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
Vegas Spread
SMU -14
O/U 70.5
teamrankings
Advanced Stats
PPA + Success Rate agree → SMU
· 73.9% ATS historically
↓ See full breakdown
Tulane 2021 Schedule
Tulane's 2021 Schedule
| Date | Matchup | Spread | Total | Result | O/U | Cover |
|---|---|---|---|---|---|---|
| Sat 9/4 | Tulane at Oklahoma | +31.0L35–40 | 66.5 | L35–40 | O | Y |
| Sat 9/11 | Tulane vs Morgan State | -47.5W69–20 | 58.0 | W69–20 | O | Y |
| Sat 9/18 | Tulane at Ole Miss | +14.0L21–61 | 77.0 | L21–61 | O | N |
| Sat 9/25 | Tulane vs UAB | -2.5L21–28 | 55.0 | L21–28 | U | N |
| Sat 10/2 | Tulane at East Carolina | -3.0L29–52 | 65.0 | L29–52 | O | N |
| Thu 10/7 | Tulane vs Houston | +6.5L22–40 | 60.0 | L22–40 | O | N |
| — Bye Week — | ||||||
| Thu 10/21 | Tulane at SMU | +14.0L26–55 | 70.5 | L26–55 | O | N |
| Sat 10/30 | Tulane vs Cincinnati | +27.5L12–31 | 61.5 | L12–31 | U | Y |
| Sat 11/6 | Tulane at UCF | +13.5L10–14 | 57.0 | L10–14 | U | Y |
| Sat 11/13 | Tulane vs Tulsa | +3.0L13–20 | 55.5 | L13–20 | U | N |
| Sat 11/20 | Tulane vs South Florida | -5.5W45–14 | 59.5 | W45–14 | U | Y |
| Sat 11/27 | Tulane at Memphis | +5.5L28–33 | 58.0 | L28–33 | O | Y |
SMU 2021 Schedule
SMU's 2021 Schedule
| Date | Matchup | Spread | Total | Result | O/U | Cover |
|---|---|---|---|---|---|---|
| Sat 9/4 | SMU vs Abilene Christian | -32.0W56–9 | 66.0 | W56–9 | U | Y |
| Sat 9/11 | SMU vs North Texas | -22.5W35–12 | 75.5 | W35–12 | U | Y |
| Sat 9/18 | SMU at Louisiana Tech | -11.0W39–37 | 65.0 | W39–37 | O | N |
| Sat 9/25 | SMU at TCU | +8.0W42–34 | 66.0 | W42–34 | O | Y |
| Sat 10/2 | SMU vs South Florida | -21.5W41–17 | 68.5 | W41–17 | U | Y |
| Sat 10/9 | SMU at Navy | -13.5W31–24 | 57.0 | W31–24 | U | N |
| — Bye Week — | ||||||
| Thu 10/21 | SMU vs Tulane | -14.0W55–26 | 70.5 | W55–26 | O | Y |
| Sat 10/30 | SMU at Houston | -1.0L37–44 | 61.5 | L37–44 | O | N |
| Sat 11/6 | SMU at Memphis | -3.5L25–28 | 72.0 | L25–28 | U | N |
| Sat 11/13 | SMU vs UCF | -7.0W55–28 | 61.5 | W55–28 | O | Y |
| Sat 11/20 | SMU at Cincinnati | +9.5L14–48 | 65.5 | L14–48 | U | N |
| Sat 11/27 | SMU vs Tulsa | -6.0L31–34 | 63.0 | L31–34 | O | N |
| Wed 12/29 | SMU vs Virginia | +2.5 | 71.0 | — | — | — |
Advanced Stats
Advanced Analytics Matchup
Matchup-adjusted (offense vs opponent defense) ·
2021 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
→ 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 · 2021 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 +0.90
CSS Edge (season-to-date)
Teams with this edge win 58.4% of games historically
Based on 6 games this season
Game Control (GC)
Win Probability Dominance
Who controls games start to finish?
SMU Edge
SMU +54.6
GC Edge (season-to-date)
Teams with this edge win 76% of games historically
Based on 6 games this season
Actual Result
CSS Battle
SMU
3 — 0 sequences
✓ Predicted correctly
GC Battle
SMU
96.6 — 1.8 GC score
✓ Predicted correctly
Game Result
SMU won by 29
✓ 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 large edge. Historically, dominant teams like this are fully priced into the spread — the agreed-upon team covers just 50.2% of the time. The metrics predict game control better than they beat the number.
ATS data is informational only. Past cover rates do not guarantee future results.
Coaching Matchup
Tulane
Willie Fritz #1
30–35 (46%)
· Yr 6 at school
OC
Chip Long
Yr 1
#1
DC
Chris Hampton
Yr 1
#1
SMU
Sonny Dykes #1
25–14 (64%)
· Yr 4 at school
OC
Garrett Riley
Yr 1
#1
DC
Jim Leavitt
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: CSS is not a predictive 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: GS is not a predictive 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: CSS is not a predictive 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: GS is not a predictive 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 ✓