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Tennis Moneyline

Tennis Moneyline Model

Match winner predictions for ATP and WTA tours using surface-weighted player ratings and cross-book line shopping.

Methodology

The Tennis Moneyline model projects match winner probabilities by analyzing player ratings that account for overall performance and surface-specific ability. The model compares these probabilities against sportsbook odds to identify value opportunities.

// Core Projection Formula
Win_Probability = f(Rating_Blend_A, Rating_Blend_B)
Where:
Rating_Blend = (Overall_Rating + Surface_Rating) / 2
Edge = Model_Prob - Implied_Prob

Rating Components

  • • Overall tour rating
  • • Hard court rating
  • • Clay court rating
  • • Grass court rating

Edge Detection

  • • Compare model vs book probability
  • • Shop lines across sportsbooks
  • • Surface minimum edge threshold
  • • Assign confidence tier

Key Factors

Surface-Specific Ratings

Players are rated separately for hard, clay, and grass courts. The match surface determines how ratings are weighted in the final projection.

Line Shopping

The model compares odds across multiple sportsbooks to find the best available price for each player, maximizing potential returns.

Tour Coverage

Full ATP and WTA tour coverage including Grand Slams, Masters 1000, and regular tour events with tour-specific calibration.

Dynamic Ratings

Player ratings update after each match, capturing current form and head-to-head results in an evolving assessment.

Frequently Asked Questions

The model uses a rating system that tracks player performance over time. Each player has both an overall rating and surface-specific ratings (hard, clay, grass). The model blends these ratings based on the match surface to calculate expected win probabilities for each player.
Tennis players often perform differently across surfaces. A clay court specialist may dominate on that surface but struggle on grass. The model maintains separate ratings for each surface type, which are weighted into the final projection based on where the match is being played.
Edge is the difference between the model's calculated win probability and the sportsbook's implied probability from the odds. For example, if the model gives a player 60% win probability but the book implies 45%, that's a 15% edge. Only matches exceeding our edge threshold are surfaced as picks.
The model shops lines across multiple sportsbooks to find the best available odds for each player. The "Best Book" shows which sportsbook is offering the most favorable price. This line shopping can significantly improve long-term returns.
Confidence tiers (MAX, STRONG, STANDARD) are based on edge percentage. Higher edge percentages receive higher confidence tiers and larger recommended unit sizes. MAX tier picks have the strongest model conviction.
Yes, the model covers both ATP (men's) and WTA (women's) tours including Grand Slams, Masters events, and regular tour-level tournaments. Each tour has separately calibrated parameters reflecting the different competitive dynamics.
Picks are generated based on the daily match schedule and locked before matches begin. The model processes all available matches and surfaces recommendations for those exceeding the edge threshold.
Players with insufficient historical data start with baseline ratings. As they play more matches, their ratings become more refined. Matches involving players with very limited data may be skipped to ensure pick quality.
Expected Value represents the theoretical profit per unit wagered based on the model's win probability and the available odds. Positive EV indicates a mathematically profitable bet over the long term, assuming the model's probabilities are accurate.
The rating system naturally captures recent form through match results. However, sudden injuries or withdrawals are not automatically detected. Always verify player status before placing wagers on any recommended pick.