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
Clemson -3.5
O/U 49.5
DraftKings
Advanced Stats
Advanced factors are split · No strong agreement signal
↓ See full breakdown
SMU 2025 Schedule
SMU's 2025 Schedule
| Date | Matchup | Spread | Total | Result | O/U | Cover |
|---|---|---|---|---|---|---|
| Sat 8/30 | SMU vs East Texas A&M | -51.0W42–13 | 65.0 | W42–13 | U | N |
| Sat 9/6 | SMU vs Baylor | -3.0L45–48 | 65.5 | L45–48 | O | N |
| Sat 9/13 | SMU at Missouri State | -29.5W28–10 | 60.5 | W28–10 | U | N |
| Sat 9/20 | SMU at TCU | +6.5L24–35 | 63.5 | L24–35 | U | N |
| — Bye Week — | ||||||
| Sat 10/4 | SMU vs Syracuse | -17.5W31–18 | 56.5 | W31–18 | U | N |
| Sat 10/11 | SMU vs Stanford | -19.5W34–10 | 55.5 | W34–10 | U | Y |
| Sat 10/18 | SMU at Clemson | +3.5W35–24 | 49.5 | W35–24 | O | Y |
| Sat 10/25 | SMU at Wake Forest | -6.5L12–13 | 53.5 | L12–13 | U | N |
| Sat 11/1 | SMU vs Miami | +8.5W26–20 | 50.5 | W26–20 | U | Y |
| Sat 11/8 | SMU at Boston College | -10.5W45–13 | 54.5 | W45–13 | O | Y |
| — Bye Week — | ||||||
| Sat 11/22 | SMU vs Louisville | -4.0W38–6 | 49.5 | W38–6 | U | Y |
| Sat 11/29 | SMU at California | -13.5L35–38 | 53.5 | L35–38 | O | N |
| Fri 1/2 | SMU vs Arizona | -2.5W24–19 | 55.5 | W24–19 | U | Y |
Clemson 2025 Schedule
Clemson's 2025 Schedule
| Date | Matchup | Spread | Total | Result | O/U | Cover |
|---|---|---|---|---|---|---|
| Sat 8/30 | Clemson vs LSU | -3.5L10–17 | 57.5 | L10–17 | U | N |
| Sat 9/6 | Clemson vs Troy | -31.0W27–16 | 51.5 | W27–16 | U | N |
| Sat 9/13 | Clemson at Georgia Tech | -2.5L21–24 | 49.5 | L21–24 | U | N |
| Sat 9/20 | Clemson vs Syracuse | -17.5L21–34 | 53.5 | L21–34 | O | N |
| — Bye Week — | ||||||
| Sat 10/4 | Clemson at North Carolina | -15.5W38–10 | 47.5 | W38–10 | O | Y |
| Sat 10/11 | Clemson at Boston College | -14.0W41–10 | 54.5 | W41–10 | U | Y |
| Sat 10/18 | Clemson vs SMU | -3.5L24–35 | 49.5 | L24–35 | O | N |
| — Bye Week — | ||||||
| Sat 11/1 | Clemson vs Duke | -4.5L45–46 | 55.5 | L45–46 | O | N |
| Sat 11/8 | Clemson vs Florida State | -1.5W24–10 | 56.5 | W24–10 | U | Y |
| Fri 11/14 | Clemson at Louisville | +1.5W20–19 | 50.5 | W20–19 | U | Y |
| Sat 11/22 | Clemson vs Furman | -41.5W45–10 | 55.5 | W45–10 | U | N |
| Sat 11/29 | Clemson at South Carolina | +2.5W28–14 | 45.5 | W28–14 | U | Y |
| Sat 12/27 | Clemson vs Penn State | -2.5L10–22 | 47.5 | L10–22 | U | N |
Advanced Stats
Advanced Analytics Matchup
Matchup-adjusted (offense vs opponent defense) ·
2025 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 · 2025 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 +0.27
CSS Edge (season-to-date)
Teams with this edge win 61.3% of games historically
Based on 6 games this season
Game Control (GC)
Win Probability Dominance
Who controls games start to finish?
SMU Edge
SMU +16.7
GC Edge (season-to-date)
Teams with this edge win 64.9% of games historically
Based on 6 games this season
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
29–12 (71%)
· Yr 4 at school
OC
Casey Woods
Yr 3
#1
DC
Scott Symons
Yr 3
#1
Clemson
Dabo Swinney #1
180–46 (80%)
· Yr 17 at school
OC
Garrett Riley
Yr 3
#1
DC
Tom Allen
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 ✓