Matchup Prediction
Memphis
has the edge in this matchup
Both Momentum Control (CSS) and Game Control metrics favor
Memphis entering this game.
Momentum Control
61.3%
Memphis wins
Lean
Game Control
49.4%
Memphis wins
Toss-up
Vegas Spread
SMU -4.5
O/U 69.0
Bovada
Advanced Stats
Advanced factors are split · No strong agreement signal
↓ See full breakdown
Memphis 2022 Schedule
Memphis's 2022 Schedule
| Date | Matchup | Spread | Total | Result | O/U | Cover |
|---|---|---|---|---|---|---|
| Sat 9/3 | Memphis at Mississippi State | +17.0L23–49 | 58.0 | L23–49 | O | N |
| Sat 9/10 | Memphis at Navy | -4.5W37–13 | 47.5 | W37–13 | O | Y |
| Sat 9/17 | Memphis vs Arkansas State | -14.5W44–32 | 64.0 | W44–32 | O | N |
| Sat 9/24 | Memphis vs North Texas | -13.0W44–34 | 68.5 | W44–34 | O | N |
| Sat 10/1 | Memphis vs Temple | -18.5W24–3 | 50.0 | W24–3 | U | Y |
| Fri 10/7 | Memphis vs Houston | -1.5L32–33 | 57.5 | L32–33 | O | N |
| Sat 10/15 | Memphis at East Carolina | +5.5L45–47 | 62.5 | L45–47 | O | Y |
| Sat 10/22 | Memphis at Tulane | +7.0L28–38 | 55.5 | L28–38 | O | N |
| — Bye Week — | ||||||
| Sat 11/5 | Memphis vs UCF | +3.0L28–35 | 60.5 | L28–35 | O | N |
| Thu 11/10 | Memphis vs Tulsa | -7.0W26–10 | 62.0 | W26–10 | U | Y |
| Sat 11/19 | Memphis vs North Alabama | -36.0W59–0 | 67.5 | W59–0 | U | Y |
| Sat 11/26 | Memphis at SMU | +4.5L31–34 | 69.0 | L31–34 | U | Y |
| Tue 12/27 | Memphis vs Utah State | -8.0W38–10 | 57.0 | W38–10 | U | Y |
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
Split
Metrics disagree
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?
Memphis Edge
Memphis +0.04
CSS Edge (season-to-date)
Teams with this edge win 61.3% of games historically
Based on 10 games this season
Game Control (GC)
Win Probability Dominance
Who controls games start to finish?
Memphis Edge
Memphis +0.9
GC Edge (season-to-date)
Teams with this edge win 49.4% of games historically
Based on 11 games this season
Actual Result
CSS Battle
SMU
2 — 0 sequences
✗ Predicted incorrectly
GC Battle
SMU
46.2 — 27.2 GC score
✗ Predicted incorrectly
Game Result
SMU won by 3
✗ Model missed it
Spread Context
ATS Historical Context
Based on 2021–2025 backtest · FBS vs FBS · Regular season
Both metrics agree on Memphis, 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
Memphis
Ryan Silverfield #1
14–10 (58%)
· Yr 3 at school
OC
Tim Cramsey
Yr 1
#1
DC
Matt Barnes
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 ✓