Tennis Totals

Tennis Totals Model

Match total games predictions for ATP and WTA tours using serve statistics, surface adjustments, and format-specific modeling.

Methodology

The Tennis Totals model projects expected total games in a match by analyzing serve and return statistics for both players. The core formula combines hold probabilities, tiebreak likelihood, and expected set count.

// Core Projection Formula

Expected_Total = Games_Per_Set × Expected_Sets

Where:

Games_Per_Set = f(Hold_A, Hold_B, Tiebreak_Prob)

Expected_Sets = f(Skill_Differential, Format)

ATP Parameters

• Avg Serve Points Won: 64%
• Avg Hold Rate: 82%
• Std Dev (Bo3): 3.5 games
• Std Dev (Bo5): 5.8 games

WTA Parameters

• Avg Serve Points Won: 54%
• Avg Hold Rate: 58%
• Std Dev (Bo3): 4.0 games
• All matches Best of 3

Key Factors

Serve Statistics

Player-specific serve point win % and hold % from historical match data. Determines baseline game expectations.

Surface Adjustments

Hard, clay, and grass surfaces affect serve dominance and tiebreak frequency. Clay = more breaks, grass = more holds.

Format Detection

Automatic Bo3 vs Bo5 detection for ATP Grand Slams. Critical for accurate total projections (40 vs 23 games).

Tour-Specific Modeling

ATP and WTA have different baseline parameters reflecting serve dominance differences between tours.

Frequently Asked Questions

We use Jeff Sackmann's comprehensive tennis databases, which include match-level statistics for ATP and WTA tours dating back decades. The model pulls serve point win percentage, service games held, and return statistics for each player. Data is automatically refreshed to use the most recent available year.

The model uses a multi-step process: (1) Calculate matchup-based hold rates using each player's serve percentage against the opponent's return ability, (2) Estimate tiebreak probability based on combined hold rates, (3) Calculate expected games per set considering break likelihood, (4) Estimate expected number of sets based on skill differential, (5) Multiply games per set by expected sets for the total projection.

ATP and WTA tours have fundamentally different serve dynamics. ATP players typically win 64% of serve points with 82% hold rates, while WTA players average 54% serve points won with 58% hold rates. This means WTA matches generally have more breaks of serve and different game totals. The model uses tour-specific parameters for accurate projections.

The model automatically detects the match format based on the tournament. ATP Grand Slam events (Australian Open, French Open, Wimbledon, US Open) use Best of 5 sets, while all WTA matches and other ATP events use Best of 3. This is crucial because Bo5 matches average 38-42 total games versus 21-24 for Bo3.

Each surface has different characteristics: Hard courts use baseline parameters, Clay courts reduce hold rates (more breaks) and lower tiebreak probability, Grass courts increase hold rates and tiebreak frequency. These adjustments are applied to both the games-per-set and tiebreak probability calculations.

Edge represents the difference between our projected total and the book's line, measured in standard deviations. An edge of 1.0 SD means our projection is one standard deviation away from the book line. Higher absolute edge values indicate stronger disagreement with the market.

Matches are skipped when player data is insufficient. If a player has fewer than 10 matches in our database, or if we cannot find a reliable name match, the projection is skipped rather than using unreliable default values. This ensures all picks have solid statistical backing.

Confidence tiers (MAX, STRONG, STANDARD) are based on a combination of: expected value (EV), edge percentage, and z-score. MAX tier requires the highest thresholds across all three metrics. Only picks that pass minimum thresholds are surfaced as recommendations.

Picks are generated and locked daily at 10:00 AM ET. This timing ensures we have the latest odds data while giving you time to act before matches begin. The model limits output to the top 8 picks by edge strength each day.

Standard deviation varies by match format and player skill differential. Bo3 matches typically have SD of 3.5-4.5 games, while Bo5 matches have SD of 5.5-6.5 games. WTA matches tend toward higher variance due to more frequent service breaks.