California at SMU Week 14 College Football Matchup California at SMU Matchup - Week 14
Sat, Nov 30 2024 · Week 14 · 🏟 Gerald J. Ford Stadium University Park, TX · Turf · 32,000 cap
California✈ 1,471 mi+2 hr TZ
6 38
Final
SMU
Home
📊 Punt & Rally Projection
California
20
SMU
34
P&R Line SMU -14.5
P&R Total O/U 54
Confidence 90 High
Vegas SMU -11.5 · O/U 54.5
Matchup Prediction
SMU has the edge in this matchup
Both Momentum Control (CSS) and Game Control metrics favor SMU entering this game.
Momentum Control
58.4%
SMU wins
Lean
Game Control
76%
SMU wins
Strong
Vegas Spread
SMU -11.5
O/U 54.5
ESPN Bet
Advanced Stats
All 4 factors agree → SMU · 83.1% ATS historically when all four align
↓ See full breakdown
California 2024 Schedule
California's 2024 Schedule
DateMatchupSpreadTotalResultO/UCover
Sat 8/31California vs UC Davis-20.5W31–1356.5W31–13UN
Sat 9/7California at Auburn+11.5W21–1452.5W21–14UY
Sat 9/14California vs San Diego State-18.5W31–1048.5W31–10UY
Sat 9/21California at Florida State+3.0L9–1444.0L9–14UN
— Bye Week —
Sat 10/5California vs Miami+10.0L38–3954.0L38–39OY
Sat 10/12California at Pittsburgh+3.5L15–1757.5L15–17UY
Sat 10/19California vs NC State-9.5L23–2446.0L23–24ON
Sat 10/26California vs Oregon State-13.0W44–751.0W44–7UY
— Bye Week —
Fri 11/8California at Wake Forest-7.5W46–3654.5W46–36OY
Sat 11/16California vs Syracuse-10.5L25–3358.0L25–33UN
Sat 11/23California vs Stanford-15.0W24–2153.5W24–21UN
Sat 11/30California at SMU+11.5L6–3854.5L6–38UN
Wed 12/18California vs UNLV+3.0L13–2445.0L13–24UN
SMU 2024 Schedule
SMU's 2024 Schedule
DateMatchupSpreadTotalResultO/UCover
Sat 8/24SMU at Nevada-28.0W29–2455.5W29–24UN
Sat 8/31SMU vs Houston Christian-30
Fri 9/6SMU vs BYU-12.5L15–1855.5L15–18UN
— Bye Week —
Sat 9/21SMU vs TCU+1.0W66–4258.5W66–42OY
Sat 9/28SMU vs Florida State-6.0W42–1646.0W42–16OY
Sat 10/5SMU at Louisville+6.5W34–2755.0W34–27OY
— Bye Week —
Sat 10/19SMU at Stanford-16.5W40–1052.5W40–10UY
Sat 10/26SMU at Duke-11.5W28–2749.5W28–27ON
Sat 11/2SMU vs Pittsburgh-7.0W48–2555.5W48–25OY
— Bye Week —
Sat 11/16SMU vs Boston College-19.0W38–2854.5W38–28ON
Sat 11/23SMU at Virginia-11.5W33–754.5W33–7UY
Sat 11/30SMU vs California-11.5W38–654.5W38–6UY
Sat 12/7SMU vs Clemson-2.5L31–3456.5L31–34ON
Sat 12/21SMU at Penn State+9.0L10–3852.5L10–38UN
Advanced Stats
Advanced Analytics Matchup
Matchup-adjusted (offense vs opponent defense) · 2024 season
SMU PPA Edge
Agreement Signals — When All Metrics Agree
Elite · 83.1% ATS
PPA + PPO + SR + Havoc
All 4 Agree
→ SMU
Elite · 82.4% ATS
PPA + PPO + Havoc
3 Agree
→ SMU
Elite · 73.9% ATS
PPA + Success Rate
Both Agree
→ SMU
Individual Factors — Ranked by Predictive Strength
PPA Overall
Points added per play · Elite predictor
California #79
+0.202
SMU #38
+0.376
SMU Edge
PPA Passing
Pass efficiency edge · Strong predictor
California #72
+0.354
SMU #19
+0.582
SMU Edge
Havoc Total
Def. disruption rate · Strong predictor
California #42
0.178
SMU #29
0.185
TFLs, sacks, PBUs, forced fumbles — higher is better
SMU Edge
Points Per Opp
Drive-finishing edge · Strong predictor
California #125
+6.156
SMU #25
+7.643
SMU Edge
Success Rate
Play consistency edge · Solid predictor
California #88
+0.782
SMU #53
+0.845
SMU Edge
Field Position
Avg start (lower=better) · Solid predictor
California #59
70.4
SMU #26
68.9
Avg yards from own endzone to average start — lower is better · longer bar = better field position
SMU Edge
Advanced stats sourced from CFBD · 2024 season · Edges are matchup-adjusted (offense vs opponent defense)
Power Ratings
Team Power Ratings
Overall · Offense · Defense ratings · Updated as season progresses
SMU Rated Higher
Overall Power Rating
California
5.3
SMU
16.2
Offense Rating
California
19.2
SMU
26.0
Defense Rating (lower = better defense)
California
13.9
SMU
9.9
Power ratings updated throughout the season as results accumulate
Momentum Control (CSS)
Consecutive Scoring Sequences Who builds scoring momentum? SMU Edge
Avg sequences created per game
California #71
1.20
SMU #25
1.30
Avg sequences allowed per game (lower is better)
California #89
0.80
SMU #22
0.30
SMU +0.10
CSS Edge (season-to-date)
Teams with this edge win 58.4% of games historically
Based on 10 games this season
Game Control (GC)
Win Probability Dominance Who controls games start to finish? SMU Edge
Avg GC score per game (offense)
California #1
45.9
SMU #1
67.2
Avg GC score allowed per game (lower is better)
California #81
36.3
SMU #15
15.6
SMU +21.3
GC Edge (season-to-date)
Teams with this edge win 76% of games historically
Based on 11 games this season
Actual Result
CSS Battle
SMU
4 — 1 sequences
✓ Predicted correctly
GC Battle
SMU
89.1 — 4.6 GC score
✓ Predicted correctly
Game Result
SMU won by 32
✓ Model called it
Spread Context
ATS Historical Context
Based on 2021–2025 backtest · FBS vs FBS · Regular season

