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
50.6%
—
Toss-up
Vegas Spread
Kentucky -10
O/U 48.5
DraftKings
Advanced Stats
All 4 factors agree → Toledo
· 83.1% ATS historically when all four align
↓ See full breakdown
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 |
Kentucky 2025 Schedule
Kentucky's 2025 Schedule
| Date | Matchup | Spread | Total | Result | O/U | Cover |
|---|---|---|---|---|---|---|
| Sat 8/30 | Kentucky vs Toledo | -10.0W24–16 | 48.5 | W24–16 | U | N |
| Sat 9/6 | Kentucky vs Ole Miss | +8.0L23–30 | 51.5 | L23–30 | O | Y |
| Sat 9/13 | Kentucky vs Eastern Michigan | -26.5W48–23 | 49.5 | W48–23 | O | N |
| — Bye Week — | ||||||
| Sat 9/27 | Kentucky at South Carolina | +5.5L13–35 | 46.5 | L13–35 | O | N |
| Sat 10/4 | Kentucky at Georgia | +19.5L14–35 | 48.5 | L14–35 | O | N |
| — Bye Week — | ||||||
| Sat 10/18 | Kentucky vs Texas | +12.5L13–16 | 45.5 | L13–16 | U | Y |
| Sat 10/25 | Kentucky vs Tennessee | +7.5L34–56 | 55.5 | L34–56 | O | N |
| Sat 11/1 | Kentucky at Auburn | +11.5W10–3 | 44.5 | W10–3 | U | Y |
| Sat 11/8 | Kentucky vs Florida | +4.5W38–7 | 44.5 | W38–7 | O | Y |
| Sat 11/15 | Kentucky vs Tennessee Tech | -22.5W42–10 | 52.5 | W42–10 | U | Y |
| Sat 11/22 | Kentucky at Vanderbilt | +7.0L17–45 | 53.5 | L17–45 | O | N |
| Sat 11/29 | Kentucky at Louisville | +1.0L0–41 | 45.5 | L0–41 | U | N |
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 +0.00
CSS Edge (season-to-date)
Teams with this edge win 58.4% of games historically
Based on 0 games this season
Game Control (GC)
Win Probability Dominance
Who controls games start to finish?
Toledo Edge
Toledo +0.0
GC Edge (season-to-date)
Teams with this edge win 50.6% of games historically
Based on 0 games this season
Spread Context
ATS Historical Context
Based on 2021–2025 backtest · FBS vs FBS · Regular season
Both metrics agree on Kentucky, but the GC edge is small. When metrics agree but GC is near-neutral, the agreed-upon team has covered only 46.7% of the time historically (n=224) — potentially a fade signal.
ATS data is informational only. Past cover rates do not guarantee future results.
Coaching Matchup
Toledo
Jason Candle #1
72–40 (64%)
· Yr 10 at school
OC
Mike Hallett
Yr 3
#1
DC
Vince Kehres
Yr 3
#1
Kentucky
Mark Stoops #1
77–73 (51%)
· Yr 13 at school
OC
Bush Hamdan
Yr 2
#1
DC
Brad White
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: 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 ✓
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 ✓