Sat, Oct 10 2026
·
Week 6
·
🏟 Bobby Dodd Stadium at Historic Grant Field
Atlanta, GA
·
Turf
·
55,000 cap
Duke✈ 344 miSame TZ
Preseason projection — This game has not yet been played and 2026 in-season data is not yet available.
Edges are based on 2025 full-season performance.
Confidence will increase once in-season games are logged.
Matchup Prediction
Metrics disagree on this matchup
Momentum Control favors Georgia Tech,
while Game Control favors Duke.
Split signals historically show weaker predictive confidence — treat as a toss-up.
⚡ Split Signal — Metrics Disagree
Momentum Control
58.4%
Georgia Tech wins
Lean
Game Control
49.4%
Duke wins
Toss-up
Advanced Stats
PPA + Success Rate agree → Georgia Tech
· 73.9% ATS historically
↓ See full breakdown
Duke 2026 Schedule
Duke's 2026 Schedule
| Date | Matchup | Spread | Total | Result | O/U | Cover |
|---|---|---|---|---|---|---|
| Sat 9/5 | Duke vs Tulane | -9.5 | — | — | — | — |
| Sat 9/12 | Duke at Illinois | +7 | — | — | — | — |
| Sat 9/19 | Duke vs Stanford | -10 | — | — | — | — |
| Sat 9/26 | Duke vs William & Mary | -28 | — | — | — | — |
| — Bye Week — | ||||||
| Sat 10/10 | Duke at Georgia Tech | +1.5 | — | — | — | — |
| Sat 10/17 | Duke vs North Carolina | -5 | — | — | — | — |
| Fri 10/23 | Duke at Virginia | +5 | — | — | — | — |
| Sat 10/31 | Duke vs Boston College | -10.5 | — | — | — | — |
| Fri 11/6 | Duke at NC State | +4 | — | — | — | — |
| Sat 11/14 | Duke at Miami | +20.5 | — | — | — | — |
| Sat 11/21 | Duke vs Clemson | +3.5 | — | — | — | — |
| Sat 11/28 | Duke at Wake Forest | +2 | — | — | — | — |
Georgia Tech 2026 Schedule
Georgia Tech's 2026 Schedule
| Date | Matchup | Spread | Total | Result | O/U | Cover |
|---|---|---|---|---|---|---|
| Thu 9/3 | Georgia Tech vs Colorado | -5.5 | — | — | — | — |
| Sat 9/12 | Georgia Tech vs Tennessee | +8.5 | — | — | — | — |
| Sat 9/19 | Georgia Tech vs Mercer | -27 | — | — | — | — |
| Sat 9/26 | Georgia Tech at Stanford | -4 | — | — | — | — |
| — Bye Week — | ||||||
| Sat 10/10 | Georgia Tech vs Duke | -1.5 | — | — | — | — |
| Sat 10/17 | Georgia Tech at Virginia Tech | +6.5 | — | — | — | — |
| Sat 10/24 | Georgia Tech vs Boston College | -10 | — | — | — | — |
| Sat 10/31 | Georgia Tech at Pittsburgh | +7 | — | — | — | — |
| Fri 11/6 | Georgia Tech vs Louisville | +5 | — | — | — | — |
| Sat 11/14 | Georgia Tech at Clemson | +9.5 | — | — | — | — |
| Sat 11/21 | Georgia Tech vs Wake Forest | -2 | — | — | — | — |
| Sat 11/28 | Georgia Tech at Georgia | +26 | — | — | — | — |
Advanced Stats
Advanced Analytics Matchup
Matchup-adjusted (offense vs opponent defense) ·
2025 season (prior year)
Agreement Signals — When All Metrics Agree
Elite · 83.1% ATS
PPA + PPO + SR + Havoc
Split
Metrics disagree
Elite · 82.4% ATS
PPA + PPO + Havoc
Split
Metrics disagree
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 · 2025 season (prior year — 2026 data not yet available) ·
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 +0.51
CSS Edge (season-to-date)
Teams with this edge win 58.4% of games historically
Based on 2025 full season · preseason estimate
Game Control (GC)
Win Probability Dominance
Who controls games start to finish?
Duke Edge
Duke +0.2
GC Edge (season-to-date)
Teams with this edge win 49.4% of games historically
Based on 2025 full season · preseason estimate
Coaching Matchup
Duke
Manny Diaz #52
18–9 (67%)
· Yr 3 at school
OC
Jonathan Brewer
Yr 3
#49
DC
Jonathan Patke
Yr 3
#112
Georgia Tech
Brent Key #62
27–20 (57%)
· Yr 5 at school
OC
George Godsey
Yr 1
#67
DC
Jason Semore
Yr 1
#42
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 ✓