Sun, Sep 3 2023
·
Week 1
·
🏟 Lane Stadium
Blacksburg, VA
·
Turf
·
66,233 cap
Old Dominion✈ 227 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
Virginia Tech -16
O/U 48.0
William Hill (New Jersey)
Advanced Stats
All 4 factors agree → Virginia Tech
· 83.1% ATS historically when all four align
↓ See full breakdown
Old Dominion 2023 Schedule
Old Dominion's 2023 Schedule
| Date | Matchup | Spread | Total | Result | O/U | Cover |
|---|---|---|---|---|---|---|
| Sat 9/2 | Old Dominion at Virginia Tech | +16.0L17–36 | 48.0 | L17–36 | O | N |
| Sat 9/9 | Old Dominion vs Louisiana | +6.0W38–31 | 51.0 | W38–31 | O | Y |
| Sat 9/16 | Old Dominion vs Wake Forest | +13.5L24–27 | 60.0 | L24–27 | U | Y |
| Sat 9/23 | Old Dominion vs East Texas A&M | -18.5 | — | — | — | — |
| Sat 9/30 | Old Dominion at Marshall | +14.5L35–41 | 47.0 | L35–41 | O | Y |
| Sat 10/7 | Old Dominion at Southern Miss | +3.0W17–13 | 56.5 | W17–13 | U | Y |
| — Bye Week — | ||||||
| Sat 10/21 | Old Dominion vs App State | +6.0W28–21 | 56.0 | W28–21 | U | Y |
| Sat 10/28 | Old Dominion at James Madison | +19.5L27–30 | 48.0 | L27–30 | O | Y |
| Sat 11/4 | Old Dominion vs Coastal Carolina | +1.0L24–28 | 51.0 | L24–28 | O | N |
| Sat 11/11 | Old Dominion at Liberty | +13.5L10–38 | 58.5 | L10–38 | U | N |
| Sat 11/18 | Old Dominion at Georgia Southern | +4.5W20–17 | 61.5 | W20–17 | U | Y |
| Sat 11/25 | Old Dominion vs Georgia State | -2.0W25–24 | 49.5 | W25–24 | U | N |
| Mon 12/18 | Old Dominion vs Western Kentucky | -4.0L35–38 | 49.0 | L35–38 | O | N |
Virginia Tech 2023 Schedule
Virginia Tech's 2023 Schedule
| Date | Matchup | Spread | Total | Result | O/U | Cover |
|---|---|---|---|---|---|---|
| Sat 9/2 | Virginia Tech vs Old Dominion | -16.0W36–17 | 48.0 | W36–17 | O | Y |
| Sat 9/9 | Virginia Tech vs Purdue | -1.5L17–24 | 49.0 | L17–24 | U | N |
| Sat 9/16 | Virginia Tech at Rutgers | +6.5L16–35 | 37.5 | L16–35 | O | N |
| Sat 9/23 | Virginia Tech at Marshall | +5.5L17–24 | 41.5 | L17–24 | U | N |
| Sat 9/30 | Virginia Tech vs Pittsburgh | +3.0W38–21 | 40.0 | W38–21 | O | Y |
| Sat 10/7 | Virginia Tech at Florida State | +23.5L17–39 | 52.5 | L17–39 | O | Y |
| Sat 10/14 | Virginia Tech vs Wake Forest | -1.5W30–13 | 48.5 | W30–13 | U | Y |
| — Bye Week — | ||||||
| Thu 10/26 | Virginia Tech vs Syracuse | -2.5W38–10 | 47.5 | W38–10 | O | Y |
| Sat 11/4 | Virginia Tech at Louisville | +9.5L3–34 | 48.5 | L3–34 | U | N |
| Sat 11/11 | Virginia Tech at Boston College | -2.5W48–22 | 48.5 | W48–22 | O | Y |
| Sat 11/18 | Virginia Tech vs NC State | -2.5L28–35 | 40.5 | L28–35 | O | N |
| Sat 11/25 | Virginia Tech at Virginia | -2.5W55–17 | 52.5 | W55–17 | O | Y |
| Wed 12/27 | Virginia Tech vs Tulane | -13.5W41–20 | 43.5 | W41–20 | O | Y |
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
→ Virginia Tech
Elite · 82.4% ATS
PPA + PPO + Havoc
3 Agree
→ Virginia Tech
Elite · 73.9% ATS
PPA + Success Rate
Both Agree
→ Virginia 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?
Old Dominion Edge
Old Dominion +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?
Old Dominion Edge
Old Dominion +0.0
GC Edge (season-to-date)
Teams with this edge win 50.6% of games historically
Based on 0 games this season
Actual Result
CSS Battle
Virginia Tech
1 — 0 sequences
✗ Predicted incorrectly
GC Battle
Virginia Tech
72.4 — 10.7 GC score
✗ Predicted incorrectly
Game Result
Virginia Tech won by 19
Spread Context
ATS Historical Context
Based on 2021–2025 backtest · FBS vs FBS · Regular season
Both metrics agree on Virginia Tech, 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
Old Dominion
Ricky Rahne #1
10–18 (36%)
· Yr 4 at school
OC
Kevin Decker
Yr 1
#1
DC
Blake Seiler
Yr 3
#1
Virginia Tech
Brent Pry #1
4–10 (29%)
· Yr 2 at school
OC
Tyler Bowen
Yr 2
#1
DC
Chris Marve
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: 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 ✓
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 ✓

