[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"reports-detail-2026-09-22-hot-cold-span-en-US":3,"reports-algorithms":41},{"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},"2026-09-22-hot-cold-span","daily",null,"2026-09-23 00:30:00","2026-09-23 00:30:20","\u002Fstatic\u002Fog\u002F2026-09-22-hot-cold-span.jpg",0,"Hot and Cold Numbers Appear Together with Concentrated Span Trends","Canada 28 Analysis: Hot and Cold Numbers with Concentrated Span Trends","Detailed analysis of Canada 28's recent results: significant hot and cold number activity and span concentration in the 4-6 range. Full insights inside.","Yesterday's Canada 28 results highlighted notable hot and cold number activity, with cold numbers absent for over 200 draws and spans concentrated in the 4-6 range.","## Notable Hot and Cold Number Activity\n\nYesterday's Canada 28 results showcased intriguing patterns in hot and cold numbers. Among the hot numbers, the sum value of 10 appeared 35 times, accounting for 8.71% of the total. Following closely were sums of 17 and 12, appearing 33 and 32 times respectively, representing 8.21% and 7.96% of the draws.\n\nOn the cold number side, numbers like 0, 1, and 24 have been absent for 230 consecutive draws, sparking interest in their potential reappearance. Additionally, cold number 4 recently ended its 53-draw absence by appearing in draw number 3485160.\n\n## Concentrated Span Distribution\n\nSpan data revealed a strong concentration in the 4-6 range, with spans of 4, 5, and 6 appearing 72, 71, and 51 times respectively, corresponding to 17.91%, 17.66%, and 12.69% of the draws. Extremely low spans (such as 0 or 1) and high spans (like 9) were rare, recorded only 2 and 27 times respectively, indicating relative stability in distribution.\n\n## AI Algorithm Performance\n\nIn yesterday's AI algorithm tests, the \"anti-Martingale method\" stood out among five tested algorithms, achieving an overall accuracy of 47.82%. The highest accuracy was observed in big\u002Fsmall predictions at 53.98%. In contrast, the \"Bayesian method\" lagged with a total accuracy of 36.63%, highlighting differences in algorithm suitability.\n\n## Rare Event Highlight\n\nA noteworthy occurrence was the appearance of the triple number \"555,\" a rare event in recent draws. While such instances are not predictive, they provide interesting data points for analysis.\n\nIn summary, the significant activity in hot and cold numbers, along with the concentrated span trends, offers valuable insights for future predictions. Continuous improvements in AI algorithms will further enhance forecasting models.",6,[18,27,35],{"slug":19,"type":20,"extremeSubtype":21,"publishAt":22,"coverImage":23,"viewCount":10,"title":24,"summary":25,"readMinutes":26},"2026-10-11-extreme-sum-zero-v2","extreme","E2","2026-10-11 11:56:58","\u002Fstatic\u002Fog\u002F2026-10-11-extreme-sum-zero-v2.jpg","Canada 28 Draw #3492654 Hits a Total Sum of 0","Canada 28 draw #3492654 recorded an extremely rare total sum of 0, with a probability of just 0.1%. The last similar result occurred in draw #3492637.",2,{"slug":28,"type":20,"extremeSubtype":29,"publishAt":30,"coverImage":31,"viewCount":10,"title":32,"summary":33,"readMinutes":34},"2026-10-11-extreme-triple-zero","E1","2026-10-11 11:56:49","\u002Fstatic\u002Fog\u002F2026-10-11-extreme-triple-zero.jpg","Canada 28 Triple Number 000 Reappears, Rare 1% Probability","Canada 28's draw #3492654 featured the rare triple number 000, with a theoretical probability of just 1%. This marks the second occurrence within an hour.",3,{"slug":36,"type":20,"extremeSubtype":21,"publishAt":37,"coverImage":38,"viewCount":10,"title":39,"summary":40,"readMinutes":26},"2026-10-11-extreme-sum-zero","2026-10-11 10:46:56","\u002Fstatic\u002Fog\u002F2026-10-11-extreme-sum-zero.jpg","Canada 28 Hits Rare