Matchup Prediction
Tulane
has the edge in this matchup
Both Momentum Control (CSS) and Game Control metrics favor
Tulane entering this game.
Momentum Control
73.7%
Tulane wins
Solid
Game Control
64.9%
Tulane wins
Lean
Vegas Spread
Tulane -5.5
O/U 54.5
ESPN Bet
Advanced Stats
Advanced factors are split · No strong agreement signal
↓ See full breakdown
Tulane 2025 Schedule
Tulane's 2025 Schedule
| Date | Matchup | Spread | Total | Result | O/U | Cover |
|---|---|---|---|---|---|---|
| Sat 8/30 | Tulane vs Northwestern | -6.5W23–3 | 47.5 | W23–3 | U | Y |
| Sat 9/6 | Tulane at South Alabama | -13.5W33–31 | 51.5 | W33–31 | O | N |
| Sat 9/13 | Tulane vs Duke | -1.5W34–27 | 52.5 | W34–27 | O | Y |
| Sat 9/20 | Tulane at Ole Miss | +12.5L10–45 | 61.5 | L10–45 | U | N |
| Sat 9/27 | Tulane at Tulsa | -14.5W31–14 | 52.5 | W31–14 | U | Y |
| — Bye Week — | ||||||
| Thu 10/9 | Tulane vs East Carolina | -7.0W26–19 | 53.5 | W26–19 | U | N |
| Sat 10/18 | Tulane vs Army | -10.0W24–17 | 44.5 | W24–17 | U | N |
| — Bye Week — | ||||||
| Thu 10/30 | Tulane at UTSA | -5.5L26–48 | 54.5 | L26–48 | O | N |
| Fri 11/7 | Tulane at Memphis | +3.0W38–32 | 53.5 | W38–32 | O | Y |
| Sat 11/15 | Tulane vs Florida Atlantic | -16.5W35–24 | 60.5 | W35–24 | U | N |
| Sat 11/22 | Tulane at Temple | -7.5W37–13 | 54.5 | W37–13 | U | Y |
| Sat 11/29 | Tulane vs Charlotte | -31.5W27–0 | 52.5 | W27–0 | U | N |
| Fri 12/5 | Tulane vs North Texas | +1.5W34–21 | 66.5 | W34–21 | U | Y |
| Sat 12/20 | Tulane at Ole Miss | +17.5L10–41 | 57.5 | L10–41 | U | N |
UTSA 2025 Schedule
UTSA's 2025 Schedule
| Date | Matchup | Spread | Total | Result | O/U | Cover |
|---|---|---|---|---|---|---|
| Sat 8/30 | UTSA at Texas A&M | +21.5L24–42 | 56.5 | L24–42 | O | Y |
| Sat 9/6 | UTSA vs Texas State | -4.5L36–43 | 64.5 | L36–43 | O | N |
| Sat 9/13 | UTSA vs Incarnate Word | -21.0W48–20 | 62.5 | W48–20 | O | Y |
| Sat 9/20 | UTSA at Colorado State | -4.5W17–16 | 58.5 | W17–16 | U | N |
| — Bye Week — | ||||||
| Sat 10/4 | UTSA at Temple | -6.5L21–27 | 58.5 | L21–27 | U | N |
| Sat 10/11 | UTSA vs Rice | -8.5W61–13 | 48.5 | W61–13 | O | Y |
| Sat 10/18 | UTSA at North Texas | +4.0L17–55 | 64.5 | L17–55 | O | N |
| — Bye Week — | ||||||
| Thu 10/30 | UTSA vs Tulane | +5.5W48–26 | 54.5 | W48–26 | O | Y |
| Thu 11/6 | UTSA at South Florida | +14.0L23–55 | 66.5 | L23–55 | O | N |
| Sat 11/15 | UTSA at Charlotte | -16.5W28–7 | 57.5 | W28–7 | U | Y |
| Sat 11/22 | UTSA vs East Carolina | +2.0W58–24 | 62.5 | W58–24 | O | Y |
| Sat 11/29 | UTSA vs Army | -8.5L24–27 | 50.5 | L24–27 | O | N |
| Fri 12/26 | UTSA vs Florida International | -7.0W57–20 | 62.5 | W57–20 | O | Y |
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?
Tulane Edge
Tulane +1.36
CSS Edge (season-to-date)
Teams with this edge win 73.7% of games historically
Based on 6 games this season
Game Control (GC)
Win Probability Dominance
Who controls games start to finish?
Tulane Edge
Tulane +12.4
GC Edge (season-to-date)
Teams with this edge win 64.9% of games historically
Based on 7 games this season
Actual Result
CSS Battle
UTSA
3 — 0 sequences
✗ Predicted incorrectly
GC Battle
UTSA
82.3 — 6.4 GC score
✗ Predicted incorrectly
Game Result
UTSA won by 22
✗ Model missed it
Spread Context
ATS Historical Context
Based on 2021–2025 backtest · FBS vs FBS · Regular season
Both metrics agree on Tulane with a moderate edge in both. This is the strongest ATS signal in our backtest: teams in this situation have covered 55.8% of the time (n=113).
ATS data is informational only. Past cover rates do not guarantee future results.
Coaching Matchup
Tulane
Jon Sumrall #1
9–4 (69%)
· Yr 2 at school
OC
Joe Craddock
Yr 2
#1
DC
Greg Gasparato
Yr 2
#1
UTSA
Jeff Traylor #1
45–20 (69%)
· Yr 6 at school
OC
Justin Burke
Yr 3
#1
DC
Jess Loepp
Yr 3
#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 ✓