Utah faces lawsuit from prediction market exchange Kalshi over gambling classification
Kalshi sues Utah officials, arguing federal CFTC oversight preempts state gambling enforcement of its prediction markets.
Chris Habib
How AI Helps Detect Gambling Addiction Patterns
How AI analyzes betting behavior to flag risky patterns, enable early intervention, and support responsible gambling.
How Adaptive Retraining Impacts Historical Benchmarks
Adaptive retraining improves prediction accuracy but complicates historical benchmarks; use calibration, NLL and real-time validation to avoid collapse.
Cross-Validation vs. Backtesting in Betting Models
Purged cross-validation plus walk‑forward backtesting reveals whether betting models truly generalize — CV finds overfitting, backtesting verifies ROI and risk.
Live Betting Stake Adjustments: Pro Tips
Clear live-betting rules for stake sizing, fractional Kelly, hedging, and bankroll limits to control emotion and manage in-play risk.
Hit Rate vs ROI: Which Metric Matters More?
Why ROI—not hit rate—determines betting success: odds, value bets and calibration drive real profitability, not raw win percentage.
Checklist for Using NLP in Betting
Step-by-step checklist for using NLP in sports betting: collect and clean data, track sentiment and odds, find value bets, backtest and validate.
Public Money vs. Consensus Models: Historical Results
Why public bettors often lose, how consensus models improve predictions, and where mismatches create value bets for profitable sports wagering.
Real-Time Alerts for Retraining Workflows
Real-time drift alerts tied to automated retraining minimize model decay and downtime, keeping sports-betting predictions reliable.
How AI Tracks Player Possession Value
How AI assigns Possession Value to every action using tracking, EPV, xT and pitch-control to reveal hidden player impact and live betting insights.
Edge Decay in Prediction Markets
Learn how prediction-market edges erode over time, how to spot decay using CLV, spreads and calibration, and practical hedging and sizing tactics.
Top Hyperparameters for Sports Betting Models
Calibration-focused hyperparameter tuning (learning rate, depth, batch size, min samples per leaf) yields higher ROI in sports betting than accuracy-only models.