Matchup Prediction
Toss-up — no clear edge
Neither metric shows a meaningful pre-game edge in this matchup.
Momentum Control
58.4%
—
Lean
Game Control
76%
Tulane wins
Strong
Vegas Spread
Tulane -22.5
O/U 59.5
William Hill (New Jersey)
Advanced Stats
Advanced factors are split · No strong agreement signal
↓ See full breakdown
UAB 2023 Schedule
UAB's 2023 Schedule
| Date | Matchup | Spread | Total | Result | O/U | Cover |
|---|---|---|---|---|---|---|
| Thu 8/31 | UAB vs North Carolina A&T | -24.5W35–6 | 46.5 | W35–6 | U | Y |
| Sat 9/9 | UAB at Georgia Southern | +7.0L35–49 | 63.0 | L35–49 | O | N |
| Sat 9/16 | UAB vs Louisiana | -2.0L21–41 | 60.0 | L21–41 | O | N |
| Sat 9/23 | UAB at Georgia | +40.0L21–49 | 56.0 | L21–49 | O | Y |
| Sat 9/30 | UAB at Tulane | +22.5L23–35 | 59.5 | L23–35 | U | Y |
| Sat 10/7 | UAB vs South Florida | +3.5W56–35 | 68.5 | W56–35 | O | Y |
| Sat 10/14 | UAB at UTSA | +9.0L20–41 | 67.0 | L20–41 | U | N |
| Sat 10/21 | UAB vs Memphis | +7.5L21–45 | 61.5 | L21–45 | O | N |
| — Bye Week — | ||||||
| Sat 11/4 | UAB vs Florida Atlantic | -1.0W45–42 | 59.5 | W45–42 | O | Y |
| Sat 11/11 | UAB at Navy | -3.5L6–31 | 52.5 | L6–31 | U | N |
| Sat 11/18 | UAB vs Temple | -8.0W34–24 | 61.5 | W34–24 | U | Y |
| Sat 11/25 | UAB at North Texas | +3.0L42–45 | 72.5 | L42–45 | O | Y |
Tulane 2023 Schedule
Tulane's 2023 Schedule
| Date | Matchup | Spread | Total | Result | O/U | Cover |
|---|---|---|---|---|---|---|
| Sat 9/2 | Tulane vs South Alabama | -6.0W37–17 | 51.0 | W37–17 | O | Y |
| Sat 9/9 | Tulane vs Ole Miss | +8.0L20–37 | 64.0 | L20–37 | U | N |
| Sat 9/16 | Tulane at Southern Miss | -8.0W21–3 | 47.5 | W21–3 | U | Y |
| Sat 9/23 | Tulane vs Nicholls | -38.0W36–7 | 55.5 | W36–7 | U | N |
| Sat 9/30 | Tulane vs UAB | -22.5W35–23 | 59.5 | W35–23 | U | N |
| — Bye Week — | ||||||
| Fri 10/13 | Tulane at Memphis | -4.5W31–21 | 54.5 | W31–21 | U | Y |
| Sat 10/21 | Tulane vs North Texas | -20.0W35–28 | 63.5 | W35–28 | U | N |
| Sat 10/28 | Tulane at Rice | -10.0W30–28 | 55.0 | W30–28 | O | N |
| Sat 11/4 | Tulane at East Carolina | -17.0W13–10 | 46.0 | W13–10 | U | N |
| Sat 11/11 | Tulane vs Tulsa | -24.5W24–22 | 52.5 | W24–22 | U | N |
| Sat 11/18 | Tulane at Florida Atlantic | -9.5W24–8 | 46.5 | W24–8 | U | Y |
| Fri 11/24 | Tulane vs UTSA | -2.5W29–16 | 51.5 | W29–16 | U | Y |
| Sat 12/2 | Tulane vs SMU | -4.0L14–26 | 50.5 | L14–26 | U | N |
| Wed 12/27 | Tulane vs Virginia Tech | +13.5L20–41 | 43.5 | L20–41 | O | N |
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
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 · 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?
UAB +0.00
CSS Edge (season-to-date)
Teams with this edge win 58.4% of games historically
Based on 3 games this season
Game Control (GC)
Win Probability Dominance
Who controls games start to finish?
Tulane Edge
Tulane +47.8
GC Edge (season-to-date)
Teams with this edge win 76% of games historically
Based on 4 games this season
Actual Result
CSS Battle
UAB
1 — 2 sequences
GC Battle
Tulane
44.0 — 35.3 GC score
✓ Predicted correctly
Game Result
Tulane won by 12
Spread Context
ATS Historical Context
Based on 2021–2025 backtest · FBS vs FBS · Regular season
Both metrics agree on Tulane 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
UAB
Trent Dilfer #1
1–2 (33%)
· Yr 1 at school
OC
Alex Mortensen
Yr 1
#1
DC
Sione Ta'ufo'ou
Yr 1
#1
Tulane
Willie Fritz #1
45–46 (50%)
· Yr 8 at school
OC
Slade Nagle
Yr 1
#1
DC
Shiel Wood
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 ✓