Pittsburgh at UCLA Week 1 College Football Matchup Pittsburgh at UCLA Matchup - Week 1
Fri, Dec 30 2022 · Postseason · Neutral Site · 🏟 Sun Bowl Stadium El Paso, TX · Turf · 51,500 cap
Pittsburgh✈ 1,587 mi-2 hr TZ UCLA✈ 695 mi+1 hr TZ
Away (Neutral)
37 35
Final
Home (Neutral)
📊 Punt & Rally Projection
Pittsburgh
26
PITT +9
UCLA
33
P&R Line UCLA -6.5
P&R Total O/U 58.5
Confidence 86 High
Vegas UCLA -9.0 · O/U 55.0
Matchup Prediction
Metrics disagree on this matchup
Momentum Control favors UCLA, while Game Control favors Pittsburgh. Split signals historically show weaker predictive confidence — treat as a toss-up.
⚡ Split Signal — Metrics Disagree
Momentum Control
58.4%
UCLA wins
Lean
Game Control
49.4%
Pittsburgh wins
Toss-up
Vegas Spread
UCLA -9.0
O/U 55.0
Bovada
Advanced Stats
PPA + Success Rate agree → UCLA · 73.9% ATS historically
↓ See full breakdown
🚌 Pittsburgh 2nd straight Road Game
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
UCLA 2022 Schedule
UCLA's 2022 Schedule
DateMatchupSpreadTotalResultO/UCover
Sat 9/3UCLA vs Bowling Green-24.0W45–1756.5W45–17OY
Sat 9/10UCLA vs Alabama State-48.5W45–761.5W45–7UN
Sat 9/17UCLA vs South Alabama-15.5W32–3159.5W32–31ON
Sat 9/24UCLA at Colorado-22.0W45–1757.0W45–17OY
Fri 9/30UCLA vs Washington+2.5W40–3265.0W40–32OY
Sat 10/8UCLA vs Utah+3.0W42–3264.5W42–32OY
— Bye Week —
Sat 10/22UCLA at Oregon+7.0L30–4570.5L30–45ON
Sat 10/29UCLA vs Stanford-16.5W38–1364.5W38–13UY
Sat 11/5UCLA at Arizona State-11.0W50–3666.5W50–36OY
Sat 11/12UCLA vs Arizona-19.5L28–3476.5L28–34UN
Sat 11/19UCLA vs USC+2.5L45–4876.5L45–48ON
Fri 11/25UCLA at California-11.5W35–2862.5W35–28ON
Fri 12/30UCLA vs Pittsburgh-9.0L35–3755.0L35–37ON
Advanced Stats
Advanced Analytics Matchup
Matchup-adjusted (offense vs opponent defense) · 2022 season
UCLA PPA Edge
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
→ UCLA
Individual Factors — Ranked by Predictive Strength
PPA Overall
Points added per play · Elite predictor
Pittsburgh
+0.413
UCLA
+0.431
UCLA Edge
PPA Passing
Pass efficiency edge · Strong predictor
Pittsburgh
+0.554
UCLA
+0.461
Pittsburgh Edge
Havoc Total
Def. disruption rate · Strong predictor
Pittsburgh
0.221
UCLA
0.125
TFLs, sacks, PBUs, forced fumbles — higher is better
Pittsburgh Edge
Points Per Opp
Drive-finishing edge · Strong predictor
Pittsburgh
+8.053
UCLA
+8.116
UCLA Edge
Success Rate
Play consistency edge · Solid predictor
Pittsburgh
+0.902
UCLA
+0.903
UCLA Edge
Field Position
Avg start (lower=better) · Solid predictor
Pittsburgh
69.3
UCLA
70.6
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
Pittsburgh
9.1
UCLA
6.6
Offense Rating
Pittsburgh
19.3
UCLA
19.6
Defense Rating (lower = better defense)
Pittsburgh
10.2
UCLA
13.0
Power ratings updated throughout the season as results accumulate
Momentum Control (CSS)
Consecutive Scoring Sequences Who builds scoring momentum? UCLA Edge
Avg sequences created per game
Pittsburgh #70
0.82
UCLA #40
1.36
Avg sequences allowed per game (lower is better)
Pittsburgh #40
1.00
UCLA #31
0.91
UCLA +0.55
CSS Edge (season-to-date)
Teams with this edge win 58.4% of games historically
Based on 11 games this season
Game Control (GC)
Win Probability Dominance Who controls games start to finish? Pittsburgh Edge
Avg GC score per game (offense)
Pittsburgh #1
66.6
UCLA #1
65.3
Avg GC score allowed per game (lower is better)
Pittsburgh #18
19.2
UCLA #20
22.3
Pittsburgh +1.3
GC Edge (season-to-date)
Teams with this edge win 49.4% of games historically
Based on 12 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
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
UCLA
Chip Kelly #1
18–25 (42%) · Yr 5 at school
OC Chip Kelly Yr 1 #1
DC Bill McGovern Yr 1 #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