Tennis Matches vs RaysTennisPredict

Updated with 2026 tour dates See the schedule and countdown to the upcoming ATP and WTA tennis tournaments. Features: - add tour dates to calendar - share tennis tournament events - works offline with cached calendar data - shows running tournaments - support for iPhone 6 and 6+ - support for the iPad multitasking (split view..) Apple Watch Features: - countdown to the current and upcoming tennis tournaments - select between ATP and WTA tournaments - watch app and glance interface for a quick lookup

RaysTennis Predict uses advanced statistical models to predict tennis match outcomes with precision. WHAT YOU GET: - TVPI Engine: Our 7-pillar scoring system analyzes serve foundation, return resilience, clutch index, dominance, first strike, form/fatigue, and momentum - Win Probabilities: Percentage-based predictions with implied odds for any ATP or WTA matchup - Tactical Insights: AI-generated battle zones and strategic analysis for each matchup - Radar Charts: Visual pillar-by-pillar comparison between players - Market Edge Detection: Compare TVPI predictions against market odds to find value - TimesFM Forecasts: Optional point-by-point based predictions using historical match data - Blended Predictions: Combined TVPI + TimesFM scores for maximum accuracy - 1st Set ML: First set moneyline predictions with hold/break modeling - Surface-Aware: Separate models for hard, clay, and grass courts - Screenshot Auto-Fill: Take a screenshot of any match and auto-fill player names via OCR HOW IT WORKS: 1. Enter two player names or upload a match screenshot 2. Select surface, tour (ATP/WTA), and tournament level 3. Tap "Run Prediction" for instant TVPI analysis (2 tokens) 4. Optionally run TimesFM for deeper forecasting (1 token) PRICING: - Starter Pack: $3.99 for 10 tokens - Each prediction costs 2 tokens (TVPI + Tactical) - TimesFM add-on costs 1 additional token Covering 1,100+ ATP players and 1,100+ WTA players with data updated weekly. Built for serious tennis fans and bettors who want data-driven edge.