About JP+

JP+ is an independent college football power ratings model. It rates every FBS team using opponent-adjusted play-by-play efficiency data, then converts those ratings into projected game spreads, win totals, and betting edges.

What Makes JP+ Different

Most public ratings (AP Poll, CFP Rankings, even some computer models) are built on outcomes: wins, losses, and point margins. JP+ ignores outcomes and measures how teams actually play on each snap. Two teams can both win 35-14, but one did it with 55% Success Rate against a top-20 defense while the other did it with 38% Success Rate against a bottom-20 defense and got lucky with three turnovers. JP+ sees the difference.

The model is also market-blind. Vegas lines are never used as inputs or training targets. When JP+ disagrees with Vegas, that disagreement is the signal — not an error to correct.

How the Model Works

Efficiency Foundation Model (EFM)

The core engine is a Ridge Regression trained on play-by-play data from every FBS game. Each team gets an opponent-adjusted offensive and defensive rating built from three inputs:

  • Success Rate — Did the play gain enough yards to stay on schedule?
  • Isolated Points Per Play — How explosive is each play, measured in expected points added, isolated from field position?

Special Teams

A separate model rates field goal accuracy, punt net yardage, and kickoff returns. Special teams ratings feed directly into the spread prediction without a cap.

Preseason Priors

Before the season starts, each team's prior-year offensive, defensive, and special teams ratings are carried forward with mean reversion, then adjusted for coaching changes, recruiting talent, and transfer portal activity. As the season progresses and real play-by-play data accumulates, the priors are gradually replaced by in-season efficiency data.

Walk-Forward Design

Every prediction is made using only data available before that game. The model never sees future games when making a prediction — the same constraint you face when placing a bet. This is validated across the full 2022-2025 backtest with strict chronological guards.

Data Freshness

During the season, ratings and picks are updated each Sunday morning after play-by-play data becomes available from the previous day's games. Opening lines are captured when sportsbooks first post them (typically Sunday morning). During the preseason, ratings are static projections based on prior-year performance, recruiting, and transfer portal activity.

How to Use JP+

  1. 1

    Check the Power Ratings

    See where every FBS team stands on offense, defense, and special teams. The gap between two teams' ratings approximates the projected point spread — before home field is applied.

  2. 2

    Browse the Picks Page

    Weekly spread, total, and moneyline parlay recommendations where JP+ disagrees meaningfully with Vegas opening lines. Filtered for the highest-confidence situations with the strongest historical edge.

  3. 3

    Dig Into Team Stories

    Click any team on the Resume Ratings page for a game-by-game season breakdown — scores, JP+ projections, and Vegas lines side by side. Great for understanding why a team is rated where it is.

Validated Performance (2022-2025)

Walk-forward backtest across 4 seasons (3,481 regular-season games, weeks 1-15). No postseason — opt-outs, coaching changes, and motivation variance make bowls a different sport. The model predicts each game using only prior data, then its line is compared to Vegas to determine if the pick covered.

MarketATSROI
All Spreads52.0%
5+ Edge (Full Szn)56.7%+9.1%
5+ Edge (Core)59.0%+13.9%
Spread Picks63.7%+23.7%
Game O/U Picks68.9%+34.7%
Team Totals66.8%+30.3%
Win Totals68.9%+39.6%

Regular season only (weeks 1-15, no postseason). All ATS vs opening lines. MAE = Mean Absolute Error (average miss in points). Win totals: 2023-2025, 20%+ EV with probability margin filter. Break-even at -110 = 52.4%. Production bet-list rows are in-sample — the selection filters were tuned on this same data. The blind holdout box below is the honest forward number.

The numbers aren't cherry-picked

A common trap in sports analytics: a model looks great on the same data it was built on. To guard against that, JP+ uses a blind holdout test — the model is tuned on three seasons and then evaluated on a fourth season it has never seen, four times over. Every season acts as the "blind year" once. The result: 61.4% ATS on data the model had no access to when its parameters were set — profitable in all four holdout years.

56.9%
2022 blind
65.0%
2023 blind
64.2%
2024 blind
58.8%
2025 blind

Realistic forward expectation: ~61.4% ATS — about 9 points above the 52.4% break-even needed to profit at standard juice.

Signal Flags & Sizing (2022–2025)

Every JP+ pick carries one or more signal flags — structural patterns that explain why the model likes the side. Flags serve two purposes: they label the thesis behind each bet, and when a flag represents an independently validated edge, they increase stake sizing.

Most flags are 1.0× (standard stake). The model's core engine already qualified the pick — the flag adds context, not the conviction. Roster Alignment is in this group: it is an early-season trust cue, not a premium sizing signal. A few flags earn 2.5× sizing when the pattern is strong enough across all four backtest seasons.

FlagRecordATSSize
Def Dom20-676.9%2.5×
Away Conviction124-6167.0%2.5×
SR Dominant32-1765.3%1.0×
Market Lag45-2960.8%1.0×

When multiple flags land on the same pick, sizing increases to 2.5× (the cap). Most flags are applied to 5+ pt edge picks in core weeks (4–15). Roster Alignment applies only in Weeks 1-2 and is reported on its admitted raw pre-selection validation surface. Records are vs opening lines across all four seasons.

How Picks Are Selected

Not every game where JP+ disagrees with Vegas makes the pick list. Games pass through three filters before surfacing as a recommendation:

  1. Edge threshold — JP+'s projected spread must disagree with Vegas by at least 5 points. Smaller edges don't reliably overcome the vig.
  2. Sigma qualification — A game-specific uncertainty model estimates how confident JP+ is in its own prediction. Games where the model's uncertainty is high relative to its edge are filtered out — even a large edge means little if the model isn't confident.
  3. Expected value — Each remaining game is priced against the vig to confirm positive expected value. If a pick doesn't clear EV after accounting for the -110 juice, it's dropped.

Three structural vetoes remove game profiles that historically neutralize the edge regardless of magnitude. Vetoed games are shadow-tracked but not staked.

How to Read the Ratings

Each team's JP+ Overall rating is measured in points versus FBS average. A team rated +20 is roughly 20 points better than average per game. The gap between two teams' ratings approximates the projected point spread before home field is applied.

The overall rating is the sum of three components:

  • Offense — Higher is better. A +10 offense generates ~10 more points per game than average.
  • Defense — Higher is better (fewer points allowed). A +10 defense allows ~10 fewer points per game than average.
  • Special Teams — Field goals, punting, and kickoff returns. Typically ranges from -2.5 to +2.5.

JP+ vs Other Models

vs SP+ (ESPN): Both use play-by-play efficiency and publish projected lines vs Vegas. SP+ optimizes for prediction accuracy (minimizing spread error) and positions itself as a measure of team quality rather than a betting model. JP+ optimizes for ATS edge — a fundamentally different objective that prioritizes finding market mispricings over minimizing MAE.

vs FPI (ESPN): FPI blends efficiency with win probability and recruiting. It's designed for editorial rankings, not spread prediction. JP+ is purpose-built for betting edge.

vs Sagarin / Massey: These are margin-of-victory models that use final scores. JP+ uses play-level data, which is more predictive because it separates process from luck.