California at Virginia Tech Week 9 College Football Matchup California at Virginia Tech Matchup - Week 9
Fri, Oct 24 2025 · Week 9 · 🏟 Lane Stadium Blacksburg, VA · Turf · 66,233 cap
California✈ 2,272 mi+3 hr TZ
34 42
Final
📊 Punt & Rally Projection
California
25
CAL +6.5
Virginia Tech
26
P&R Line California -0.5
P&R Total O/U 52
Confidence 90 High
Vegas Virginia Tech -6.5 · O/U 50.5
Matchup Prediction
California has the edge in this matchup
Both Momentum Control (CSS) and Game Control metrics favor California entering this game.
Momentum Control
61.3%
California wins
Lean
Game Control
75.9%
California wins
Solid
Vegas Spread
Virginia Tech -6.5
O/U 50.5
ESPN Bet
Advanced Stats
All 4 factors agree → California · 83.1% ATS historically when all four align
↓ See full breakdown
🛋 Virginia Tech Coming off BYE
California 2025 Schedule
California's 2025 Schedule
DateMatchupSpreadTotalResultO/UCover
Sat 8/30California at Oregon State+3.0W34–1551.5W34–15UY
Sat 9/6California vs Texas Southern-44.5W35–354.5W35–3UN
Sat 9/13California vs Minnesota+3.0W27–1441.5W27–14UY
Sat 9/20California at San Diego State-14.0L0–3447.5L0–34UN
Sat 9/27California at Boston College+6.0W28–2454.5W28–24UY
Sat 10/4California vs Duke+3.5L21–4554.5L21–45ON
— Bye Week —
Fri 10/17California vs North Carolina-7.5W21–1845.5W21–18UN
Fri 10/24California at Virginia Tech+6.5L34–4250.5L34–42ON
Sat 11/1California vs Virginia+6.5L21–3152.5L21–31UN
Sat 11/8California at Louisville+18.5W29–2648.5W29–26OY
— Bye Week —
Sat 11/22California at Stanford-4.5L10–3147.5L10–31UN
Sat 11/29California vs SMU+13.5W38–3553.5W38–35OY
Wed 12/24California at Hawai'i+1.5L31–3550.5L31–35ON
Virginia Tech 2025 Schedule
Virginia Tech's 2025 Schedule
DateMatchupSpreadTotalResultO/UCover
Sun 8/31Virginia Tech vs South Carolina+8.5L11–2448.5L11–24UN
Sat 9/6Virginia Tech vs Vanderbilt-2.5L20–4446.5L20–44ON
Sat 9/13Virginia Tech vs Old Dominion-5.5L26–4550.5L26–45ON
Sat 9/20Virginia Tech vs Wofford-35.5W38–651.5W38–6UN
Sat 9/27Virginia Tech at NC State+10.0W23–2157.5W23–21UY
Sat 10/4Virginia Tech vs Wake Forest-4.5L23–3051.5L23–30ON
Sat 10/11Virginia Tech at Georgia Tech+14.0L20–3555.5L20–35UN
— Bye Week —
Fri 10/24Virginia Tech vs California-6.5W42–3450.5W42–34OY
Sat 11/1Virginia Tech vs Louisville+10.5L16–2852.5L16–28UN
— Bye Week —
Sat 11/15Virginia Tech at Florida State+13.5L14–3453.5L14–34UN
Sat 11/22Virginia Tech vs Miami+18.5L17–3449.0L17–34OY
Sat 11/29Virginia Tech at Virginia+9.5L7–2753.5L7–27UN
Advanced Stats
Advanced Analytics Matchup
Matchup-adjusted (offense vs opponent defense) · 2025 season
California PPA Edge
Agreement Signals — When All Metrics Agree
Elite · 83.1% ATS
PPA + PPO + SR + Havoc
All 4 Agree
→ California
Elite · 82.4% ATS
PPA + PPO + Havoc
3 Agree
→ California
Elite · 73.9% ATS
PPA + Success Rate
Both Agree
→ California
Individual Factors — Ranked by Predictive Strength
PPA Overall
Points added per play · Elite predictor
California #98
+0.403
Virginia Tech #70
+0.341
California Edge
PPA Passing
Pass efficiency edge · Strong predictor
California #78
+0.648
Virginia Tech #113
+0.300
California Edge
Havoc Total
Def. disruption rate · Strong predictor
California #80
0.151
Virginia Tech #116
0.132
TFLs, sacks, PBUs, forced fumbles — higher is better
California Edge
Points Per Opp
Drive-finishing edge · Strong predictor
California #66
+8.047
Virginia Tech #70
+7.367
California Edge
Success Rate
Play consistency edge · Solid predictor
California #95
+0.861
Virginia Tech #84
+0.839
California Edge
Field Position
Avg start (lower=better) · Solid predictor
California #122
72.9
Virginia Tech #124
73.2
Avg yards from own endzone to average start — lower is better · longer bar = better field position
California Edge
Advanced stats sourced from CFBD · 2025 season · Edges are matchup-adjusted (offense vs opponent defense)
Power Ratings
Team Power Ratings
Overall · Offense · Defense ratings · Updated as season progresses
Virginia Tech Rated Higher
Overall Power Rating
California
5.3
Virginia Tech
5.9
Offense Rating
California
19.2
Virginia Tech
18.4
Defense Rating (lower = better defense)
California
14.0
Virginia Tech
12.5
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 #56
0.83
Virginia Tech #106
0.50
Avg sequences allowed per game (lower is better)
California #80
1.17
Virginia Tech #98
1.67
California +0.33
CSS Edge (season-to-date)
Teams with this edge win 61.3% of games historically
Based on 6 games this season
Game Control (GC)
Win Probability Dominance Who controls games start to finish? California Edge
Avg GC score per game (offense)
California #1
54.9
Virginia Tech #1
33.2
Avg GC score allowed per game (lower is better)
California #62
32.1
Virginia Tech #116
52.8
California +21.7
GC Edge (season-to-date)
Teams with this edge win 75.9% of games historically
Based on 7 games this season
Actual Result
CSS Battle
California
2 — 3 sequences
✓ Predicted correctly
GC Battle
Virginia Tech
44.8 — 30.4 GC score
✗ Predicted incorrectly
Game Result
Virginia Tech won by 8
✗ Model missed it
Spread Context
ATS Historical Context
Based on 2021–2025 backtest · FBS vs FBS · Regular season

Both metrics agree on California 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
42–49 (46%) · Yr 9 at school
OC Bryan Harsin Yr 1 #1
DC Vacant Yr 1 #1
Staff Rating
0.00 #1
Virginia Tech
Brent Pry #1
16–20 (44%) · Yr 4 at school
OC Philip Montgomery Yr 1 #1
DC Sam Siefkes Yr 1 #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