How the RTP Prediction Model Works
Our prediction engine uses a combination of statistical techniques to estimate probable RTP ranges for the near future:
1. Autoregressive Moving Average
We model daily observed RTP as an AR(1) process with mean-reversion toward the theoretical RTP. The autocorrelation coefficient determines how strongly yesterday's RTP influences tomorrow's prediction.
2. Volatility Estimation
The rolling 7-day standard deviation (σ) determines the width of confidence bands. High-volatility slots have wider prediction ranges. We use σ to compute 50%, 80%, and 95% confidence intervals.
3. Provider & Category Priors
We factor in the average RTP drift across all slots from the same provider, and the slot's volatility category (high, medium, low). These hierarchical priors improve prediction accuracy, especially for slots with fewer days of data.
4. Confidence Intervals Explained
Important Disclaimer: RTP predictions are statistical estimates based on historical data patterns. They do NOT guarantee future outcomes. Each individual spin is completely random and independent of past results. This tool is for educational and entertainment purposes only. The house always maintains a mathematical edge. Please gamble responsibly.