Sat, Nov 5 2022
·
Week 10
·
🏟 Acrisure Stadium
Pittsburgh, PA
·
Turf
·
68,400 cap
Syracuse✈ 268 miSame TZ
Matchup Prediction
Metrics disagree on this matchup
Momentum Control favors Pittsburgh,
while Game Control favors Syracuse.
Split signals historically show weaker predictive confidence — treat as a toss-up.
⚡ Split Signal — Metrics Disagree
Momentum Control
58.4%
Pittsburgh wins
Lean
Game Control
58.3%
Syracuse wins
Lean
Vegas Spread
Pittsburgh -3.5
O/U 47.5
teamrankings
Advanced Stats
PPA + Success Rate agree → Pittsburgh
· 73.9% ATS historically
↓ See full breakdown
Syracuse 2022 Schedule
Syracuse's 2022 Schedule
| Date | Matchup | Spread | Total | Result | O/U | Cover |
|---|---|---|---|---|---|---|
| Sat 9/3 | Syracuse vs Louisville | +6.0W31–7 | 55.0 | W31–7 | U | Y |
| Sat 9/10 | Syracuse at UConn | -23.5W48–14 | 49.5 | W48–14 | O | Y |
| Sat 9/17 | Syracuse vs Purdue | -1.5W32–29 | 59.5 | W32–29 | O | Y |
| Fri 9/23 | Syracuse vs Virginia | -9.5W22–20 | 53.5 | W22–20 | U | N |
| Sat 10/1 | Syracuse vs Wagner | -54.0W59–0 | 62.5 | W59–0 | U | Y |
| — Bye Week — | ||||||
| Sat 10/15 | Syracuse vs NC State | -3.0W24–9 | 42.5 | W24–9 | U | Y |
| Sat 10/22 | Syracuse at Clemson | +14.0L21–27 | 50.0 | L21–27 | U | Y |
| Sat 10/29 | Syracuse vs Notre Dame | -1.0L24–41 | 48.0 | L24–41 | O | N |
| Sat 11/5 | Syracuse at Pittsburgh | +3.5L9–19 | 47.5 | L9–19 | U | N |
| Sat 11/12 | Syracuse vs Florida State | +7.5L3–38 | 51.0 | L3–38 | U | N |
| Sat 11/19 | Syracuse at Wake Forest | +9.5L35–45 | 58.5 | L35–45 | O | N |
| Sat 11/26 | Syracuse at Boston College | -10.5W32–23 | 47.0 | W32–23 | O | N |
| Thu 12/29 | Syracuse vs Minnesota | +10.5L20–28 | 45.0 | L20–28 | O | Y |
Pittsburgh 2022 Schedule
Pittsburgh's 2022 Schedule
| Date | Matchup | Spread | Total | Result | O/U | Cover |
|---|---|---|---|---|---|---|
| Thu 9/1 | Pittsburgh vs West Virginia | -7.5W38–31 | 50.0 | W38–31 | O | N |
| Sat 9/10 | Pittsburgh vs Tennessee | +6.0L27–34 | 63.0 | L27–34 | U | N |
| Sat 9/17 | Pittsburgh at Western Michigan | -10.0W34–13 | 46.0 | W34–13 | O | Y |
| Sat 9/24 | Pittsburgh vs Rhode Island | -32.5W45–24 | 55.0 | W45–24 | O | N |
| Sat 10/1 | Pittsburgh vs Georgia Tech | -21.5L21–26 | 47.0 | L21–26 | U | N |
| Sat 10/8 | Pittsburgh vs Virginia Tech | -14.5W45–29 | 42.0 | W45–29 | O | Y |
| — Bye Week — | ||||||
| Sat 10/22 | Pittsburgh at Louisville | +1.5L10–24 | 55.0 | L10–24 | U | N |
| Sat 10/29 | Pittsburgh at North Carolina | +2.5L24–42 | 65.5 | L24–42 | O | N |
| Sat 11/5 | Pittsburgh vs Syracuse | -3.5W19–9 | 47.5 | W19–9 | U | Y |
| Sat 11/12 | Pittsburgh at Virginia | -5.5W37–7 | 41.5 | W37–7 | O | Y |
| Sat 11/19 | Pittsburgh vs Duke | -6.5W28–26 | 49.0 | W28–26 | O | N |
| Sat 11/26 | Pittsburgh at Miami | -5.5W42–16 | 43.0 | W42–16 | O | Y |
| Fri 12/30 | Pittsburgh vs UCLA | +9.0W37–35 | 55.0 | W37–35 | O | Y |
Advanced Stats
Advanced Analytics Matchup
Matchup-adjusted (offense vs opponent defense) ·
2022 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
Split
Metrics disagree
Elite · 73.9% ATS
PPA + Success Rate
Both Agree
→ Pittsburgh
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 · 2022 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?
Pittsburgh Edge
Pittsburgh +0.29
CSS Edge (season-to-date)
Teams with this edge win 58.4% of games historically
Based on 7 games this season
Game Control (GC)
Win Probability Dominance
Who controls games start to finish?
Syracuse Edge
Syracuse +7.0
GC Edge (season-to-date)
Teams with this edge win 58.3% of games historically
Based on 8 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
Syracuse
Dino Babers #1
29–43 (40%)
· Yr 7 at school
OC
Robert Anae
Yr 1
#1
DC
Tony White
Yr 2
#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
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: CSS is not a predictive 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: GS is not a predictive 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: CSS is not a predictive 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: GS is not a predictive 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 ✓