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Intelligent Systems in the Gambling Industry

Explore the use of intelligent systems in the gambling industry, including sports betting predictors, fraud detection algorithms, and machine vision for table monitoring. Discover how these technologies maximize profit, minimize risk, and improve accuracy.

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Intelligent Systems in the Gambling Industry

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  1. Intelligent Systems inthe Gambling Industry Kieran O’Neill 25/03/10

  2. Introduction • Motivation • Sports Betting • Victor the Predictor • MAIT • Accuscore • Casinos • Table-Eye 21 • Conclusion

  3. Motivation • Predicting an outcome is difficult • Requires time and dedication • Often requires luck • Try to predict more favorable odds • Minimize risk • Casinos and Bookmakers • Need to secure their profit • Need to detect cheaters

  4. Victor The Predictor • Neural Network • 30 Input Features • 3 Outputs – Win/Loss/Draw • Single Hidden Layer • Back-propagation Learning

  5. MAIT • Neural Network • Neuron Activation - Sigmoid Function • 83.3% in Rugby World Cup 07 • 55.8% in English Premier League

  6. Accuscore • Clients • ESPN, Yahoo! Sports • 67% Accuracy in 08/09 NFL Season • Evolutionary Algorithms • Simulates each game

  7. Casino Fraud • Lavish casinos built on losers • Casino games generally have “House Advantage” • Blackjack has adjustable house advantage • Card-counting methods lower advantage • Maximize Profit • Lower staff numbers • Reduce croupier errors • Comprehensive Benefits “comps” • Understand players betting patterns

  8. TableEye 21 • Machine Vision Detects • Dealt Card and Suit • Dealer Errors • Card Counting • Bets Placed with RFID • Betting Patterns • Comps for Players

  9. Conclusion • Neural Networks have drawbacks • Models based on teams not players • Accuscore dominates market for now • Machine Vision implemented in casinos • Very accurate feature detection • Need to reduce cost of implementation

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