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Understanding Our Predictions

🤖 What Do the Percentages Mean?

Our machine learning models calculate the true probability of each player winning:

Example: 65% = player has 65% chance to win based on historical data analysis

65%
Win Probability

💰 What is "No-Vig" or "Fair Odds"?

Sportsbooks build in a profit margin (the "vig" or "juice") to all bets. We remove this to show you the true fair value.

Sportsbook Example:
Player A: -150
Implied: 60%
Player B: +130
Implied: 43%
Total: 103% (3% vig)
Our Fair Odds:
Player A: -140
True: 58%
Player B: +140
True: 42%
Total: 100% (no vig)
Key Takeaway

Our odds represent the true probability without bookmaker profit margins.

🎯 When Should You Consider Betting?

✅ Potential Value

Sportsbook offers BETTER odds than our fair value

Our Fair:
+150
Sportsbook:
+180

You're getting more value than the true probability suggests

❌ Less Value

Sportsbook offers WORSE odds than our fair value

Our Fair:
-140
Sportsbook:
-160

You're getting less value than the true probability suggests

💡 Pro Tip: Look for Value Discrepancies

The biggest opportunities come when our models strongly disagree with sportsbook odds. When we show 70% probability but sportsbooks price it like 60%, that's potential value!

Quick Reference Guide

📊
Reading Match Cards
  • Win Probability: Our model's predicted chance to win
  • Fair Odds: True value without bookmaker margin
  • Confidence Meter: Visual indicator of prediction strength
Using the Data
  • Compare our fair odds with sportsbook offerings
  • Focus on matches with clear probability edges
  • Use head-to-head history for additional context