Matchup Prediction
TCU
has the edge in this matchup
Both Momentum Control (CSS) and Game Control metrics favor
TCU entering this game.
Momentum Control
73.7%
TCU wins
Solid
Game Control
64.9%
TCU wins
Lean
Vegas Spread
TCU -2.5
O/U 72.0
teamrankings
Advanced Stats
PPA + Success Rate agree → TCU
· 73.9% ATS historically
↓ See full breakdown
TCU 2022 Schedule
TCU's 2022 Schedule
| Date | Matchup | Spread | Total | Result | O/U | Cover |
|---|---|---|---|---|---|---|
| Fri 9/2 | TCU at Colorado | -13.5W38–13 | 59.0 | W38–13 | U | Y |
| Sat 9/10 | TCU vs Tarleton State | -40.0W59–17 | 66.5 | W59–17 | O | Y |
| — Bye Week — | ||||||
| Sat 9/24 | TCU at SMU | -2.5W42–34 | 72.0 | W42–34 | O | Y |
| Sat 10/1 | TCU vs Oklahoma | +5.0W55–24 | 69.5 | W55–24 | O | Y |
| Sat 10/8 | TCU at Kansas | -7.0W38–31 | 70.0 | W38–31 | U | N |
| Sat 10/15 | TCU vs Oklahoma State | -5.0W43–40 | 69.5 | W43–40 | O | N |
| Sat 10/22 | TCU vs Kansas State | -3.5W38–28 | 54.5 | W38–28 | O | Y |
| Sat 10/29 | TCU at West Virginia | -7.0W41–31 | 70.0 | W41–31 | O | Y |
| Sat 11/5 | TCU vs Texas Tech | -8.5W34–24 | 69.0 | W34–24 | U | Y |
| Sat 11/12 | TCU at Texas | +7.5W17–10 | 65.0 | W17–10 | U | Y |
| Sat 11/19 | TCU at Baylor | -2.0W29–28 | 58.0 | W29–28 | U | N |
| Sat 11/26 | TCU vs Iowa State | -9.5W62–14 | 46.0 | W62–14 | O | Y |
| Sat 12/3 | TCU vs Kansas State | -1.0L28–31 | 60.5 | L28–31 | U | N |
| Sat 12/31 | TCU vs Michigan | +8.0W51–45 | 56.0 | W51–45 | O | Y |
| Mon 1/9 | TCU vs Georgia | +13.5L7–65 | 62.0 | L7–65 | O | N |
SMU 2022 Schedule
SMU's 2022 Schedule
| Date | Matchup | Spread | Total | Result | O/U | Cover |
|---|---|---|---|---|---|---|
| Sat 9/3 | SMU at North Texas | -9.5W48–10 | 67.5 | W48–10 | U | Y |
| Sat 9/10 | SMU vs Lamar | -48.5W45–16 | 66.0 | W45–16 | U | N |
| Sat 9/17 | SMU at Maryland | +3.0L27–34 | 74.0 | L27–34 | U | N |
| Sat 9/24 | SMU vs TCU | +2.5L34–42 | 72.0 | L34–42 | O | N |
| — Bye Week — | ||||||
| Wed 10/5 | SMU at UCF | +3.0L19–41 | 65.0 | L19–41 | U | N |
| Fri 10/14 | SMU vs Navy | -12.5W40–34 | 59.0 | W40–34 | O | N |
| Sat 10/22 | SMU vs Cincinnati | +3.5L27–29 | 59.5 | L27–29 | U | Y |
| Sat 10/29 | SMU at Tulsa | -1.0W45–34 | 63.5 | W45–34 | O | Y |
| Sat 11/5 | SMU vs Houston | -3.5W77–63 | 66.0 | W77–63 | O | Y |
| Sat 11/12 | SMU at South Florida | -17.5W41–23 | 72.5 | W41–23 | U | Y |
| Thu 11/17 | SMU at Tulane | +3.5L24–59 | 65.0 | L24–59 | O | N |
| Sat 11/26 | SMU vs Memphis | -4.5W34–31 | 69.0 | W34–31 | U | N |
| Sat 12/17 | SMU vs BYU | -4.5L23–24 | 65.0 | L23–24 | U | N |
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
→ 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 · 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?
TCU Edge
TCU +1.50
CSS Edge (season-to-date)
Teams with this edge win 73.7% of games historically
Based on 2 games this season
Game Control (GC)
Win Probability Dominance
Who controls games start to finish?
TCU Edge
TCU +15.2
GC Edge (season-to-date)
Teams with this edge win 64.9% of games historically
Based on 3 games this season
Spread Context
ATS Historical Context
Based on 2021–2025 backtest · FBS vs FBS · Regular season
Both metrics agree on TCU with a moderate edge in both. This is the strongest ATS signal in our backtest: teams in this situation have covered 55.8% of the time (n=113).
ATS data is informational only. Past cover rates do not guarantee future results.
Coaching Matchup
TCU
Sonny Dykes #1
0–0 (0%)
· Yr 1 at school
OC
Garrett Riley
Yr 1
#1
DC
Joseph Gillespie
Yr 1
#1
SMU
Rhett Lashlee #1
0–0 (0%)
· Yr 1 at school
OC
Casey Woods
Yr 1
#1
DC
Scott Symons
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 ✓