California at Texas Tech Week 1 College Football Matchup California at Texas Tech Matchup - Week 1
Sun, Dec 17 2023 · Postseason · Neutral Site · 🏟 Independence Stadium Shreveport, FL · Turf · 49,565 cap
California✈ 1,643 mi+2 hr TZ Texas Tech✈ 474 miSame TZ
Away (Neutral)
14 34
Final
Home (Neutral)
📊 Punt & Rally Projection
California
27
Texas Tech
30
P&R Line Texas Tech -3.5
P&R Total O/U 56.5
Confidence 75 Good
Vegas Texas Tech -3.5 · O/U 54.5
Matchup Prediction
Metrics disagree on this matchup
Momentum Control favors California, while Game Control favors Texas Tech. Split signals historically show weaker predictive confidence — treat as a toss-up.
⚡ Split Signal — Metrics Disagree
Momentum Control
61.3%
California wins
Lean
Game Control
50.6%
Texas Tech wins
Toss-up
Vegas Spread
Texas Tech -3.5
O/U 54.5
Bovada
Advanced Stats
Advanced factors are split · No strong agreement signal
↓ See full breakdown
🚌 California 3rd straight Road Game
California 2023 Schedule
California's 2023 Schedule
DateMatchupSpreadTotalResultO/UCover
Sat 9/2California at North Texas-5.0W58–2153.5W58–21OY
Sat 9/9California vs Auburn+5.0L10–1455.5L10–14UY
Sat 9/16California vs Idaho-14.5W31–1752.5W31–17UN
Sat 9/23California at Washington+21.0L32–5955.5L32–59ON
Sat 9/30California vs Arizona State-13.0W24–2147.5W24–21UN
Sat 10/7California vs Oregon State+7.5L40–5251.0L40–52ON
Sat 10/14California at Utah+9.0L14–3442.5L14–34ON
— Bye Week —
Sat 10/28California vs USC+10.5L49–5067.5L49–50OY
Sat 11/4California at Oregon+26.5L19–6361.5L19–63ON
Sat 11/11California vs Washington State-1.5W42–3958.5W42–39OY
Sat 11/18California at Stanford-6.5W27–1552.5W27–15UY
Sat 11/25California at UCLA+9.5W33–750.5W33–7UY
Sat 12/16California vs Texas Tech+3.5L14–3454.5L14–34UN
Texas Tech 2023 Schedule
Texas Tech's 2023 Schedule
DateMatchupSpreadTotalResultO/UCover
Sat 9/2Texas Tech at Wyoming-13.0L33–3550.5L33–35ON
Sat 9/9Texas Tech vs Oregon+4.5L30–3870.0L30–38UN
Sat 9/16Texas Tech vs Tarleton State-36.5W41–375.5W41–3UY
Sat 9/23Texas Tech at West Virginia-6.0L13–2053.5L13–20UN
Sat 9/30Texas Tech vs Houston-8.5W49–2852.0W49–28OY
Sat 10/7Texas Tech at Baylor-2.5W39–1459.5W39–14UY
Sat 10/14Texas Tech vs Kansas State-1.0L21–3857.0L21–38ON
Sat 10/21Texas Tech at BYU-3.0L14–2749.0L14–27UN
— Bye Week —
Thu 11/2Texas Tech vs TCU-2.5W35–2859.5W35–28OY
Sat 11/11Texas Tech at Kansas+3.5W16–1361.5W16–13UY
Sat 11/18Texas Tech vs UCF-2.0W24–2359.0W24–23UN
Fri 11/24Texas Tech at Texas+16.5L7–5753.5L7–57ON
Sat 12/16Texas Tech vs California-3.5W34–1454.5W34–14UY
Advanced Stats
Advanced Analytics Matchup
Matchup-adjusted (offense vs opponent defense) · 2023 season
California PPA Edge
Agreement Signals — When All Metrics Agree
Elite · 83.1% ATS
PPA + PPO + SR + Havoc
Split
Metrics disagree
Elite · 82.4% ATS
PPA + PPO + Havoc
Split
Metrics disagree
Elite · 73.9% ATS
PPA + Success Rate
Split
Metrics disagree
Individual Factors — Ranked by Predictive Strength
PPA Overall
Points added per play · Elite predictor
California #61
+0.363
Texas Tech #92
+0.355
California Edge
PPA Passing
Pass efficiency edge · Strong predictor
California #92
+0.421
Texas Tech #111
+0.452
Texas Tech Edge
Havoc Total
Def. disruption rate · Strong predictor
California #75
0.160
Texas Tech #91
0.151
TFLs, sacks, PBUs, forced fumbles — higher is better
California Edge
Points Per Opp
Drive-finishing edge · Strong predictor
California #46
+7.582
Texas Tech #70
+8.311
Texas Tech Edge
Success Rate
Play consistency edge · Solid predictor
California #88
+0.814
Texas Tech #59
+0.875
Texas Tech Edge
Field Position
Avg start (lower=better) · Solid predictor
California #18
68.8
Texas Tech #50
70.0
Avg yards from own endzone to average start — lower is better · longer bar = better field position
California Edge
Advanced stats sourced from CFBD · 2023 season · Edges are matchup-adjusted (offense vs opponent defense)
Power Ratings
Team Power Ratings
Overall · Offense · Defense ratings · Updated as season progresses
Texas Tech Rated Higher
Overall Power Rating
California
5.3
Texas Tech
27.6
Offense Rating
California
19.2
Texas Tech
29.0
Defense Rating (lower = better defense)
California
13.9
Texas Tech
1.3
Power ratings updated throughout the season as results accumulate
Momentum Control (CSS)
Consecutive Scoring Sequences Who builds scoring momentum? California Edge
Avg sequences created per game
California #72
0.82
Texas Tech #88
0.55
Avg sequences allowed per game (lower is better)
California #116
1.64
Texas Tech #75
1.18
California +0.27
CSS Edge (season-to-date)
Teams with this edge win 61.3% of games historically
Based on 11 games this season
Game Control (GC)
Win Probability Dominance Who controls games start to finish? Texas Tech Edge
Avg GC score per game (offense)
California #1
45.4
Texas Tech #1
45.8
Avg GC score allowed per game (lower is better)
California #74
38.3
Texas Tech #57
37.9
Texas Tech +0.4
GC Edge (season-to-date)
Teams with this edge win 50.6% of games historically
Based on 12 games this season
Actual Result
CSS Battle
Texas Tech
1 — 0 sequences
✗ Predicted incorrectly
GC Battle
Texas Tech
63.0 — 24.8 GC score
✓ Predicted correctly
Game Result
Texas Tech won by 20
Spread Context
ATS Historical Context
Based on 2021–2025 backtest · FBS vs FBS · Regular season

CSS and GC disagree on this matchup. When the metrics split, historical cover rates are essentially random — treat this as a coin flip against the spread.

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

Coaching Matchup
California
Justin Wilcox #1
32–37 (46%) · Yr 7 at school
OC Jake Spavital Yr 1 #1
DC Peter Sirmon Yr 3 #1
Staff Rating
0.00 #1
Texas Tech
Joey McGuire #1
9–7 (56%) · Yr 2 at school
OC Zach Kittley Yr 2 #1
DC Tim DeRuyter Yr 2 #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