Matchup Prediction
Toledo
has the edge in this matchup
Both Momentum Control (CSS) and Game Control metrics favor
Toledo entering this game.
Momentum Control
58.4%
Toledo wins
Lean
Game Control
76%
Toledo wins
Strong
Vegas Spread
Toledo -21.5
O/U 50.5
DraftKings
Advanced Stats
All 4 factors agree → Toledo
· 83.1% ATS historically when all four align
↓ See full breakdown
Akron 2025 Schedule
Akron's 2025 Schedule
| Date | Matchup | Spread | Total | Result | O/U | Cover |
|---|---|---|---|---|---|---|
| Thu 8/28 | Akron vs Wyoming | +8.5L0–10 | 49.5 | L0–10 | U | N |
| Sat 9/6 | Akron at Nebraska | +34.0L0–68 | 47.5 | L0–68 | O | N |
| Sat 9/13 | Akron at UAB | +12.5L28–31 | 58.5 | L28–31 | O | Y |
| Sat 9/20 | Akron vs Duquesne | -10.5W51–7 | 51.0 | W51–7 | O | Y |
| Sat 9/27 | Akron at Toledo | +21.5L3–45 | 50.5 | L3–45 | U | N |
| Sat 10/4 | Akron vs Central Michigan | +7.0W28–22 | 47.5 | W28–22 | O | Y |
| Sat 10/11 | Akron vs Miami (OH) | +11.5L7–20 | 47.5 | L7–20 | U | N |
| Sat 10/18 | Akron at Ball State | -2.5L28–42 | 44.5 | L28–42 | O | N |
| Sat 10/25 | Akron at Buffalo | +10.0W24–16 | 48.5 | W24–16 | U | Y |
| — Bye Week — | ||||||
| Tue 11/4 | Akron vs Massachusetts | -12.5W44–10 | 51.5 | W44–10 | O | Y |
| Tue 11/11 | Akron vs Kent State | -7.5L35–42 | 49.5 | L35–42 | O | N |
| Tue 11/18 | Akron at Bowling Green | +2.5W19–16 | 47.5 | W19–16 | U | Y |
Toledo 2025 Schedule
Toledo's 2025 Schedule
| Date | Matchup | Spread | Total | Result | O/U | Cover |
|---|---|---|---|---|---|---|
| Sat 8/30 | Toledo at Kentucky | +10.0L16–24 | 48.5 | L16–24 | U | Y |
| Sat 9/6 | Toledo vs Western Kentucky | -8.5W45–21 | 57.5 | W45–21 | O | Y |
| Sat 9/13 | Toledo vs Morgan State | -33.5W60–0 | 54.5 | W60–0 | O | Y |
| Sat 9/20 | Toledo at Western Michigan | -13.5L13–14 | 48.5 | L13–14 | U | N |
| Sat 9/27 | Toledo vs Akron | -21.5W45–3 | 50.5 | W45–3 | U | Y |
| — Bye Week — | ||||||
| Sat 10/11 | Toledo at Bowling Green | -10.5L23–28 | 45.5 | L23–28 | O | N |
| Sat 10/18 | Toledo vs Kent State | -25.5W45–10 | 48.5 | W45–10 | O | Y |
| Sat 10/25 | Toledo at Washington State | -1.5L7–28 | 44.5 | L7–28 | U | N |
| — Bye Week — | ||||||
| Wed 11/5 | Toledo vs Northern Illinois | -14.5W42–3 | 42.5 | W42–3 | O | Y |
| Wed 11/12 | Toledo at Miami (OH) | -6.5W24–3 | 44.5 | W24–3 | U | Y |
| Sat 11/22 | Toledo vs Ball State | -29.5W38–9 | 45.5 | W38–9 | O | N |
| Sat 11/29 | Toledo at Central Michigan | -11.5W21–3 | 46.5 | W21–3 | U | Y |
| Tue 12/23 | Toledo vs Louisville | +12.5L22–27 | 44.5 | L22–27 | 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
All 4 Agree
→ Toledo
Elite · 82.4% ATS
PPA + PPO + Havoc
3 Agree
→ Toledo
Elite · 73.9% ATS
PPA + Success Rate
Both Agree
→ Toledo
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?
Toledo Edge
Toledo +0.67
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?
Toledo Edge
Toledo +29.0
GC Edge (season-to-date)
Teams with this edge win 76% of games historically
Based on 4 games this season
Actual Result
CSS Battle
Toledo
3 — 0 sequences
✓ Predicted correctly
GC Battle
Toledo
98.0 — 2.0 GC score
✓ Predicted correctly
Game Result
Toledo won by 42
✓ Model called it
Spread Context
ATS Historical Context
Based on 2021–2025 backtest · FBS vs FBS · Regular season
Both metrics agree on Toledo 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
Akron
Joe Moorhead #1
8–28 (22%)
· Yr 4 at school
OC
Taylor Housewright
Yr 2
#1
DC
Tim Tibesar
Yr 3
#1
Toledo
Jason Candle #1
72–40 (64%)
· Yr 10 at school
OC
Mike Hallett
Yr 3
#1
DC
Vince Kehres
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 ✓