Value Betting, Step-by-Step (with Free Calculator)

A fast, practical guide for finding +EV bets on softbooks using Pinnacle as the baseline and sizing them with Kelly.

Open Edge Finder

TL;DR

  • Scan the softbook for interesting prices.
  • For each candidate, use Pinnacle’s search to open the same fixture/market/line and read Pinnacle’s price.
  • Enter both books’ odds into Edge Finder.
  • The tool removes Pinnacle’s overround (vig) → you get fair odds (probabilities) and EV% instantly.
  • If EV% > 0, it’s value. Stake with Kelly (e.g., half-Kelly) and round to your step.
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What is a value bet?

A value bet has positive expected value: the softbook price is better than the fair price implied by true probability. We use Pinnacle as a sharp baseline and de-vig its market to estimate the fair probability.

EV formula: EV = odds × p_fair − 1 → EV% = EV × 100

Step-by-step

  1. Pick the market. Choose 2-way or 1X2. In-play works too, but lines move — refresh inputs as you go.
  2. Scan softbook → look up in Pinnacle. Browse the softbook and note prices that look high. For each one, search in Pinnacle to open the exact same fixture, market, and line (e.g., +0.5 vs +1.0; OT/void/retirement rules).
  3. Enter odds in Edge Finder. Fill in Pinnacle prices for both sides (H/D/A for 1X2), then the softbook prices for the same market.
  4. Read the outputs. You’ll see Fair odds (de-vig), EV%, Spread% per side, and a Recommended stake based on Kelly.
  5. Stake with risk control. Use a Kelly divisor (e.g., 2 = half-Kelly, 4 = quarter-Kelly), set a rounding step (e.g., €5), and respect softbook max limits/boost terms.

The math (short)

  • Implied probability: p_i = 1 / o_i
  • Overround (vig): Σ p_i − 1
  • De-vig fair probability: p_fair_i = p_i / Σ p_i → Fair odds: 1 / p_fair_i
  • Expected value: EV = odds × p_fair − 1 → EV% = 100 × EV
  • Kelly fraction (2-way): f* = (odds × p_fair − 1) / (odds − 1) — Stake: bankroll × f* / (Kelly divisor)

Common pitfalls

  • Comparing different lines/rules (AH vs moneyline, OT included vs not, retirement/void handling).
  • Skipping de-vig — raw implied probabilities overstate Kelly.
  • Going full Kelly by default — larger drawdowns and model-error risk.
  • Ignoring softbook constraints — max stake, boosts, and bet eligibility.