[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"reports-detail-2026-05-27-span-distribution-en-US":3,"reports-algorithms":39},{"slug":4,"type":5,"extremeSubtype":6,"publishAt":7,"updateTime":8,"coverImage":9,"viewCount":10,"title":11,"metaTitle":12,"metaDesc":13,"summary":14,"content":15,"readMinutes":16,"related":17},"2026-05-27-span-distribution","daily",null,"2026-05-28 00:30:00","2026-05-28 00:30:14","\u002Fstatic\u002Fog\u002F2026-05-27-span-distribution.jpg",0,"Span Extreme Value 9 Returns and Data Distribution Analysis","Canada 28 Daily Analysis: Span Extreme Value 9 and Data Distribution","Yesterday's Canada 28 draw saw the rare return of span extreme value 9. Dive into the day's data distribution and AI algorithm performance for key insights.","Yesterday, span extreme value 9 made a rare appearance, with data distribution concentrated around 6 points. Deep neural networks led AI algorithm performance.","## Span Distribution: Extreme Value 9 Returns\n\nYesterday's Canada 28 draws brought an intriguing phenomenon: the span of three numbers reached the extreme value of 9 points. Data analysis revealed that there were 17 instances of span value 9, accounting for 4.67% of the day's total draws. Why is this noteworthy? Because the span range is limited to 0 through 9, and the occurrence of the extreme value 9 often signals unique patterns that can serve as critical points for further analysis.\n\nNext, let's examine the overall span distribution. The data showed that span value 6 dominated, appearing 63 times and making up 17.31%. Following closely were span values 3 and 4, with 49 and 48 occurrences respectively, representing 13.46% and 13.19%. Span value 0 appeared only 4 times, making it the least frequent.\n\n### Hot Numbers and Cold Numbers: Another Perspective\n\nAmong yesterday's hot numbers, the sum value 14 emerged as the \"winner,\" appearing 33 times and accounting for 9.07% of the total draws. On the other hand, cold numbers displayed extreme behavior, with sum values 0, 3, and 26 having gone 230 consecutive draws without appearing. Such prolonged absences might hint at potential rebounds in future data.\n\n## AI Algorithm Performance: Highlights and Shortcomings\n\nThe performance of AI algorithms yesterday deserves attention. Overall, deep neural network algorithms led the pack with a comprehensive accuracy rate of 45.68%. Their predictive accuracy for numbers was particularly impressive, reaching 53.82%. However, some algorithms underperformed, such as the volatility algorithm, which achieved only a 33.14% accuracy rate. This disparity highlights how different algorithms adapt to daily data variations.\n\n### Special Events: Span Extreme Value and Triple Numbers\n\nIn addition to the return of span extreme value 9, yesterday also featured multiple instances of triple numbers, such as the identical digits in draw 3437606. These rare occurrences often attract significant interest from data analysts.\n\n## Summary\n\nThrough data observation and AI algorithm evaluation, the appearance of span extreme value 9 and the distribution of hot and cold numbers provide valuable insights into future trends. The strong performance of deep neural network algorithms further underscores their adaptability. How will the data evolve next? Stay tuned for more updates.",8,[18,27,33],{"slug":19,"type":20,"extremeSubtype":21,"publishAt":22,"coverImage":23,"viewCount":10,"title":24,"summary":25,"readMinutes":26},"2026-06-03-extreme-triple-5","extreme","E1","2026-06-03 02:01:48","\u002Fstatic\u002Fog\u002F2026-06-03-extreme-triple-5.jpg","Rare Triple Number Emerges: 5+5+5 Stuns in Canada 28","Today's Canada 28 draw 3440224 featured the rare triple number 5+5+5, with an extreme probability of only 1%, marking the second consecutive day of such phenomena.",2,{"slug":28,"type":5,"extremeSubtype":6,"publishAt":29,"coverImage":30,"viewCount":10,"title":31,"summary":32,"readMinutes":16},"2026-06-02-extreme-events","2026-06-03 00:30:00","\u002Fstatic\u002Fog\u002F2026-06-02-extreme-events.jpg","Rare Triple Numbers Appear Frequently, AI Algorithm Shines","Yesterday's Canada 28 draws featured three rare triple numbers, while AI algorithms achieved an impressive 41.6% hit rate, showcasing