Sat, Nov 30 2024
·
Week 14
·
🏟 Nippert Stadium
Cincinnati, OH
·
Turf
·
40,000 cap
TCU✈ 843 mi+1 hr TZ
Matchup Prediction
Toss-up — no clear edge
Neither metric shows a meaningful pre-game edge in this matchup.
Momentum Control
58.4%
—
Lean
Game Control
50.6%
Cincinnati wins
Toss-up
Vegas Spread
TCU -2.5
O/U 58.5
ESPN Bet
Advanced Stats
PPA + Success Rate agree → TCU
· 73.9% ATS historically
↓ See full breakdown
TCU 2024 Schedule
TCU's 2024 Schedule
| Date | Matchup | Spread | Total | Result | O/U | Cover |
|---|---|---|---|---|---|---|
| Fri 8/30 | TCU at Stanford | -8.0W34–27 | 58.5 | W34–27 | O | N |
| Sat 9/7 | TCU vs Long Island University | -45.5W45–0 | 56.5 | W45–0 | U | N |
| Sat 9/14 | TCU vs UCF | -1.5L34–35 | 61.5 | L34–35 | O | N |
| Sat 9/21 | TCU at SMU | -1.0L42–66 | 58.5 | L42–66 | O | N |
| Sat 9/28 | TCU vs Kansas | +1.5W38–27 | 58.5 | W38–27 | O | Y |
| Fri 10/4 | TCU vs Houston | -16.5L19–30 | 52.0 | L19–30 | U | N |
| — Bye Week — | ||||||
| Sat 10/19 | TCU at Utah | +3.0W13–7 | 52.0 | W13–7 | U | Y |
| Sat 10/26 | TCU vs Texas Tech | -5.0W35–34 | 66.0 | W35–34 | O | N |
| Sat 11/2 | TCU at Baylor | +2.5L34–37 | 64.0 | L34–37 | O | N |
| Sat 11/9 | TCU vs Oklahoma State | -10.5W38–13 | 68.5 | W38–13 | U | Y |
| — Bye Week — | ||||||
| Sat 11/23 | TCU vs Arizona | -10.5W49–28 | 60.0 | W49–28 | O | Y |
| Sat 11/30 | TCU at Cincinnati | -2.5W20–13 | 58.5 | W20–13 | U | Y |
| Sat 12/28 | TCU vs Louisiana | -9.5W34–3 | 61.0 | W34–3 | U | Y |
Cincinnati 2024 Schedule
Cincinnati's 2024 Schedule
| Date | Matchup | Spread | Total | Result | O/U | Cover |
|---|---|---|---|---|---|---|
| Sat 8/31 | Cincinnati vs Towson | -33.5W38–20 | 56.5 | W38–20 | O | N |
| Sat 9/7 | Cincinnati vs Pittsburgh | +2.5L27–28 | 62.5 | L27–28 | U | Y |
| Sat 9/14 | Cincinnati at Miami (OH) | -3.5W27–16 | 47.5 | W27–16 | U | Y |
| Sat 9/21 | Cincinnati vs Houston | -4.0W34–0 | 47.5 | W34–0 | U | Y |
| Sat 9/28 | Cincinnati at Texas Tech | +3.0L41–44 | 60.0 | L41–44 | O | Y |
| — Bye Week — | ||||||
| Sat 10/12 | Cincinnati at UCF | +2.0W19–13 | 58.0 | W19–13 | U | Y |
| Sat 10/19 | Cincinnati vs Arizona State | -5.5W24–14 | 51.0 | W24–14 | U | Y |
| Sat 10/26 | Cincinnati at Colorado | +6.0L23–34 | 57.0 | L23–34 | U | N |
| — Bye Week — | ||||||
| Sat 11/9 | Cincinnati vs West Virginia | -5.5L24–31 | 54.5 | L24–31 | O | N |
| Sat 11/16 | Cincinnati at Iowa State | +7.0L17–34 | 52.5 | L17–34 | U | N |
| Sat 11/23 | Cincinnati at Kansas State | +7.5L15–41 | 54.5 | L15–41 | O | N |
| Sat 11/30 | Cincinnati vs TCU | +2.5L13–20 | 58.5 | L13–20 | U | N |
Advanced Stats
Advanced Analytics Matchup
Matchup-adjusted (offense vs opponent defense) ·
2024 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
→ TCU
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 · 2024 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?
TCU +0.00
CSS Edge (season-to-date)
Teams with this edge win 58.4% of games historically
Based on 10 games this season
Game Control (GC)
Win Probability Dominance
Who controls games start to finish?
Cincinnati Edge
Cincinnati +2.4
GC Edge (season-to-date)
Teams with this edge win 50.6% of games historically
Based on 11 games this season
Spread Context
ATS Historical Context
Based on 2021–2025 backtest · FBS vs FBS · Regular season
Both metrics agree on Cincinnati, but the GC edge is small. When metrics agree but GC is near-neutral, the agreed-upon team has covered only 46.7% of the time historically (n=224) — potentially a fade signal.
ATS data is informational only. Past cover rates do not guarantee future results.
Coaching Matchup
TCU
Sonny Dykes #1
18–9 (67%)
· Yr 3 at school
OC
Kendal Briles
Yr 2
#1
DC
Andy Avalos
Yr 1
#1
Cincinnati
Scott Satterfield #1
3–9 (25%)
· Yr 2 at school
OC
Brad Glenn
Yr 2
#1
DC
Nate Fuqua
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 ✓