Daily 2026-07-05 00:30:00 6 min read 0 views

Hot Numbers Dominate While Cold Numbers Stay Absent

Summary:On July 4, 2026, Canada 28 data showed sum 14 as the most frequent hot number, appearing 9.95% of the time, while cold numbers continued their absence. AI algorithms achieved an overall accuracy of 42.3%.

According to yesterday's Canada 28 data (July 4, 2026), a total of 402 draws were conducted. Analyzing the big/small ratio, big numbers (14-27) appeared 219 times, accounting for 54.48%, while small numbers (0-13) appeared 183 times, making up 45.52%. Regarding odd/even distribution, even numbers were drawn 206 times (51.24%), and odd numbers appeared 196 times (48.76%).

Hot Numbers Dominate

Statistics indicate that sum 14 was the most frequent hot number yesterday, appearing 40 times and accounting for 9.95% of all draws. Additionally, sums 12 and 13 each appeared 30 times, representing 7.46% each. Sums 15 and 18 rounded out the top five, appearing 29 and 28 times, respectively. This concentration of hot numbers has been a noticeable trend in recent data.

Cold Numbers Stay Absent

As for cold numbers, sums 0 and 27 have each gone 230 consecutive draws without appearing, maintaining their cold status. Sum 26 has been absent for 196 draws, last appearing in draw number 3452858. Other cold numbers, such as sums 1 and 6, have not appeared in the last 124 and 94 draws, respectively. This widespread absence of cold numbers is a trend worth monitoring.

AI Algorithm Performance

Data from 30 AI algorithms showed an overall accuracy rate of 42.3% yesterday. The Monte Carlo algorithm led with an accuracy of 47.83%, followed closely by the Volatility and Mean Reversion algorithms, both at 47.27%. The Dual-Step Transition algorithm performed the worst, with an accuracy of only 37.06%. Analysis of sample data across all 402 draws indicates consistent performance by the Monte Carlo algorithm.

Further Observations

The high concentration of hot numbers may signal short-term pattern shifts, while the continued absence of cold numbers presents challenges for predictive models.

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