Sun, Aug 31 2025
·
Week 1
·
Neutral Site
·
🏟 Mercedes-Benz Stadium
Atlanta, GA
·
Turf
·
71,000 cap
Virginia Tech✈ 327 miSame TZ
South Carolina✈ 194 miSame TZ
Matchup Prediction
Toss-up — no clear edge
Neither metric shows a meaningful pre-game edge in this matchup.
Momentum Control
58.4%
—
Lean
Game Control
50.6%
—
Toss-up
Vegas Spread
South Carolina -8.5
O/U 48.5
DraftKings
Advanced Stats
3 factors agree (PPA + PPO + Havoc) → South Carolina
· 82.4% ATS historically
↓ See full breakdown
Virginia Tech 2025 Schedule
Virginia Tech's 2025 Schedule
| Date | Matchup | Spread | Total | Result | O/U | Cover |
|---|---|---|---|---|---|---|
| Sun 8/31 | Virginia Tech vs South Carolina | +8.5L11–24 | 48.5 | L11–24 | U | N |
| Sat 9/6 | Virginia Tech vs Vanderbilt | -2.5L20–44 | 46.5 | L20–44 | O | N |
| Sat 9/13 | Virginia Tech vs Old Dominion | -5.5L26–45 | 50.5 | L26–45 | O | N |
| Sat 9/20 | Virginia Tech vs Wofford | -35.5W38–6 | 51.5 | W38–6 | U | N |
| Sat 9/27 | Virginia Tech at NC State | +10.0W23–21 | 57.5 | W23–21 | U | Y |
| Sat 10/4 | Virginia Tech vs Wake Forest | -4.5L23–30 | 51.5 | L23–30 | O | N |
| Sat 10/11 | Virginia Tech at Georgia Tech | +14.0L20–35 | 55.5 | L20–35 | U | N |
| — Bye Week — | ||||||
| Fri 10/24 | Virginia Tech vs California | -6.5W42–34 | 50.5 | W42–34 | O | Y |
| Sat 11/1 | Virginia Tech vs Louisville | +10.5L16–28 | 52.5 | L16–28 | U | N |
| — Bye Week — | ||||||
| Sat 11/15 | Virginia Tech at Florida State | +13.5L14–34 | 53.5 | L14–34 | U | N |
| Sat 11/22 | Virginia Tech vs Miami | +18.5L17–34 | 49.0 | L17–34 | O | Y |
| Sat 11/29 | Virginia Tech at Virginia | +9.5L7–27 | 53.5 | L7–27 | U | N |
South Carolina 2025 Schedule
South Carolina's 2025 Schedule
| Date | Matchup | Spread | Total | Result | O/U | Cover |
|---|---|---|---|---|---|---|
| Sun 8/31 | South Carolina vs Virginia Tech | -8.5W24–11 | 48.5 | W24–11 | U | Y |
| Sat 9/6 | South Carolina vs South Carolina State | -43.0W38–10 | 54.0 | W38–10 | U | N |
| Sat 9/13 | South Carolina vs Vanderbilt | -3.0L7–31 | 48.5 | L7–31 | U | N |
| Sat 9/20 | South Carolina at Missouri | +10.0L20–29 | 48.5 | L20–29 | O | Y |
| Sat 9/27 | South Carolina vs Kentucky | -5.5W35–13 | 46.5 | W35–13 | O | Y |
| — Bye Week — | ||||||
| Sat 10/11 | South Carolina at LSU | +8.5L10–20 | 44.5 | L10–20 | U | N |
| Sat 10/18 | South Carolina vs Oklahoma | +4.5L7–26 | 42.5 | L7–26 | U | N |
| Sat 10/25 | South Carolina vs Alabama | +11.5L22–29 | 47.5 | L22–29 | O | Y |
| Sat 11/1 | South Carolina at Ole Miss | +12.5L14–30 | 55.5 | L14–30 | U | N |
| — Bye Week — | ||||||
| Sat 11/15 | South Carolina at Texas A&M | +16.5L30–31 | 49.5 | L30–31 | O | Y |
| Sat 11/22 | South Carolina vs Coastal Carolina | -24.0W51–7 | 50.0 | W51–7 | O | Y |
| Sat 11/29 | South Carolina vs Clemson | -2.5L14–28 | 45.5 | L14–28 | U | N |
Advanced Stats
Advanced Analytics Matchup
Matchup-adjusted (offense vs opponent defense) ·
2025 season
Agreement Signals — When All Metrics Agree
Elite · 83.1% ATS
PPA + PPO + SR + Havoc
Split
Metrics disagree
Elite · 82.4% ATS
PPA + PPO + Havoc
3 Agree
→ South Carolina
Elite · 73.9% ATS
PPA + Success Rate
Split
Metrics disagree
Individual Factors — Ranked by Predictive Strength
PPA Overall
Points added per play · Elite predictor
PPA Passing
Pass efficiency edge · Strong predictor
Havoc Total
Def. disruption rate · Strong predictor
TFLs, sacks, PBUs, forced fumbles — higher is better
Points Per Opp
Drive-finishing edge · Strong predictor
Success Rate
Play consistency edge · Solid predictor
Field Position
Avg start (lower=better) · Solid predictor
Avg yards from own endzone to average start — lower is better · longer bar = better field position
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
Power ratings updated throughout the season as results accumulate
Momentum Control (CSS)
Consecutive Scoring Sequences
Who builds scoring momentum?
Virginia Tech Edge
Virginia Tech +0.00
CSS Edge (season-to-date)
Teams with this edge win 58.4% of games historically
Based on 0 games this season
Game Control (GC)
Win Probability Dominance
Who controls games start to finish?
Virginia Tech Edge
Virginia Tech +0.0
GC Edge (season-to-date)
Teams with this edge win 50.6% of games historically
Based on 0 games this season
Spread Context
ATS Historical Context
Based on 2021–2025 backtest · FBS vs FBS · Regular season
Both metrics agree on South Carolina, but the GC edge is small. When metrics agree but GC is near-neutral, the agreed-upon team has covered only 46.7% of the time historically (n=224) — potentially a fade signal.
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
South Carolina
Shane Beamer #1
29–21 (58%)
· Yr 5 at school
OC
Mike Shula
Yr 1
#1
DC
Clayton White
Yr 3
#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: CSS is not a predictive 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: GS is not a predictive 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 ✓
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: CSS is not a predictive 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: GS is not a predictive 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 ✓