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Methodology

Last updated: 2026-05-26 · v1.0.1

How we surface +EV markets — the math, the signals, and the boundaries we know about. No marketing, no logos.

1. Reference data

The system aggregates prices and signals from a curated set of references chosen for accuracy, not visibility. We don't publish the list — that's intentional, see §7.

Sharp market consensus

A basket of low-vig reference books, used to estimate true probabilities.

Regulated sharp markets

Cross-validation on major North American leagues.

Exchange liquidity

Peer-to-peer prices as a sanity check on bookmaker odds.

Event metadata

Injury reports, confirmed lineups, weather, historical splits.

Market intelligence

Sharp-money flow, reverse-line-movement flags, steam detection.

Streaming odds feeds

Real-time refresh across every tracked market.

If you want to know whether a specific book was covered for a given pick, the answer is in the transparency log. Every published pick lists the books that priced it at publication.

2. EV calculation

EV%    = (p_true × decimal_odds − 1) × 100
p_true = 1 / no_vig_implied_odds

True probability is obtained by removing the bookmaker margin from sharp consensus lines at the moment of market open, before late action displaces them. Default: multiplicative devig method. Logarithmic and Shin variants are exposed under advanced filters.

The EV figure shown next to each pick is the edge against the best price available at publication — not the price you'll see at click time. Lines move.

3. CLV (Closing Line Value)

CLV% = (bet_odds / close_odds − 1) × 100

CLV measures whether you beat the line at close. A bettor with persistent positive CLV has a real edge regardless of short-term win rate. Target: CLV > +1.5% averaged over 500+ settled bets.

CLV is the only metric we trust for long-horizon evaluation. Hit rate, profit, and ROI on small samples are noise.

4. Sharp signal

Three independent inputs blended into one normalized score (0–100):

  • Directional agreement across our reference books
  • Reverse line movement (line moves against the public)
  • Steam detection (synchronized moves across multiple books within a narrow window)

Score > 55: sharp side aligns with model. > 75: unanimous. < 40: not published.

5. Publication threshold

EV    > +2.0%
Sharp > 55
Books ≥ 3 offering the price

Parlays are not algorithmically recommended. Combined edge degrades multiplicatively and most parlay structures hide correlation that the math doesn't catch.

6. Known limitations

  • Closing-line data carries ~30s latency from the underlying market.
  • Injury and lineup data is pulled from public feeds. Late scratches and warmup decisions may not propagate in time.
  • Free accounts see odds with a 15-minute display delay.
  • The model does not estimate correlation across legs in custom parlays.
  • Small-sample warning: EV figures over fewer than 200 settled bets are statistically meaningless.

7. Why we don't publish the source list

  • Operational

    Naming the reference books invites them to throttle or block our access. The stack was assembled to survive that pressure — naming it defeats the point.

  • Honest

    The value isn't which sources we use, it's how they're combined, devigged, and timed. A vendor list wouldn't help you reproduce the signal.

  • Boring

    A public source list reads like a brochure. We're shipping a tool, not selling logos.

Found a methodological error? Open it on /transparency.

We post corrections in the /changelog.