA/play distance
WyomingSP+ -15.2
Off EPA/play +0.071Def EPA/play +0.169Elo 1300
Match
99%
UNLVSP+ +2.3
Off EPA/play +0.041Def EPA/play +0.186Elo 1589
Match
99%
Bowling GreenSP+ -12.8
Off EPA/play +0.025Def EPA/play +0.147Elo 1340
Match
98%
Boston CollegeSP+ -7.4
Off EPA/play +0.102Def EPA/play +0.148Elo 1379
Match
98%
Eastern MichiganSP+ -15.6
Off EPA/play +0.041Def EPA/play +0.117Elo 1353
Match
97%
RiceSP+ -10.4
Off EPA/play +0.060Def EPA/play +0.229Elo 1196
Match
97%

Similarity = normalized Euclidean distance on season offensive and defensive EPA/play. Teams within ±0.02 EPA/play on both units score >90%.

Program Trajectory · CORE rating · 20152026 · points per game vs an average FBS team

2015: +14.0, #25 of 1282016: -3.9, #81 of 1282017: -6.5, #85 of 1302018: +0.3, #62 of 1302019: +0.7, #59 of 1302020: -7.7, #89 of 1242021: -1.2, #78 of 1302022: -4.6, #82 of 1312023: -0.6, #64 of 1332024: +6.9, #42 of 1342025: -6.6, #85 of 1362026: -9.4, #106 of 138
20152026
Now -9.4 · #106 of 138Best +14.0 in 2015Worst -9.4 in 2026

Program History

recent seasons
YearOverallConfWin %xWLuck
20260-10-0
0%
0.0-0.0
20257-64-4
54%
6.2+0.8
20246-72-6
46%
7.0-1.0
20236-74-5
46%
6.4-0.4
20224-82-7
33%
3.7+0.3
20215-74-5
42%
6.1-1.1
20201-31-3
25%
1.1-0.1
20198-54-5
62%
7.8+0.2
20187-64-5
54%
6.3+0.7
20175-72-7
42%
5.4-0.4

xW = expected wins from per-game dominance. Luck = actual − expected (positive = won close games).

0.3%of 50,000 simulated 2026 seasons end with them in the field

0-1 so far, projected to finish 4.6-7.4.

If they finish with…

40%
2 losses
3.7%
3 losses
0.4%
4 losses

Their chance of making it at each final loss count.

down 3.5 points since preseasonlost 24-45 to UCLA against an expected margin of 0, so 21.0 against the number.

  • At 2 losses they are 40% where the average ACC team is 44%.
  • The ACC takes 1.54 bids in an average season, and four or more in 0.7%.

California’s own turning points

Points of playoff probability between winning and losing.

  • wk8at SMU1.4
  • wk11at Virginia1.4
  • wk13vs Pittsburgh1.2
  • wk6vs Virginia Tech0.9
  • wk9at NC State0.8
  • wk4vs Clemson0.8

Who to root for

Games California is not in that move its odds most. Same units, much smaller scale.

  • wk5Clemson over Miami0.2
  • wk5Arkansas over Texas A&M0.2
  • wk7Ball State over Bowling Green0.2
  • wk11Duke over Miami0.2
  • wk2Penn State over Temple0.2
  • wk2Sacred Heart over Massachusetts0.2
The full playoff picture →

ACC

0-0 in league play, projected 3.3-5.714 of 17 by title odds
0.3%
Wins the ACC
1.3%
Reaches the title game

The ACC sends its top two by conference winning percentage, head-to-head breaking a tie. The last berth is level on percentage in 37% of simulated seasons, so a tiebreaker decides it about that often.

  • wk8California at SMU1.1

Points of title probability riding on each result. The whole ACC race →

If not the playoff, then

32%
Bowl eligible
31%
Placed in a bowl
0.3%
In the playoff
69%
Season over in November

California is 0-1 and needs 6 more wins from 11 games to reach the six that make a team eligible — at most one of which may come against an FCS opponent. In 1.3% of seasons they get there and still go nowhere: there are more eligible teams than seats.

  • Military Bowl4.9%
  • Fenway Bowl4.8%
  • Pinstripe Bowl3.9%
  • Pop-Tarts Bowl3.1%
  • Birmingham Bowl2.8%
  • Sun Bowl2.6%

Every bowl, and how each one picks →

Recruiting Pipelines

since 2010

Of the 170 high-school programs with a pipeline page here, 14 have sent California a player since 2010 — 44 signees between them. Where they signed, not where they were offered, and not a complete list of California's feeder schools: only these 170 have the outcome history to measure.

High schoolSignedDrafted
Corona CentennialCA61
De La SalleCA50
Junipero SerraCA50
WestlakeGA50
LibertyNV40
SkylineTX40
St. John BoscoCA40
CentennialCA20
All 170 high-school pipelines →
✓/✗ = whether our pregame model picked the winner. Win % & projections from the Gridpex model. Data: CollegeFootballData.