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
Illinois -7
O/U 45.5
William Hill (New Jersey)
Advanced Stats
All 4 factors agree → Toledo
· 83.1% ATS historically when all four align
↓ See full breakdown
Toledo 2023 Schedule
Toledo's 2023 Schedule
| Date | Matchup | Spread | Total | Result | O/U | Cover |
|---|---|---|---|---|---|---|
| Sat 9/2 | Toledo at Illinois | +7.0L28–30 | 45.5 | L28–30 | O | Y |
| Sat 9/9 | Toledo vs Texas Southern | -40.5W71–3 | 61.0 | W71–3 | O | Y |
| Sat 9/16 | Toledo vs San José State | -9.0W21–17 | 56.5 | W21–17 | U | N |
| Sat 9/23 | Toledo vs Western Michigan | -21.5W49–31 | 52.5 | W49–31 | O | N |
| Sat 9/30 | Toledo vs Northern Illinois | -13.0W35–33 | 48.0 | W35–33 | O | N |
| Sat 10/7 | Toledo at Massachusetts | -19.0W41–24 | 55.5 | W41–24 | O | N |
| Sat 10/14 | Toledo at Ball State | -17.5W13–6 | 48.5 | W13–6 | U | N |
| Sat 10/21 | Toledo at Miami (OH) | -2.0W21–17 | 46.5 | W21–17 | U | Y |
| — Bye Week — | ||||||
| Tue 10/31 | Toledo vs Buffalo | -14.0W31–13 | 47.0 | W31–13 | U | Y |
| Wed 11/8 | Toledo vs Eastern Michigan | -19.5W49–23 | 45.5 | W49–23 | O | Y |
| Tue 11/14 | Toledo at Bowling Green | -9.5W32–31 | 48.5 | W32–31 | O | N |
| Fri 11/24 | Toledo at Central Michigan | -12.5W32–17 | 54.5 | W32–17 | U | Y |
| Sat 12/2 | Toledo vs Miami (OH) | -8.5L14–23 | 46.0 | L14–23 | U | N |
| Sat 12/30 | Toledo vs Wyoming | +4.5L15–16 | 43.5 | L15–16 | U | Y |
Illinois 2023 Schedule
Illinois's 2023 Schedule
| Date | Matchup | Spread | Total | Result | O/U | Cover |
|---|---|---|---|---|---|---|
| Sat 9/2 | Illinois vs Toledo | -7.0W30–28 | 45.5 | W30–28 | O | N |
| Fri 9/8 | Illinois at Kansas | +3.5L23–34 | 57.5 | L23–34 | U | N |
| Sat 9/16 | Illinois vs Penn State | +14.0L13–30 | 47.5 | L13–30 | U | N |
| Sat 9/23 | Illinois vs Florida Atlantic | -16.0W23–17 | 45.5 | W23–17 | U | N |
| Sat 9/30 | Illinois at Purdue | +1.0L19–44 | 54.0 | L19–44 | O | N |
| Fri 10/6 | Illinois vs Nebraska | -3.5L7–20 | 43.0 | L7–20 | U | N |
| Sat 10/14 | Illinois at Maryland | +13.5W27–24 | 52.0 | W27–24 | U | Y |
| Sat 10/21 | Illinois vs Wisconsin | +3.0L21–25 | 40.5 | L21–25 | O | N |
| — Bye Week — | ||||||
| Sat 11/4 | Illinois at Minnesota | +1.5W27–26 | 43.0 | W27–26 | O | Y |
| Sat 11/11 | Illinois vs Indiana | -4.5W48–45 | 43.5 | W48–45 | O | N |
| Sat 11/18 | Illinois at Iowa | +2.5L13–15 | 33.5 | L13–15 | U | Y |
| Sat 11/25 | Illinois vs Northwestern | -5.0L43–45 | 46.5 | L43–45 | 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
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 · 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?
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
Actual Result
CSS Battle
Toledo
1 — 3 sequences
✗ Predicted incorrectly
GC Battle
Illinois
66.6 — 20.0 GC score
✗ Predicted incorrectly
Game Result
Illinois won by 2
Spread Context
ATS Historical Context
Based on 2021–2025 backtest · FBS vs FBS · Regular season
Both metrics agree on Illinois, 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
56–33 (63%)
· Yr 8 at school
OC
Mike Hallett
Yr 3
#1
DC
Vince Kehres
Yr 3
#1
Illinois
Bret Bielema #1
14–14 (50%)
· Yr 3 at school
OC
Barry Lunney Jr.
Yr 2
#1
DC
Aaron Henry
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 ✓