Sat, Sep 21 2024
·
Week 4
·
🏟 Houchens Industries-L. T. Smith Stadium
Bowling Green, KY
·
Turf
·
22,113 cap
Toledo✈ 356 mi-1 hr TZ
Matchup Prediction
Metrics disagree on this matchup
Momentum Control favors Western Kentucky,
while Game Control favors Toledo.
Split signals historically show weaker predictive confidence — treat as a toss-up.
⚡ Split Signal — Metrics Disagree
Momentum Control
71.6%
Western Kentucky wins
Solid
Game Control
75.9%
Toledo wins
Solid
Vegas Spread
Toledo -2
O/U 60.5
DraftKings
Advanced Stats
PPA + Success Rate agree → Toledo
· 73.9% ATS historically
↓ See full breakdown
Toledo 2024 Schedule
Toledo's 2024 Schedule
| Date | Matchup | Spread | Total | Result | O/U | Cover |
|---|---|---|---|---|---|---|
| Thu 8/29 | Toledo vs Duquesne | -27.5W49–10 | 53.5 | W49–10 | O | Y |
| Sat 9/7 | Toledo vs Massachusetts | -17.5W38–23 | 50.5 | W38–23 | O | N |
| Sat 9/14 | Toledo at Mississippi State | +10.5W41–17 | 56.5 | W41–17 | O | Y |
| Sat 9/21 | Toledo at Western Kentucky | -2.0L21–26 | 60.5 | L21–26 | U | N |
| — Bye Week — | ||||||
| Sat 10/5 | Toledo vs Miami (OH) | -4.5W30–20 | 44.0 | W30–20 | O | Y |
| Sat 10/12 | Toledo at Buffalo | -10.5L15–30 | 44.5 | L15–30 | O | N |
| Sat 10/19 | Toledo at Northern Illinois | +3.0W13–6 | 42.5 | W13–6 | U | Y |
| Sat 10/26 | Toledo vs Bowling Green | -1.5L26–41 | 47.5 | L26–41 | O | N |
| Sat 11/2 | Toledo at Eastern Michigan | -10.0W29–28 | 54.5 | W29–28 | O | N |
| — Bye Week — | ||||||
| Tue 11/12 | Toledo vs Central Michigan | -15.0W37–10 | 52.5 | W37–10 | U | Y |
| Wed 11/20 | Toledo vs Ohio | -1.5L7–24 | 47.0 | L7–24 | U | N |
| Tue 11/26 | Toledo at Akron | -9.5L14–21 | 50.5 | L14–21 | U | N |
| Thu 12/26 | Toledo vs Pittsburgh | +6.5W48–46 | 48.5 | W48–46 | O | Y |
Western Kentucky 2024 Schedule
Western Kentucky's 2024 Schedule
| Date | Matchup | Spread | Total | Result | O/U | Cover |
|---|---|---|---|---|---|---|
| Sat 8/31 | Western Kentucky at Alabama | +31.0L0–63 | 60.0 | L0–63 | O | N |
| Sat 9/7 | Western Kentucky vs Eastern Kentucky | -18.5W31–0 | 59.5 | W31–0 | U | Y |
| Sat 9/14 | Western Kentucky at Middle Tennessee | -10.5W49–21 | 53.5 | W49–21 | O | Y |
| Sat 9/21 | Western Kentucky vs Toledo | +2.0W26–21 | 60.5 | W26–21 | U | Y |
| Sat 9/28 | Western Kentucky at Boston College | +7.5L20–21 | 48.0 | L20–21 | U | Y |
| — Bye Week — | ||||||
| Thu 10/10 | Western Kentucky vs UTEP | -19.0W44–17 | 55.5 | W44–17 | O | Y |
| Wed 10/16 | Western Kentucky at Sam Houston | +1.5W31–14 | 55.0 | W31–14 | U | Y |
| — Bye Week — | ||||||
| Wed 10/30 | Western Kentucky vs Kennesaw State | -24.0W31–14 | 49.0 | W31–14 | U | N |
| Sat 11/9 | Western Kentucky at New Mexico State | -18.0W41–28 | 53.5 | W41–28 | O | N |
| Sat 11/16 | Western Kentucky vs Louisiana Tech | -11.5L7–12 | 52.5 | L7–12 | U | N |
| Sat 11/23 | Western Kentucky at Liberty | +1.0L21–38 | 56.5 | L21–38 | O | N |
| Sat 11/30 | Western Kentucky vs Jacksonville State | +0.5W19–17 | 62.5 | W19–17 | U | Y |
| Fri 12/6 | Western Kentucky at Jacksonville State | +4.5L12–52 | 58.5 | L12–52 | O | N |
| Wed 12/18 | Western Kentucky vs James Madison | +7.5L17–27 | 50.5 | L17–27 | U | N |
Advanced Stats
Advanced Analytics Matchup
Matchup-adjusted (offense vs opponent defense) ·
2024 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
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 · 2024 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?
Western Kentucky Edge
Western Kentucky +1.00
CSS Edge (season-to-date)
Teams with this edge win 71.6% of games historically
Based on 2 games this season
Game Control (GC)
Win Probability Dominance
Who controls games start to finish?
Toledo Edge
Toledo +22.3
GC Edge (season-to-date)
Teams with this edge win 75.9% of games historically
Based on 3 games this season
Actual Result
CSS Battle
Western Kentucky
1 — 0 sequences
✓ Predicted correctly
GC Battle
Toledo
20.7 — 58.3 GC score
✓ Predicted correctly
Game Result
Western Kentucky won by 5
Spread Context
ATS Historical Context
Based on 2021–2025 backtest · FBS vs FBS · Regular season
CSS and GC disagree on this matchup. When the metrics split, historical cover rates are essentially random — treat this as a coin flip against the spread.
ATS data is informational only. Past cover rates do not guarantee future results.
Coaching Matchup
Toledo
Jason Candle #1
65–35 (65%)
· Yr 9 at school
OC
Mike Hallett
Yr 3
#1
DC
Vince Kehres
Yr 3
#1
Western Kentucky
Tyson Helton #1
40–26 (61%)
· Yr 6 at school
OC
Will Friend
Yr 1
#1
DC
Tyson Summers
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 ✓