Sum 0 Again","On October 11, JND28 draw #3492634 recorded an extremely rare sum of 0, with a theoretical probability of only 0.1%, marking the second occurrence in just two days.",[42,48,53,58,64,70,75,81,87,93,99,105,111,117,123,129,135,141,146,152,158,164,170,176,182,188,194,200,206,212],{"code":43,"nameZhCn":44,"nameZhTw":45,"nameEnUs":46,"sortOrder":47},"quantum_probability","量子概率引擎","量子機率引擎","Quantum Probability Engine",1,{"code":49,"nameZhCn":50,"nameZhTw":51,"nameEnUs":52,"sortOrder":26},"deep_neural_network","深度神经网络","深度神經網路","Deep Neural Network",{"code":54,"nameZhCn":55,"nameZhTw":56,"nameEnUs":57,"sortOrder":34},"genetic_evolution","遗传进化算法","遺傳進化演算法","Genetic Evolution Algorithm",{"code":59,"nameZhCn":60,"nameZhTw":61,"nameEnUs":62,"sortOrder":63},"markov_chain","马尔可夫链","馬可夫鏈","Markov Chain",4,{"code":65,"nameZhCn":66,"nameZhTw":67,"nameEnUs":68,"sortOrder":69},"deep_learning","深度学习","深度學習","Deep Learning",5,{"code":71,"nameZhCn":72,"nameZhTw":73,"nameEnUs":74,"sortOrder":16},"bayesian","贝叶斯推理","貝氏推論","Bayesian Inference",{"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":86},"lstm","LSTM 长短期记忆","LSTM 長短期記憶","LSTM Network",8,{"code":88,"nameZhCn":89,"nameZhTw":90,"nameEnUs":91,"sortOrder":92},"monte_carlo","蒙特卡洛模拟","蒙地卡羅模擬","Monte Carlo Simulation",9,{"code":94,"nameZhCn":95,"nameZhTw":96,"nameEnUs":97,"sortOrder":98},"clustering","聚类追踪","聚類追蹤","Cluster Tracking",10,{"code":100,"nameZhCn":101,"nameZhTw":102,"nameEnUs":103,"sortOrder":104},"volatility","波动率","波動率","Volatility",11,{"code":106,"nameZhCn":107,"nameZhTw":108,"nameEnUs":109,"sortOrder":110},"edge_value","边缘值","邊緣值","Edge Value",12,{"code":112,"nameZhCn":113,"nameZhTw":114,"nameEnUs":115,"sortOrder":116},"anti_martingale","反马丁格尔","反馬丁格爾","Anti-Martingale",13,{"code":118,"nameZhCn":119,"nameZhTw":120,"nameEnUs":121,"sortOrder":122},"ensemble_voting","综合投票","綜合投票","Ensemble Voting",14,{"code":124,"nameZhCn":125,"nameZhTw":126,"nameEnUs":127,"sortOrder":128},"momentum","动量加速度","動量加速度","Momentum",15,{"code":130,"nameZhCn":131,"nameZhTw":132,"nameEnUs":133,"sortOrder":134},"quantile","分位数","分位數","Quantile",16,{"code":136,"nameZhCn":137,"nameZhTw":138,"nameEnUs":139,"sortOrder":140},"double_step_transition","双步转移","雙步轉移","Double-Step Transition",17,{"code":142,"nameZhCn":143,"nameZhTw":143,"nameEnUs":144,"sortOrder":145},"local_entropy","局部熵","Local Entropy",18,{"code":147,"nameZhCn":148,"nameZhTw":149,"nameEnUs":150,"sortOrder":151},"residual_trend","残差趋势","殘差趨勢","Residual Trend",19,{"code":153,"nameZhCn":154,"nameZhTw":155,"nameEnUs":156,"sortOrder":157},"streak_length","连势长度","連勢長度","Streak Length",20,{"code":159,"nameZhCn":160,"nameZhTw":161,"nameEnUs":162,"sortOrder":163},"decay_missing","衰减遗漏","衰減遺漏","Decay Missing",21,{"code":165,"nameZhCn":166,"nameZhTw":167,"nameEnUs":168,"sortOrder":169},"rule_voting","规则投票","規則投票","Rule Voting",22,{"code":171,"nameZhCn":172,"nameZhTw":173,"nameEnUs":174,"sortOrder":175},"cold_hot_balance","冷热平衡","冷熱平衡","Cold-Hot Balance",23,{"code":177,"nameZhCn":178,"nameZhTw":179,"nameEnUs":180,"sortOrder":181},"kelly","凯利公式","凱利公式","Kelly Criterion",24,{"code":183,"nameZhCn":184,"nameZhTw":185,"nameEnUs":186,"sortOrder":187},"mean_reversion","均值回归","均值回歸","Mean Reversion",25,{"code":189,"nameZhCn":190,"nameZhTw":191,"nameEnUs":192,"sortOrder":193},"autocorrelation","自相关","自相關","Autocorrelation",26,{"code":195,"nameZhCn":196,"nameZhTw":197,"nameEnUs":198,"sortOrder":199},"fibonacci","斐波那契","費波那契","Fibonacci",27,{"code":201,"nameZhCn":202,"nameZhTw":203,"nameEnUs":204,"sortOrder":205},"miss_chase","遗漏追热","遺漏追熱","Miss Chase",28,{"code":207,"nameZhCn":208,"nameZhTw":209,"nameEnUs":210,"sortOrder":211},"number_combination","数字组合","數字組合","Number Combination",29,{"code":213,"nameZhCn":214,"nameZhTw":215,"nameEnUs":216,"sortOrder":217},"recent_chain","近链推演","近鏈推演","Recent Chain",30]