Georgia Tech at Pittsburgh Week 5 College Football Matchup Georgia Tech at Pittsburgh Matchup - Week 5
Sun, Oct 2 2022 · Week 5 · 🏟 Acrisure Stadium Pittsburgh, PA · Turf · 68,400 cap
Georgia Tech✈ 520 miSame TZ
26 21
Final
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📊 Punt & Rally Projection
Georgia Tech
13
Pittsburgh
36
P&R Line Pittsburgh -23
P&R Total O/U 49
Confidence 90 High
Vegas Pittsburgh -21.5 · O/U 47.0
Matchup Prediction
Pittsburgh has the edge in this matchup
Both Momentum Control (CSS) and Game Control metrics favor Pittsburgh entering this game.
Momentum Control
71.6%
Pittsburgh wins
Solid
Game Control
76%
Pittsburgh wins
Strong
Vegas Spread
Pittsburgh -21.5
O/U 47.0
teamrankings
Advanced Stats
All 4 factors agree → Pittsburgh · 83.1% ATS historically when all four align
↓ See full breakdown
🏠 Pittsburgh 2nd straight Home Game 🚌 Georgia Tech 2nd straight Road Game
Georgia Tech 2022 Schedule
Georgia Tech's 2022 Schedule
DateMatchupSpreadTotalResultO/UCover
Mon 9/5Georgia Tech vs Clemson+24.5L10–4151.0L10–41UN
Sat 9/10Georgia Tech vs Western Carolina-24.5W35–1765.5W35–17UN
Sat 9/17Georgia Tech vs Ole Miss+17.0L0–4263.0L0–42UN
Sat 9/24Georgia Tech at UCF+21.0L10–2756.5L10–27UY
Sat 10/1Georgia Tech at Pittsburgh+21.5W26–2147.0W26–21UY
Sat 10/8Georgia Tech vs Duke+3.5W23–2054.0W23–20UY
— Bye Week —
Thu 10/20Georgia Tech vs Virginia-3.5L9–1648.0L9–16UN
Sat 10/29Georgia Tech at Florida State+23.5L16–4148.0L16–41ON
Sat 11/5Georgia Tech at Virginia Tech+4.0W28–2740.5W28–27OY
Sat 11/12Georgia Tech vs Miami-2.0L14–3543.5L14–35ON
Sat 11/19Georgia Tech at North Carolina+21.5W21–1763.5W21–17UY
Sat 11/26Georgia Tech at Georgia+36.5L14–3749.0L14–37OY
Pittsburgh 2022 Schedule
Pittsburgh's 2022 Schedule
DateMatchupSpreadTotalResultO/UCover
Thu 9/1Pittsburgh vs West Virginia-7.5W38–3150.0W38–31ON
Sat 9/10Pittsburgh vs Tennessee+6.0L27–3463.0L27–34UN
Sat 9/17Pittsburgh at Western Michigan-10.0W34–1346.0W34–13OY
Sat 9/24Pittsburgh vs Rhode Island-32.5W45–2455.0W45–24ON
Sat 10/1Pittsburgh vs Georgia Tech-21.5L21–2647.0L21–26UN
Sat 10/8Pittsburgh vs Virginia Tech-14.5W45–2942.0W45–29OY
— Bye Week —
Sat 10/22Pittsburgh at Louisville+1.5L10–2455.0L10–24UN
Sat 10/29Pittsburgh at North Carolina+2.5L24–4265.5L24–42ON
Sat 11/5Pittsburgh vs Syracuse-3.5W19–947.5W19–9UY
Sat 11/12Pittsburgh at Virginia-5.5W37–741.5W37–7OY
Sat 11/19Pittsburgh vs Duke-6.5W28–2649.0W28–26ON
Sat 11/26Pittsburgh at Miami-5.5W42–1643.0W42–16OY
Fri 12/30Pittsburgh vs UCLA+9.0W37–3555.0W37–35OY
Advanced Stats
Advanced Analytics Matchup
Matchup-adjusted (offense vs opponent defense) · 2022 season
Pittsburgh PPA Edge
Agreement Signals — When All Metrics Agree
Elite · 83.1% ATS
PPA + PPO + SR + Havoc
All 4 Agree
→ Pittsburgh
Elite · 82.4% ATS
PPA + PPO + Havoc
3 Agree
→ Pittsburgh
Elite · 73.9% ATS
PPA + Success Rate
Both Agree
→ Pittsburgh
Individual Factors — Ranked by Predictive Strength
PPA Overall
Points added per play · Elite predictor
Georgia Tech
+0.106
Pittsburgh
+0.356
Pittsburgh Edge
PPA Passing
Pass efficiency edge · Strong predictor
Georgia Tech
+0.113
Pittsburgh
+0.426
Pittsburgh Edge
Havoc Total
Def. disruption rate · Strong predictor
Georgia Tech
0.166
Pittsburgh
0.221
TFLs, sacks, PBUs, forced fumbles — higher is better
Pittsburgh Edge
Points Per Opp
Drive-finishing edge · Strong predictor
Georgia Tech
+6.871
Pittsburgh
+6.998
Pittsburgh Edge
Success Rate
Play consistency edge · Solid predictor
Georgia Tech
+0.726
Pittsburgh
+0.867
Pittsburgh Edge
Field Position
Avg start (lower=better) · Solid predictor
Georgia Tech
73.1
Pittsburgh
69.3
Avg yards from own endzone to average start — lower is better · longer bar = better field position
Pittsburgh Edge
Advanced stats sourced from CFBD · 2022 season · Edges are matchup-adjusted (offense vs opponent defense)
Power Ratings
Team Power Ratings
Overall · Offense · Defense ratings · Updated as season progresses
Pittsburgh Rated Higher
Overall Power Rating
Georgia Tech
1.1
Pittsburgh
9.1
Offense Rating
Georgia Tech
14.2
Pittsburgh
19.3
Defense Rating (lower = better defense)
Georgia Tech
13.1
Pittsburgh
10.2
Power ratings updated throughout the season as results accumulate
Momentum Control (CSS)
Consecutive Scoring Sequences Who builds scoring momentum? Pittsburgh Edge
Avg sequences created per game
Georgia Tech #125
0.00
Pittsburgh #70
1.00
Avg sequences allowed per game (lower is better)
Georgia Tech #132
2.67
Pittsburgh #40
1.00
Pittsburgh +1.00
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? Pittsburgh Edge
Avg GC score per game (offense)
Georgia Tech #1
18.0
Pittsburgh #1
65.9
Avg GC score allowed per game (lower is better)
Georgia Tech #126
72.9
Pittsburgh #18
22.5
Pittsburgh +47.9
GC Edge (season-to-date)
Teams with this edge win 76% of games historically
Based on 4 games this season
Spread Context
ATS Historical Context
Based on 2021–2025 backtest · FBS vs FBS · Regular season

Both metrics agree on Pittsburgh 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
Georgia Tech
Geoff Collins #1
9–24 (27%) · Yr 4 at school
OC Chip Long Yr 1 #1
DC Andrew Thacker Yr 1 #1
Staff Rating
0.00 #1
Pittsburgh
Pat Narduzzi #1
53–37 (59%) · Yr 8 at school
OC Frank Cignetti Jr. Yr 1 #1
DC Randy Bates Yr 2 #1
Staff Rating
0.00 #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