remarkable performance.",{"slug":34,"type":20,"extremeSubtype":21,"publishAt":35,"coverImage":36,"viewCount":10,"title":37,"summary":38,"readMinutes":26},"2026-06-02-extreme-triple-7","2026-06-02 16:43:49","\u002Fstatic\u002Fog\u002F2026-06-02-extreme-triple-7.jpg","Rare Triple Number Appears: 7+7+7 Stuns in Draw","Draw #3440074 of Canada 28 featured the rare triple number 7+7+7, with a theoretical probability of just 1%, making it an exceptional occurrence.",[40,46,51,57,63,69,75,81,86,92,98,104,110,116,122,128,134,140,145,151,157,163,169,175,181,187,193,199,205,211],{"code":41,"nameZhCn":42,"nameZhTw":43,"nameEnUs":44,"sortOrder":45},"quantum_probability","量子概率引擎","量子機率引擎","Quantum Probability Engine",1,{"code":47,"nameZhCn":48,"nameZhTw":49,"nameEnUs":50,"sortOrder":26},"deep_neural_network","深度神经网络","深度神經網路","Deep Neural Network",{"code":52,"nameZhCn":53,"nameZhTw":54,"nameEnUs":55,"sortOrder":56},"genetic_evolution","遗传进化算法","遺傳進化演算法","Genetic Evolution Algorithm",3,{"code":58,"nameZhCn":59,"nameZhTw":60,"nameEnUs":61,"sortOrder":62},"markov_chain","马尔可夫链","馬可夫鏈","Markov Chain",4,{"code":64,"nameZhCn":65,"nameZhTw":66,"nameEnUs":67,"sortOrder":68},"deep_learning","深度学习","深度學習","Deep Learning",5,{"code":70,"nameZhCn":71,"nameZhTw":72,"nameEnUs":73,"sortOrder":74},"bayesian","贝叶斯推理","貝氏推論","Bayesian Inference",6,{"code":76,"nameZhCn":77,"nameZhTw":78,"nameEnUs":79,"sortOrder":80},"random_forest","随机森林","隨機森林","Random Forest",7,{"code":82,"nameZhCn":83,"nameZhTw":84,"nameEnUs":85,"sortOrder":16},"lstm","LSTM 长短期记忆","LSTM 長短期記憶","LSTM Network",{"code":87,"nameZhCn":88,"nameZhTw":89,"nameEnUs":90,"sortOrder":91},"monte_carlo","蒙特卡洛模拟","蒙地卡羅模擬","Monte Carlo Simulation",9,{"code":93,"nameZhCn":94,"nameZhTw":95,"nameEnUs":96,"sortOrder":97},"clustering","聚类追踪","聚類追蹤","Cluster Tracking",10,{"code":99,"nameZhCn":100,"nameZhTw":101,"nameEnUs":102,"sortOrder":103},"volatility","波动率","波動率","Volatility",11,{"code":105,"nameZhCn":106,"nameZhTw":107,"nameEnUs":108,"sortOrder":109},"edge_value","边缘值","邊緣值","Edge Value",12,{"code":111,"nameZhCn":112,"nameZhTw":113,"nameEnUs":114,"sortOrder":115},"anti_martingale","反马丁格尔","反馬丁格爾","Anti-Martingale",13,{"code":117,"nameZhCn":118,"nameZhTw":119,"nameEnUs":120,"sortOrder":121},"ensemble_voting","综合投票","綜合投票","Ensemble Voting",14,{"code":123,"nameZhCn":124,"nameZhTw":125,"nameEnUs":126,"sortOrder":127},"momentum","动量加速度","動量加速度","Momentum",15,{"code":129,"nameZhCn":130,"nameZhTw":131,"nameEnUs":132,"sortOrder":133},"quantile","分位数","分位數","Quantile",16,{"code":135,"nameZhCn":136,"nameZhTw":137,"nameEnUs":138,"sortOrder":139},"double_step_transition","双步转移","雙步轉移","Double-Step Transition",17,{"code":141,"nameZhCn":142,"nameZhTw":142,"nameEnUs":143,"sortOrder":144},"local_entropy","局部熵","Local Entropy",18,{"code":146,"nameZhCn":147,"nameZhTw":148,"nameEnUs":149,"sortOrder":150},"residual_trend","残差趋势","殘差趨勢","Residual Trend",19,{"code":152,"nameZhCn":153,"nameZhTw":154,"nameEnUs":155,"sortOrder":156},"streak_length","连势长度","連勢長度","Streak Length",20,{"code":158,"nameZhCn":159,"nameZhTw":160,"nameEnUs":161,"sortOrder":162},"decay_missing","衰减遗漏","衰減遺漏","Decay Missing",21,{"code":164,"nameZhCn":165,"nameZhTw":166,"nameEnUs":167,"sortOrder":168},"rule_voting","规则投票","規則投票","Rule Voting",22,{"code":170,"nameZhCn":171,"nameZhTw":172,"nameEnUs":173,"sortOrder":174},"cold_hot_balance","冷热平衡","冷熱平衡","Cold-Hot Balance",23,{"code":176,"nameZhCn":177,"nameZhTw":178,"nameEnUs":179,"sortOrder":180},"kelly","凯利公式","凱利公式","Kelly Criterion",24,{"code":182,"nameZhCn":183,"nameZhTw":184,"nameEnUs":185,"sortOrder":186},"mean_reversion","均值回归","均值回歸","Mean Reversion",25,{"code":188,"nameZhCn":189,"nameZhTw":190,"nameEnUs":191,"sortOrder":192},"autocorrelation","自相关","自相關","Autocorrelation",26,{"code":194,"nameZhCn":195,"nameZhTw":196,"nameEnUs":197,"sortOrder":198},"fibonacci","斐波那契","費波那契","Fibonacci",27,{"code":200,"nameZhCn":201,"nameZhTw":202,"nameEnUs":203,"sortOrder":204},"miss_chase","遗漏追热","遺漏追熱","Miss Chase",28,{"code":206,"nameZhCn":207,"nameZhTw":208,"nameEnUs":209,"sortOrder":210},"number_combination","数字组合","數字組合","Number Combination",29,{"code":212,"nameZhCn":213,"nameZhTw":214,"nameEnUs":215,"sortOrder":216},"recent_chain","近链推演","近鏈推演","Recent Chain",30]