Sat, Nov 4 2023
·
Week 10
·
🏟 Scott Stadium
Charlottesville, VA
·
Turf
·
61,500 cap
Georgia Tech✈ 441 miSame TZ
Matchup Prediction
Metrics disagree on this matchup
Momentum Control favors Georgia Tech,
while Game Control favors Virginia.
Split signals historically show weaker predictive confidence — treat as a toss-up.
⚡ Split Signal — Metrics Disagree
Momentum Control
61.3%
Georgia Tech wins
Lean
Game Control
50.6%
Virginia wins
Toss-up
Vegas Spread
Virginia -2
O/U 57.5
DraftKings
Advanced Stats
All 4 factors agree → Georgia Tech
· 83.1% ATS historically when all four align
↓ See full breakdown
Georgia Tech 2023 Schedule
Georgia Tech's 2023 Schedule
| Date | Matchup | Spread | Total | Result | O/U | Cover |
|---|---|---|---|---|---|---|
| Fri 9/1 | Georgia Tech vs Louisville | +7.0L34–39 | 49.5 | L34–39 | O | Y |
| Sat 9/9 | Georgia Tech vs South Carolina State | -44.0W48–13 | 53.5 | W48–13 | O | N |
| Sat 9/16 | Georgia Tech at Ole Miss | +17.0L23–48 | 61.5 | L23–48 | O | N |
| Sat 9/23 | Georgia Tech at Wake Forest | +3.5W30–16 | 58.5 | W30–16 | U | Y |
| Sat 9/30 | Georgia Tech vs Bowling Green | -21.0L27–38 | 49.5 | L27–38 | O | N |
| Sat 10/7 | Georgia Tech at Miami | +19.0W23–20 | 57.0 | W23–20 | U | Y |
| — Bye Week — | ||||||
| Sat 10/21 | Georgia Tech vs Boston College | -5.5L23–38 | 57.0 | L23–38 | O | N |
| Sat 10/28 | Georgia Tech vs North Carolina | +12.0W46–42 | 65.5 | W46–42 | O | Y |
| Sat 11/4 | Georgia Tech at Virginia | +2.0W45–17 | 57.5 | W45–17 | O | Y |
| Sat 11/11 | Georgia Tech at Clemson | +17.5L21–42 | 55.5 | L21–42 | O | N |
| Sat 11/18 | Georgia Tech vs Syracuse | -6.5W31–22 | 51.5 | W31–22 | O | Y |
| Sat 11/25 | Georgia Tech vs Georgia | +23.0L23–31 | 59.5 | L23–31 | U | Y |
| Fri 12/22 | Georgia Tech vs UCF | +6.0W30–17 | 66.5 | W30–17 | U | Y |
Virginia 2023 Schedule
Virginia's 2023 Schedule
| Date | Matchup | Spread | Total | Result | O/U | Cover |
|---|---|---|---|---|---|---|
| Sat 9/2 | Virginia vs Tennessee | +27.5L13–49 | 56.0 | L13–49 | O | N |
| Sat 9/9 | Virginia vs James Madison | +6.0L35–36 | 40.0 | L35–36 | O | Y |
| Fri 9/15 | Virginia at Maryland | +16.5L14–42 | 48.5 | L14–42 | O | N |
| Fri 9/22 | Virginia vs NC State | +8.5L21–24 | 47.5 | L21–24 | U | Y |
| Sat 9/30 | Virginia at Boston College | +5.0L24–27 | 52.5 | L24–27 | U | Y |
| Sat 10/7 | Virginia vs William & Mary | -10.0W27–13 | 42.0 | W27–13 | U | Y |
| — Bye Week — | ||||||
| Sat 10/21 | Virginia at North Carolina | +24.0W31–27 | 58.0 | W31–27 | U | Y |
| Sat 10/28 | Virginia at Miami | +18.5L26–29 | 48.0 | L26–29 | O | Y |
| Sat 11/4 | Virginia vs Georgia Tech | -2.0L17–45 | 57.5 | L17–45 | O | N |
| Thu 11/9 | Virginia at Louisville | +20.5L24–31 | 49.5 | L24–31 | O | Y |
| Sat 11/18 | Virginia vs Duke | +4.0W30–27 | 48.5 | W30–27 | O | Y |
| Sat 11/25 | Virginia vs Virginia Tech | +2.5L17–55 | 52.5 | L17–55 | O | N |
Advanced Stats
Advanced Analytics Matchup
Matchup-adjusted (offense vs opponent defense) ·
2023 season
Agreement Signals — When All Metrics Agree
Elite · 83.1% ATS
PPA + PPO + SR + Havoc
All 4 Agree
→ Georgia Tech
Elite · 82.4% ATS
PPA + PPO + Havoc
3 Agree
→ Georgia Tech
Elite · 73.9% ATS
PPA + Success Rate
Both Agree
→ Georgia Tech
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 · 2023 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?
Georgia Tech Edge
Georgia Tech +0.57
CSS Edge (season-to-date)
Teams with this edge win 61.3% of games historically
Based on 7 games this season
Game Control (GC)
Win Probability Dominance
Who controls games start to finish?
Virginia Edge
Virginia +0.4
GC Edge (season-to-date)
Teams with this edge win 50.6% of games historically
Based on 8 games this season
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
Georgia Tech
Brent Key #1
5–6 (46%)
· Yr 2 at school
OC
Buster Faulkner
Yr 1
#1
DC
Kevin Sherrer
Yr 1
#1
Virginia
Tony Elliott #1
3–10 (23%)
· Yr 2 at school
OC
Des Kitchings
Yr 2
#1
DC
John Rudzinski
Yr 2
#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 ✓