\n| Gracz<\/span><\/td>\n | Ilość żetonów<\/span><\/td>\n | Prawdopodobieństwo zajęcia 1\/2\/3\/4\/5 miejsca
<\/span><\/td>\n | Wartość stacków
<\/span><\/td>\n<\/tr>\n\n1<\/strong><\/td>\n| 1000<\/td>\n | 7,42% \/ 9,33% \/ 12,94% \/ 22,05% \/ 48,4%<\/td>\n | 8,17 $<\/td>\n<\/tr>\n | \n2<\/strong><\/td>\n| 3500<\/td>\n | 25,92% \/ 25,73% \/ 23,74% \/ 17,25% \/ 7,5%<\/td>\n | 22,87 $<\/td>\n<\/tr>\n | \n3<\/strong><\/td>\n| 3000<\/td>\n | 22,22% \/ 23,43% \/ 24,34% \/ 20,05% \/ 10%<\/td>\n | 20,70 $<\/td>\n<\/tr>\n | \n4<\/strong><\/td>\n| 1500<\/td>\n | 11,12% \/ 13,53% \/ 17,74% \/ 27,95% \/ 29,7%<\/td>\n | 11,84 $<\/td>\n<\/tr>\n | \n5<\/strong><\/td>\n| 4500<\/td>\n | 33,32% \/ 28,03% \/ 21,44% \/ 12,85% \/ 4,4%<\/td>\n | 26,42 $<\/td>\n<\/tr>\n<\/tbody>\n<\/table> <\/p> W następnych lekcjach dowiesz się, w których sytuacjach oszacowywanie pieniężnej wartości stacków jest szczególnie ważne i w jaki sposób powinieneś wykorzystywać tę umiejętność.<\/p> Założenia i ograniczenia<\/h2>ICM bazuje na pewnych założeniach. Aby uprościć procedurę i w ogóle umożliwić rozwiązanie tych skomplikowanych równań zakłada się, że:<\/p> \n- Wszyscy gracze mają taki sam poziom umiejętności.<\/li>\n
- Pozycja graczy nie ma znaczenia.<\/li>\n
- Image graczy nie ma znaczenia.<\/li>\n
- Blindy nie mają znaczenia.<\/li>\n<\/ul>
Założenia te umożliwiają proces obliczeń, jak również wskazują na pewne ograniczenia ICM. Ponieważ wymienione zmienne - nie uwzględniane przez ICM - są wyjątkowo ważne w trakcie podejmowania decyzji przy stole, będą tematem oddzielnych lekcji, w których nauczysz się poprawnie dopasowywać swoją grę. Ze względu na powyższe założenia model ICM nie zawsze bywa precyzyjny, w dalszym ciągu jednak dostarcza cennych i użytecznych wyników.<\/p> Istnieje wiele różnych wersji algorytmu ICM, najbardziej popularna z nich to model Malmuth-Harville.<\/em> W tej lekcji do obliczeń został wykorzystany właśnie ten model. W bardziej zaawansowanych lekcjach na temat ICM zapoznasz się również z innymi algorytmami ICM i dowiesz się, co je łączy oraz czym się między sobą różnią.<\/p>Podsumowanie<\/h2>W tej lekcji zapoznałeś się z podstawami Independent Chip Model.<\/p> \n- Independent Chip Model (ICM)<\/strong> to model, który służy do przydzielania turniejowym stackom ich pieniężnej wartości.<\/li>\n
- ICM przydziela stackom ich pieniężną wartość<\/strong>, wyliczając dla każdego gracza prawdopodobieństwo ukończenia turnieju na danym miejscu i obliczając w ten sposób equity względem puli nagród.<\/li>\n
- ICM bazuje na pewnych założeniach<\/strong> i dlatego ma też ograniczenia.<\/li>\n<\/ul>\n","protected":false},"excerpt":{"rendered":"
Chip Value (2): Podstawy Independent Chip Model (ICM) Zanim przejdziesz do tej lekcji, powinieneś przeczytać następujący artykuł: Chip Value (1): […]<\/p>\n","protected":false},"author":1,"featured_media":0,"template":"","meta":{"_acf_changed":false,"inline_featured_image":false,"_lmt_disableupdate":"","_lmt_disable":""},"strategy_category":[101],"strategy_level":[17],"class_list":["post-43232","strategy","type-strategy","status-publish","hentry","strategy_category-sit-and-go-chip-value"],"acf":[],"yoast_head":"\n Chip Value (2): Podstawy Independent Chip Model (ICM) - PokerStrategy PL<\/title>\n<meta name=\"description\" content=\"Ucz si\u0119 pokera na PokerStrategy.com - najwi\u0119kszej szkole pokera na \u015bwiecie. 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