SPORTS BETTING MATH APPLIED PROBABILITY INSTITUTE
APPLIED PROBABILITY INSTITUTE // RESEARCH ARCHIVE

Research Publications

Independent mathematical research, closed-form derivations, and empirical probability studies for sports wagering efficiency.

PILLAR 01 // FAIR ODDS & MARGIN ANALYSIS
LIVE

No-Vig Fair Odds & Bookmaker Overround Decomposition

Mathematical methods for stripping bookmaker margins from odds: Multiplicative, Additive, Power, and Shin's method. Reveals the true implied probability behind every sports betting line.

Core Derivation: P_fair = (1 / O_i) / Σ(1 / O_k)
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PILLAR 02 // EXPECTED VALUE & +EV IDENTIFICATION
LIVE

Expected Value Formula & Why 98% of Bettors Lose to the Margin

Formal derivation of EV = (P_win × (Odds - 1)) - (P_loss × 1). Demonstrates the mathematical inevitability of long-term loss when betting into margins exceeding 5%.

Core Derivation: EV = (P_win × (Odds - 1)) - (P_loss × 1)
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PILLAR 03 // KELLY CRITERION & BANKROLL OPTIMIZATION
LIVE

Kelly Criterion Staking: Full, Half & Quarter Kelly with Risk of Ruin Analysis

Optimal geometric growth bet sizing derived from Kelly's 1956 paper. Covers fractional Kelly variants, tilt protection, drawdown limits, and risk of ruin simulation.

Core Derivation: f* = (b × p - q) / b
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PILLAR 04 // POISSON DISTRIBUTION & MATCH MODELING
LIVE

Poisson Goal Expectancy Engine: 1X2, Over/Under & Correct Score Probabilities

Poisson distribution modeling for football and hockey outcomes. Calculates independent goal probabilities for 1X2, Over/Under 2.5, correct score matrices, and BTTS markets.

Core Derivation: P(X=k) = (λ^k · e^-λ) / k!
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