Yesterday's Canada 28 draws, spanning 402 rounds from 3461094 to 3461495, revealed intriguing trends. Data shows that small numbers had a slight edge with a 50.75% occurrence rate, while odd numbers led the odd/even ratio at 51.24%. Among hot numbers for sum values, 13 appeared most frequently, with 33 occurrences, accounting for 8.21%. Additionally, spans were primarily concentrated between 4 and 6, totaling 175 rounds or approximately 43.53% of all draws.
Analysis of Top Five AI Algorithms
Based on yesterday's statistics, the average hit rate across 30 AI algorithms on this platform was 40.93%. Leading the pack was the "Anti-Martingale" algorithm, achieving a hit rate of 45.62%. Its number accuracy stood out at 55.33%, surpassing the average by about 14.4 percentage points. Following closely was the "Deep Neural Network" algorithm, with a hit rate of 44.86% and the highest number accuracy among all algorithms at 55.84%.
The "Deep Learning" and "Local Entropy" algorithms demonstrated similar hit rates, both around 44.7%, showcasing steady predictive capabilities. Meanwhile, the "Kelly Criterion" and "Deep Learning" algorithms tied for fourth place, each achieving a hit rate of 44.73%.
Performance of the Bottom Three Algorithms
On the lower end, the "Two-Step Transition" and "Volatility" algorithms recorded hit rates of 33.44% and 33.5%, respectively, significantly below the average. The "Two-Step Transition" algorithm, in particular, struggled with number accuracy, achieving only 10.15%, indicating sensitivity issues with specific patterns. The "Bayesian Algorithm" fared slightly better, with a hit rate of 34.84%, but still showed room for improvement.
Observations on Cold and Hot Numbers
Yesterday's cold number data highlighted several numbers missing for 230 consecutive rounds, including sum values 0, 1, 25, 26, and 27. In contrast, hot numbers were concentrated around sum values 13, 12, and 16, appearing 33, 32, and 31 times respectively.
Additional Insights
Overall, yesterday's Canada 28 AI algorithm performance was stable, with intense competition among the top five. The fluctuations observed in the bottom three algorithms may point to differences in data adaptability, which warrants further attention.