Advanced Baseball Game Prediction Model

A sophisticated logistic regression model that calculates win probabilities based on multiple performance metrics

Game Parameters

Team Performance (TP)

Weighted average of win percentage: TP = 0.7 × (Last 10 Games Win %) + 0.3 × (Season Win %)

Starting Pitcher (SPS)

SPS = (League Avg. ERA / Pitcher ERA) × (League Avg. WHIP / Pitcher WHIP)

Bullpen Strength (BS)

Bullpen ERA and WHIP compared to league average (similar to SPS calculation)

Batting Strength (BAT)

BAT = 0.5 × OPS + 0.3 × wOBA + 0.2 × Runs/Game

Injury Impact (INJ)

INJ = Total WAR of Injured Players / Team's Total WAR

Head-to-Head (H2H)

Home team's win percentage against the opponent in the last 5 meetings

Weather Factor (WTH)

1.0 for neutral, 0.9 for rain (pitcher-friendly), 1.1 for strong wind (hitter-friendly)

Home Field Advantage

Binary parameter: 1 for home team, 0 for away. Coefficient typically ~0.24 (54% win probability)

Prediction Results

Win Probability

Home Team Away Team
50% 50%

Key Factors

Team Performance +0.15
Starting Pitcher +0.80
Batting Strength +0.07
Injury Impact -0.05
Home Field Advantage +0.24

Probability Formula

P(Home Win) = 1 / (1 + e-z)

Where z = β₀ + Σ(βᵢ × Xᵢ)

Model Interpretation

Probabilities above 70% indicate strong favorites, while 55-60% suggests a slight edge. Values between 45-55% represent essentially even matchups.

Model Details

Logistic Regression Formula

P(Home Win) = 1 / (1 + e-(β₀ + ΣβᵢXᵢ))

This logistic function converts the weighted sum of input parameters into a probability between 0 and 1.

Each parameter (Xᵢ) represents the difference between home and away team metrics, except for binary factors like home field advantage.

Parameter Weights (β coefficients)

Intercept (β₀) 0.50
Team Performance (β₁) 2.00
Starting Pitcher (β₂) 1.20
Batting Strength (β₃) 1.50
Bullpen Strength (β₄) 0.80
Home Field (β₅) 0.24
Injury Impact (β₆) -0.50

Example Calculation

Given differences: TP = +0.15, SPS = +0.8, HFA = 1, INJ = -0.1

z = 0.5 + (2.0 × 0.15) + (1.2 × 0.8) + (0.24 × 1) + (-0.5 × -0.1)

z = 0.5 + 0.3 + 0.96 + 0.24 + 0.05 = 2.05

P(Home Win) = 1 / (1 + e-2.05) ≈ 88.6%

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