Virginia Tech at Virginia Week 14 College Football Matchup Virginia Tech at Virginia Matchup - Week 14
Sat, Nov 29 2025 · Week 14 · 🏟 Scott Stadium Charlottesville, VA · Turf · 61,500 cap
Virginia Tech✈ 118 miSame TZ
7 27
Final
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📊 Punt & Rally Projection
Virginia Tech
16
UVA -9.5
Virginia
36
P&R Line Virginia -20
P&R Total O/U 52
Confidence 90 High
Vegas Virginia -9.5 · O/U 53.5
Matchup Prediction
Virginia has the edge in this matchup
Both Momentum Control (CSS) and Game Control metrics favor Virginia entering this game.
Momentum Control
58.4%
Virginia wins
Lean
Game Control
76%
Virginia wins
Strong
Vegas Spread
Virginia -9.5
O/U 53.5
ESPN Bet
Advanced Stats
All 4 factors agree → Virginia · 83.1% ATS historically when all four align
↓ See full breakdown
🛋 Virginia Coming off BYE
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
Virginia 2025 Schedule
Virginia's 2025 Schedule
DateMatchupSpreadTotalResultO/UCover
Sat 8/30Virginia vs Coastal Carolina-12.5W48–757.5W48–7UY
Sat 9/6Virginia at NC State+3.0L31–3553.0L31–35ON
Sat 9/13Virginia vs William & Mary-30.5W55–1654.5W55–16OY
Sat 9/20Virginia vs Stanford-16.5W48–2048.5W48–20OY
Fri 9/26Virginia vs Florida State+7.0W46–3859.5W46–38OY
Sat 10/4Virginia at Louisville+6.5W30–2759.5W30–27UY
— Bye Week —
Sat 10/18Virginia vs Washington State-16.5W22–2056.5W22–20UN
Sat 10/25Virginia at North Carolina-12.5W17–1651.5W17–16UN
Sat 11/1Virginia at California-6.5W31–2152.5W31–21UY
Sat 11/8Virginia vs Wake Forest-7.0L9–1648.5L9–16UN
Sat 11/15Virginia at Duke+5.5W34–1759.5W34–17UY
— Bye Week —
Sat 11/29Virginia vs Virginia Tech-9.5W27–753.5W27–7UY
Sat 12/6Virginia vs Duke-3.5L20–2758.5L20–27UN
Sat 12/27Virginia vs Missouri+4.0W13–743.5W13–7UY
Advanced Stats
Advanced Analytics Matchup
Matchup-adjusted (offense vs opponent defense) · 2025 season
Virginia PPA Edge
Agreement Signals — When All Metrics Agree
Elite · 83.1% ATS
PPA + PPO + SR + Havoc
All 4 Agree
→ Virginia
Elite · 82.4% ATS
PPA + PPO + Havoc
3 Agree
→ Virginia
Elite · 73.9% ATS
PPA + Success Rate
Both Agree
→ Virginia
Individual Factors — Ranked by Predictive Strength
PPA Overall
Points added per play · Elite predictor
Virginia Tech #70
+0.233
Virginia #64
+0.462
Virginia Edge
PPA Passing
Pass efficiency edge · Strong predictor
Virginia Tech #113
+0.301
Virginia #76
+0.656
Virginia Edge
Havoc Total
Def. disruption rate · Strong predictor
Virginia Tech #116
0.132
Virginia #23
0.181
TFLs, sacks, PBUs, forced fumbles — higher is better
Virginia Edge
Points Per Opp
Drive-finishing edge · Strong predictor
Virginia Tech #70
+6.693
Virginia #82
+7.905
Virginia Edge
Success Rate
Play consistency edge · Solid predictor
Virginia Tech #84
+0.789
Virginia #82
+0.872
Virginia Edge
Field Position
Avg start (lower=better) · Solid predictor
Virginia Tech #124
73.2
Virginia #30
69.3
Avg yards from own endzone to average start — lower is better · longer bar = better field position
Virginia 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 Rated Higher
Overall Power Rating
Virginia Tech
5.9
Virginia
7.0
Offense Rating
Virginia Tech
18.4
Virginia
17.9
Defense Rating (lower = better defense)
Virginia Tech
12.5
Virginia
10.9
Power ratings updated throughout the season as results accumulate
Momentum Control (CSS)
Consecutive Scoring Sequences Who builds scoring momentum? Virginia Edge
Avg sequences created per game
Virginia Tech #106
0.50
Virginia #29
1.40
Avg sequences allowed per game (lower is better)
Virginia Tech #98
1.90
Virginia #9
0.50
Virginia +0.90
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? Virginia Edge
Avg GC score per game (offense)
Virginia Tech #1
30.7
Virginia #1
58.1
Avg GC score allowed per game (lower is better)
Virginia Tech #116
53.4
Virginia #18
20.2
Virginia +27.4
GC Edge (season-to-date)
Teams with this edge win 76% of games historically
Based on 11 games this season
Actual Result
CSS Battle
Virginia
1 — 0 sequences
✓ Predicted correctly
GC Battle
Virginia
91.3 — 5.0 GC score
✓ Predicted correctly
Game Result
Virginia won by 20
✓ Model called it
Spread Context
ATS Historical Context
Based on 2021–2025 backtest · FBS vs FBS · Regular season

Both metrics agree on Virginia 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
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
Virginia
Tony Elliott #1
11–23 (32%) · Yr 4 at school
OC Des Kitchings Yr 3 #1
DC John Rudzinski 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