Sat, Sep 30 2023
·
Week 5
·
🏟 Bobby Dodd Stadium at Historic Grant Field
Atlanta, GA
·
Turf
·
55,000 cap
Bowling Green✈ 527 miSame TZ
Matchup Prediction
Georgia Tech
has the edge in this matchup
Both Momentum Control (CSS) and Game Control metrics favor
Georgia Tech entering this game.
Momentum Control
71.6%
Georgia Tech wins
Solid
Game Control
76%
Georgia Tech wins
Strong
Vegas Spread
Georgia Tech -21
O/U 49.5
William Hill (New Jersey)
Advanced Stats
3 factors agree (PPA + PPO + Havoc) → Georgia Tech
· 82.4% ATS historically
↓ See full breakdown
Bowling Green 2023 Schedule
Bowling Green's 2023 Schedule
| Date | Matchup | Spread | Total | Result | O/U | Cover |
|---|---|---|---|---|---|---|
| Sat 9/2 | Bowling Green at Liberty | +8.5L24–34 | 48.5 | L24–34 | O | N |
| Sat 9/9 | Bowling Green vs Eastern Illinois | -17.0W38–15 | 48.0 | W38–15 | O | Y |
| Sat 9/16 | Bowling Green at Michigan | +40.5L6–31 | 53.5 | L6–31 | U | Y |
| Sat 9/23 | Bowling Green vs Ohio | +13.0L7–38 | 45.0 | L7–38 | U | N |
| Sat 9/30 | Bowling Green at Georgia Tech | +21.0W38–27 | 49.5 | W38–27 | O | Y |
| Sat 10/7 | Bowling Green at Miami (OH) | +7.5L0–27 | 43.0 | L0–27 | U | N |
| Sat 10/14 | Bowling Green at Buffalo | +3.0W24–14 | 44.5 | W24–14 | U | Y |
| Sat 10/21 | Bowling Green vs Akron | -7.0W41–14 | 37.0 | W41–14 | O | Y |
| — Bye Week — | ||||||
| Wed 11/1 | Bowling Green vs Ball State | -4.5W24–21 | 39.5 | W24–21 | O | N |
| Wed 11/8 | Bowling Green at Kent State | -10.5W49–19 | 41.5 | W49–19 | O | Y |
| Tue 11/14 | Bowling Green vs Toledo | +9.5L31–32 | 48.5 | L31–32 | O | Y |
| Tue 11/21 | Bowling Green at Western Michigan | -2.0W34–10 | 54.5 | W34–10 | U | Y |
| Tue 12/26 | Bowling Green vs Minnesota | +2.5L24–30 | 45.0 | L24–30 | O | N |
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 |
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
Split
Metrics disagree
Elite · 82.4% ATS
PPA + PPO + Havoc
3 Agree
→ Georgia Tech
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 · 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 +1.33
CSS Edge (season-to-date)
Teams with this edge win 71.6% of games historically
Based on 3 games this season
Game Control (GC)
Win Probability Dominance
Who controls games start to finish?
Georgia Tech Edge
Georgia Tech +27.0
GC Edge (season-to-date)
Teams with this edge win 76% of games historically
Based on 4 games this season
Actual Result
CSS Battle
Bowling Green
1 — 2 sequences
✗ Predicted incorrectly
GC Battle
Bowling Green
29.8 — 54.2 GC score
✗ Predicted incorrectly
Game Result
Bowling Green won by 11
✗ Model missed it
Spread Context
ATS Historical Context
Based on 2021–2025 backtest · FBS vs FBS · Regular season
Both metrics agree on Georgia Tech 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
Bowling Green
Scot Loeffler #1
14–31 (31%)
· Yr 5 at school
OC
Greg Nosal
Yr 1
#1
DC
Sammy Lawanson
Yr 1
#1
Georgia Tech
Brent Key #1
5–6 (46%)
· Yr 2 at school
OC
Buster Faulkner
Yr 1
#1
DC
Kevin Sherrer
Yr 1
#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 ✓

