Bowling Green at UCLA Week 1 College Football Matchup Bowling Green at UCLA Matchup - Week 1
Sat, Sep 3 2022 · Week 1 · 🏟 Rose Bowl Pasadena, CA · Turf · 92,542 cap
Bowling Green✈ 1,937 mi-3 hr TZ
17 45
Final
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📊 Punt & Rally Projection
Bowling Green
14
UCLA
45
P&R Line UCLA -31
P&R Total O/U 59.5
Confidence 86 High
Vegas UCLA -24 · O/U 56.5
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
UCLA -24
O/U 56.5
teamrankings
Advanced Stats
PPA + Success Rate agree → UCLA · 73.9% ATS historically
↓ See full breakdown
Bowling Green 2022 Schedule
Bowling Green's 2022 Schedule
DateMatchupSpreadTotalResultO/UCover
Sat 9/3Bowling Green at UCLA+24.0L17–4556.5L17–45ON
Sat 9/10Bowling Green vs Eastern Kentucky-7.5L57–5957.0L57–59ON
Sat 9/17Bowling Green vs Marshall+17.0W34–3150.0W34–31OY
Sat 9/24Bowling Green at Mississippi State+31.0L14–4553.0L14–45OY
Sat 10/1Bowling Green at Akron-9.0W31–2849.5W31–28ON
Sat 10/8Bowling Green vs Buffalo+2.0L7–3855.5L7–38UN
Sat 10/15Bowling Green vs Miami (OH)+7.0W17–1345.0W17–13UY
Sat 10/22Bowling Green at Central Michigan+5.5W34–1851.0W34–18OY
— Bye Week —
Wed 11/2Bowling Green vs Western Michigan-5.0W13–948.0W13–9UN
Wed 11/9Bowling Green vs Kent State+2.5L6–4055.5L6–40UN
Tue 11/15Bowling Green at Toledo+14.5W42–3547.0W42–35OY
Tue 11/22Bowling Green at Ohio+5.5L14–3852.5L14–38UN
Mon 12/26Bowling Green vs New Mexico State-3.0L19–2451.0L19–24UN
UCLA 2022 Schedule
UCLA's 2022 Schedule
DateMatchupSpreadTotalResultO/UCover
Sat 9/3UCLA vs Bowling Green-24.0W45–1756.5W45–17OY
Sat 9/10UCLA vs Alabama State-48.5W45–761.5W45–7UN
Sat 9/17UCLA vs South Alabama-15.5W32–3159.5W32–31ON
Sat 9/24UCLA at Colorado-22.0W45–1757.0W45–17OY
Fri 9/30UCLA vs Washington+2.5W40–3265.0W40–32OY
Sat 10/8UCLA vs Utah+3.0W42–3264.5W42–32OY
— Bye Week —
Sat 10/22UCLA at Oregon+7.0L30–4570.5L30–45ON
Sat 10/29UCLA vs Stanford-16.5W38–1364.5W38–13UY
Sat 11/5UCLA at Arizona State-11.0W50–3666.5W50–36OY
Sat 11/12UCLA vs Arizona-19.5L28–3476.5L28–34UN
Sat 11/19UCLA vs USC+2.5L45–4876.5L45–48ON
Fri 11/25UCLA at California-11.5W35–2862.5W35–28ON
Fri 12/30UCLA vs Pittsburgh-9.0L35–3755.0L35–37ON
Advanced Stats
Advanced Analytics Matchup
Matchup-adjusted (offense vs opponent defense) · 2022 season
UCLA PPA Edge
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
→ UCLA
Individual Factors — Ranked by Predictive Strength
PPA Overall
Points added per play · Elite predictor
Bowling Green
+0.384
UCLA
+0.551
UCLA Edge
PPA Passing
Pass efficiency edge · Strong predictor
Bowling Green
+0.567
UCLA
+0.676
UCLA Edge
Havoc Total
Def. disruption rate · Strong predictor
Bowling Green
0.184
UCLA
0.125
TFLs, sacks, PBUs, forced fumbles — higher is better
Bowling Green Edge
Points Per Opp
Drive-finishing edge · Strong predictor
Bowling Green
+7.087
UCLA
+8.580
UCLA Edge
Success Rate
Play consistency edge · Solid predictor
Bowling Green
+0.858
UCLA
+0.958
UCLA Edge
Field Position
Avg start (lower=better) · Solid predictor
Bowling Green
69.9
UCLA
70.6
Avg yards from own endzone to average start — lower is better · longer bar = better field position
Bowling Green Edge
Advanced stats sourced from CFBD · 2022 season · Edges are matchup-adjusted (offense vs opponent defense)
Power Ratings
Team Power Ratings
Overall · Offense · Defense ratings · Updated as season progresses
UCLA Rated Higher
Overall Power Rating
Bowling Green
-9.7
UCLA
6.6
Offense Rating
Bowling Green
10.9
UCLA
19.6
Defense Rating (lower = better defense)
Bowling Green
20.7
UCLA
12.9
Power ratings updated throughout the season as results accumulate
Momentum Control (CSS)
Consecutive Scoring Sequences Who builds scoring momentum? Bowling Green Edge
Avg sequences created per game
Bowling Green #97
0.00
UCLA #40
0.00
Avg sequences allowed per game (lower is better)
Bowling Green #122
0.00
UCLA #31
0.00
Bowling Green +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? Bowling Green Edge
Avg GC score per game (offense)
Bowling Green #1
0.0
UCLA #1
0.0
Avg GC score allowed per game (lower is better)
Bowling Green #110
0.0
UCLA #20
0.0
Bowling Green +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
UCLA
2 — 1 sequences
✗ Predicted incorrectly
GC Battle
UCLA
83.0 — 8.3 GC score
✗ Predicted incorrectly
Game Result
UCLA won by 28
Spread Context
ATS Historical Context
Based on 2021–2025 backtest · FBS vs FBS · Regular season

Both metrics agree on UCLA, 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
Bowling Green
Scot Loeffler #1
7–22 (24%) · Yr 4 at school
OC Terry Malone Yr 2 #1
DC Eric Lewis Yr 2 #1
Staff Rating
0.00 #1
UCLA
Chip Kelly #1
18–25 (42%) · Yr 5 at school
OC Chip Kelly Yr 1 #1
DC Bill McGovern Yr 1 #1
Staff Rating
0.00 #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