Both metrics agree on SMU with a large edge. Historically, dominant teams like this are fully priced into the spread — the agreed-upon team covers just 50.2% of the time. The metrics predict game control better than they beat the number.

ATS data is informational only. Past cover rates do not guarantee future results.

Coaching Matchup
California
Justin Wilcox #1
36–43 (46%) · Yr 8 at school
OC Mike Bloesch Yr 1 #1
DC Peter Sirmon Yr 3 #1
Staff Rating
0.00 #1
SMU
Rhett Lashlee #1
18–10 (64%) · Yr 3 at school
OC Casey Woods Yr 3 #1
DC Scott Symons Yr 3 #1
Staff Rating
0.00 #1
About these metrics
Advanced Stats shows matchup-adjusted factor edges (offense vs opponent defense). Combination signals — when PPA, PPO, Success Rate, and Havoc all point the same direction — have historically predicted the SU winner in 95–97% of games and the ATS winner in 82–83% of games (2021–2025, FBS vs FBS, regular season).
Impact: Advanced Stats are the best performance based metric used to predict the outcome of games.

Momentum Control (CSS) measures consecutive scoring sequences — when a team scores, holds the opponent scoreless, then scores again. Teams entering a game with a CSS edge of +1.0 or more have won 71–78% of games historically (2021–2025, FBS vs FBS).
Impact: Momentum Control is a great measure for predicting game outcome but NOT an ATS advantage, data shows this is already considered when lines are set.

Game Control (GC) measures win probability dominance — how thoroughly a team controlled the game from start to finish. Teams with a GC edge of +12 or more have won 67–76% of games historically. When both metrics agree, combined confidence is higher. When they split, treat as a lean at best.
Impact: Game Control is another great measure for predicting game outcome but NOT an ATS advantage, data shows this is already considered when lines are set.

Power Ratings are a custom-built composite of a Teams Talent, Experience & Production, Coaching & Performance Metrics. These are updated constantly with roster changes, performance once the games start for the 2026 season, injuries the team is dealing with and scheduling situations.
Impact: There are a wide range of power ratings available, we think ours is the best, you can decide for yourself