Matchup Prediction
SMU
has the edge in this matchup
Both Momentum Control (CSS) and Game Control metrics favor
SMU entering this game.
Momentum Control
61.3%
SMU wins
Lean
Game Control
64.9%
SMU wins
Lean
Vegas Spread
SMU -9.5
O/U 64.5
ESPN Bet
Advanced Stats
All 4 factors agree → SMU
· 83.1% ATS historically when all four align
↓ See full breakdown
SMU 2023 Schedule
SMU's 2023 Schedule
| Date | Matchup | Spread | Total | Result | O/U | Cover |
|---|---|---|---|---|---|---|
| Sat 9/2 | SMU vs Louisiana Tech | -21.0W38–14 | 66.0 | W38–14 | U | Y |
| Sat 9/9 | SMU at Oklahoma | +16.5L11–28 | 68.5 | L11–28 | U | N |
| Sat 9/16 | SMU vs Prairie View A&M | -42.5W69–0 | 63.5 | W69–0 | O | Y |
| Sat 9/23 | SMU at TCU | +7.0L17–34 | 63.5 | L17–34 | U | N |
| Sat 9/30 | SMU vs Charlotte | -22.5W34–16 | 53.0 | W34–16 | U | N |
| — Bye Week — | ||||||
| Thu 10/12 | SMU at East Carolina | -11.5W31–10 | 48.5 | W31–10 | U | Y |
| Fri 10/20 | SMU at Temple | -24.0W55–0 | 53.0 | W55–0 | O | Y |
| Sat 10/28 | SMU vs Tulsa | -20.5W69–10 | 55.0 | W69–10 | O | Y |
| Sat 11/4 | SMU at Rice | -12.0W36–31 | 59.5 | W36–31 | O | N |
| Fri 11/10 | SMU vs North Texas | -21.5W45–21 | 67.5 | W45–21 | U | Y |
| Sat 11/18 | SMU at Memphis | -9.5W38–34 | 64.5 | W38–34 | O | N |
| Sat 11/25 | SMU vs Navy | -20.0W59–14 | 46.0 | W59–14 | O | Y |
| Sat 12/2 | SMU at Tulane | +4.0W26–14 | 50.5 | W26–14 | U | Y |
| Thu 12/28 | SMU vs Boston College | -13.5L14–23 | 49.0 | L14–23 | U | N |
Memphis 2023 Schedule
Memphis's 2023 Schedule
| Date | Matchup | Spread | Total | Result | O/U | Cover |
|---|---|---|---|---|---|---|
| Sat 9/2 | Memphis vs Bethune-Cookman | -49.0W56–14 | 59.5 | W56–14 | O | N |
| Sat 9/9 | Memphis at Arkansas State | -21.0W37–3 | 57.0 | W37–3 | U | Y |
| Thu 9/14 | Memphis vs Navy | -12.5W28–24 | 47.0 | W28–24 | O | N |
| Sat 9/23 | Memphis vs Missouri | +6.5L27–34 | 52.0 | L27–34 | O | N |
| Sat 9/30 | Memphis vs Boise State | -3.0W35–32 | 58.0 | W35–32 | O | N |
| — Bye Week — | ||||||
| Fri 10/13 | Memphis vs Tulane | +4.5L21–31 | 54.5 | L21–31 | U | N |
| Sat 10/21 | Memphis at UAB | -7.5W45–21 | 61.5 | W45–21 | O | Y |
| Sat 10/28 | Memphis at North Texas | -6.5W45–42 | 70.0 | W45–42 | O | N |
| Sat 11/4 | Memphis vs South Florida | -13.5W59–50 | 68.5 | W59–50 | O | N |
| Sat 11/11 | Memphis at Charlotte | -9.5W44–38 | 51.5 | W44–38 | O | N |
| Sat 11/18 | Memphis vs SMU | +9.5L34–38 | 64.5 | L34–38 | O | Y |
| Fri 11/24 | Memphis at Temple | -13.5W45–21 | 63.5 | W45–21 | O | Y |
| Fri 12/29 | Memphis at Iowa State | +10.5W36–26 | 58.0 | W36–26 | O | Y |
Advanced Stats
Advanced Analytics Matchup
Matchup-adjusted (offense vs opponent defense) ·
2023 season
Agreement Signals — When All Metrics Agree
Elite · 83.1% ATS
PPA + PPO + SR + Havoc
All 4 Agree
→ SMU
Elite · 82.4% ATS
PPA + PPO + Havoc
3 Agree
→ SMU
Elite · 73.9% ATS
PPA + Success Rate
Both Agree
→ SMU
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 · 2023 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?
SMU Edge
SMU +0.89
CSS Edge (season-to-date)
Teams with this edge win 61.3% of games historically
Based on 9 games this season
Game Control (GC)
Win Probability Dominance
Who controls games start to finish?
SMU Edge
SMU +16.9
GC Edge (season-to-date)
Teams with this edge win 64.9% of games historically
Based on 10 games this season
Actual Result
CSS Battle
Memphis
1 — 0 sequences
✗ Predicted incorrectly
GC Battle
SMU
16.8 — 58.7 GC score
✓ Predicted correctly
Game Result
SMU won by 4
✓ Model called it
Spread Context
ATS Historical Context
Based on 2021–2025 backtest · FBS vs FBS · Regular season
Both metrics agree on SMU with a solid GC edge. Teams with this profile have covered 53.0% of the time historically (n=330) — a mild lean.
ATS data is informational only. Past cover rates do not guarantee future results.
Coaching Matchup
SMU
Rhett Lashlee #1
9–7 (56%)
· Yr 2 at school
OC
Casey Woods
Yr 2
#1
DC
Scott Symons
Yr 2
#1
Memphis
Ryan Silverfield #1
24–16 (60%)
· Yr 4 at school
OC
Tim Cramsey
Yr 2
#1
DC
Matt Barnes
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: 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 ✓