Missouri State at SMU Week 4 College Football Matchup Missouri State at SMU Matchup - Week 4
Sat, Sep 26 2026 · Week 4 · 🏟 Gerald J. Ford Stadium University Park, TX · Turf · 32,000 cap
Missouri State✈ 360 miSame TZ
Preseason projection — This game has not yet been played and 2026 in-season data is not yet available. Edges are based on 2025 full-season performance. Confidence will increase once in-season games are logged.
📊 Punt & Rally Projection
Missouri State
13
SMU
41
P&R Line SMU -28.5
P&R Total O/U 53.5
Confidence 69 Good
Matchup Prediction
SMU has the edge in this matchup
Both Momentum Control (CSS) and Game Control metrics favor SMU entering this game.
Momentum Control
58.4%
SMU wins
Lean
Game Control
76%
SMU wins
Strong
Advanced Stats
All 4 factors agree → SMU · 83.1% ATS historically when all four align
↓ See full breakdown
🛋 Missouri State Coming off BYE
Missouri State 2026 Schedule
Missouri State's 2026 Schedule
DateMatchupSpreadTotalResultO/UCover
Sat 9/5Missouri State at Texas A&M+30
— Bye Week —
Sat 9/26Missouri State at SMU+28.5
SMU 2026 Schedule
SMU's 2026 Schedule
DateMatchupSpreadTotalResultO/UCover
Mon 9/7SMU at Florida State-2.5
Sat 9/12SMU vs UC Davis-31.5
Sat 9/19SMU at Louisville+0.5
Sat 9/26SMU vs Missouri State-28.5
Sat 10/3SMU vs Boston College-19.5
— Bye Week —
Sat 10/17SMU vs Virginia-9
Fri 10/23SMU vs California-11
Fri 10/30SMU at Syracuse-12
Fri 11/6SMU vs Virginia Tech-8
Sat 11/14SMU vs Wake Forest-11.5
Sat 11/21SMU at Notre Dame+16.5
Sat 11/28SMU at Stanford-13.5
Advanced Stats
Advanced Analytics Matchup
Matchup-adjusted (offense vs opponent defense) · 2025 season (prior year)
SMU PPA Edge
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
Missouri State #69
+0.207
SMU #30
+0.463
SMU Edge
PPA Passing
Pass efficiency edge · Strong predictor
Missouri State #41
+0.521
SMU #23
+0.731
SMU Edge
Havoc Total
Def. disruption rate · Strong predictor
Missouri State #83
0.150
SMU #15
0.188
TFLs, sacks, PBUs, forced fumbles — higher is better
SMU Edge
Points Per Opp
Drive-finishing edge · Strong predictor
Missouri State #68
+6.481
SMU #53
+7.779
SMU Edge
Success Rate
Play consistency edge · Solid predictor
Missouri State #105
+0.796
SMU #64
+0.853
SMU Edge
Field Position
Avg start (lower=better) · Solid predictor
Missouri State #54
70.5
SMU #109
72.4
Avg yards from own endzone to average start — lower is better · longer bar = better field position
Missouri State Edge
Advanced stats sourced from CFBD · 2025 season (prior year — 2026 data not yet available) · Edges are matchup-adjusted (offense vs opponent defense)
Power Ratings
Team Power Ratings
Overall · Offense · Defense ratings · Updated as season progresses
SMU Rated Higher
Overall Power Rating
Missouri State #110
-8.9
SMU #16
15.2
Offense Rating
Missouri State #102
11.8
SMU #10
25.0
Defense Rating (lower = better defense)
Missouri State #117
20.7
SMU #23
9.8
Power ratings updated throughout the season as results accumulate
Momentum Control (CSS)
Consecutive Scoring Sequences Who builds scoring momentum? SMU Edge
Avg sequences created per game
Missouri State #96
0.75
SMU #22
1.58
Avg sequences allowed per game (lower is better)
Missouri State #132
1.58
SMU #2
0.25
SMU +0.83
CSS Edge (season-to-date)
Teams with this edge win 58.4% of games historically
Based on 2025 full season · preseason estimate
Game Control (GC)
Win Probability Dominance Who controls games start to finish? SMU Edge
Avg GC score per game (offense)
Missouri State #93
37.0
SMU #15
60.7
Avg GC score allowed per game (lower is better)
Missouri State #89
45.5
SMU #19
25.9
SMU +23.7
GC Edge (season-to-date)
Teams with this edge win 76% of games historically
Based on 2025 full season · preseason estimate
Coaching Matchup
Missouri State
Casey Woods #77
0–0 (0%) · Yr 1 at school
OC Mark Cala Yr 1 #118
DC Jack Curtis Yr 1 #103
Staff Rating
2.35 #100
SMU
Rhett Lashlee #12
38–17 (69%) · Yr 5 at school
OC Rob Likens Yr 1 #67
DC Maurice Crum Jr Yr 1 #52
Staff Rating
3.30 #26
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