SennaMatchupy
Dane matchupów Senna dla League of Legends patch 26.10. Win rate, statystyki wydajności i najlepsze buildy dla każdego matchupu Senna. Dowiedz się kogo Senna pokonuje i komu przegrywa na linii.
Senna Matchup Breakdown
Use the dropdown to select an opponent and see a detailed breakdown of how Senna performs against them. You'll get head-to-head win rates, laning stats, the best build and runes for the matchup, and early vs late game analysis — all based on real ranked data.
Dane matchupow Senna dla patcha 26.10 League of Legends. Ponizszatabela pokazuje wskaznik wygranych Senna, roznice w zlocie i statystyki wydajnosci przeciwko kazdemu czempionowi w aktualnej mecie. Kliknij nazwe czempiona, aby zobaczyc szczegolowy rozklad, w tym najlepszy build Senna, runy, statystyki liniowe i analize wczesnej vs poznej gry dla tego konkretnego matchupu.
Przeciwnik | Winrate | Mecze | CS/min | OBR/min | Zloto/mecz | Wczesne WR | Pozne WR |
|---|---|---|---|---|---|---|---|
| 49.38% | 649 | 1.8 | 582 | 10,075 | 44.6% | 53.0% | |
| 52.65% | 547 | 1.6 | 633 | 10,065 | 53.3% | 52.0% | |
| 49.90% | 521 | 6.2 | 914 | 13,499 | 48.6% | 50.8% | |
| 53.37% | 489 | 1.8 | 553 | 10,445 | 43.6% | 59.9% | |
| 53.83% | 470 | 1.5 | 607 | 10,147 | 50.2% | 57.0% | |
| 50.35% | 433 | 5.3 | 732 | 11,899 | 51.1% | 49.8% | |
| 51.35% | 407 | 1.5 | 585 | 10,250 | 50.0% | 52.5% | |
| 52.48% | 383 | 6.0 | 765 | 12,796 | 55.9% | 50.0% | |
| 50.82% | 366 | 2.4 | 644 | 11,378 | 51.1% | 50.7% | |
| 48.45% | 322 | 1.6 | 620 | 10,343 | 46.4% | 50.0% | |
| 49.64% | 280 | 1.7 | 640 | 10,759 | 47.8% | 50.9% | |
| 48.16% | 272 | 1.6 | 600 | 10,303 | 45.4% | 50.3% | |
| 47.58% | 269 | 1.5 | 613 | 9,715 | 45.0% | 50.0% | |
| 49.43% | 264 | 1.5 | 594 | 9,872 | 57.7% | 41.4% | |
| 46.15% | 247 | 1.5 | 631 | 9,578 | 48.1% | 44.0% | |
| 52.32% | 237 | 5.9 | 779 | 12,986 | 56.7% | 49.7% | |
| 45.53% | 235 | 6.1 | 815 | 13,079 | 44.3% | 46.5% | |
| 55.36% | 233 | 5.8 | 834 | 13,190 | 50.0% | 59.3% | |
| 54.39% | 228 | 1.5 | 579 | 10,143 | 52.6% | 55.7% | |
| 54.79% | 219 | 1.6 | 621 | 10,410 | 54.1% | 55.4% | |
| 49.76% | 211 | 2.2 | 687 | 11,098 | 59.4% | 45.1% | |
| 54.33% | 208 | 5.4 | 800 | 12,619 | 54.3% | 54.4% | |
| 53.40% | 206 | 1.5 | 530 | 10,044 | 59.3% | 48.7% | |
| 47.72% | 197 | 1.8 | 581 | 11,073 | 51.4% | 45.7% | |
| 59.16% | 191 | 1.7 | 624 | 10,983 | 52.9% | 62.6% | |
| 60.32% | 189 | 1.5 | 642 | 10,260 | 60.6% | 60.0% | |
| 53.23% | 186 | 1.7 | 766 | 9,787 | 58.1% | 48.4% | |
| 55.91% | 186 | 1.5 | 689 | 10,308 | 51.6% | 60.2% | |
| 56.83% | 183 | 1.5 | 587 | 9,980 | 61.1% | 52.7% | |
| 52.22% | 180 | 2.0 | 582 | 10,571 | 42.0% | 58.6% | |
| 57.54% | 179 | 1.6 | 622 | 10,216 | 62.8% | 53.5% | |
| 55.07% | 138 | 6.0 | 824 | 13,084 | 51.5% | 58.6% | |
| 55.22% | 134 | 2.4 | 659 | 10,942 | 51.9% | 57.3% | |
| 51.97% | 127 | 5.9 | 846 | 12,992 | 67.2% | 39.1% | |
| 45.76% | 118 | 1.5 | 710 | 10,928 | 54.8% | 40.8% | |
| 53.10% | 113 | 1.5 | 616 | 10,045 | 62.5% | 43.9% | |
| 48.11% | 106 | 1.5 | 561 | 9,698 | 54.7% | 41.5% | |
| 52.00% | 100 | 6.1 | 827 | 12,713 | 57.1% | 48.3% | |
| 44.21% | 95 | 5.8 | 839 | 13,371 | 55.0% | 36.4% | |
| 53.19% | 94 | 5.2 | 602 | 11,609 | 58.1% | 49.0% | |
| 55.32% | 94 | 1.5 | 648 | 10,560 | 56.8% | 54.4% | |
| 49.46% | 93 | 1.7 | 680 | 10,598 | 63.6% | 36.7% | |
| 50.55% | 91 | 6.4 | 834 | 13,031 | 52.4% | 49.0% | |
| 56.04% | 91 | 1.8 | 614 | 10,805 | 45.7% | 62.5% | |
| 59.55% | 89 | 1.6 | 694 | 10,795 | 55.3% | 62.8% | |
| 43.42% | 76 | 2.4 | 626 | 10,850 | 37.0% | 46.9% | |
| 43.42% | 76 | 5.7 | 658 | 11,444 | 39.5% | 47.4% | |
| 44.00% | 75 | 5.8 | 787 | 11,280 | 43.2% | 45.2% | |
| 41.89% | 74 | 1.7 | 607 | 10,659 | 39.3% | 43.5% | |
| 45.45% | 66 | 5.7 | 740 | 12,249 | 39.3% | 50.0% | |
| 57.58% | 66 | 6.4 | 856 | 12,986 | 54.8% | 60.0% | |
| 62.90% | 62 | 1.8 | 682 | 11,552 | 69.6% | 59.0% | |
| 50.00% | 62 | 6.3 | 853 | 13,100 | 37.9% | 60.6% | |
| 59.65% | 57 | 3.4 | 702 | 11,503 | 52.4% | 63.9% | |
| 56.14% | 57 | 1.4 | 608 | 9,655 | 64.3% | 48.3% | |
| 55.36% | 56 | 5.9 | 830 | 13,364 | 47.6% | 60.0% | |
| 44.44% | 54 | 6.3 | 793 | 11,963 | 46.4% | 42.3% | |
| 54.72% | 53 | 1.4 | 715 | 10,154 | 62.5% | 48.3% | |
| 52.00% | 50 | 2.2 | 670 | 10,657 | 47.4% | 54.8% | |
| 46.81% | 47 | 2.3 | 687 | 10,492 | 52.6% | 42.9% | |
| 39.13% | 46 | 2.4 | 697 | 11,249 | 35.3% | 41.4% | |
| 54.55% | 44 | 5.2 | 773 | 13,453 | 57.1% | 53.3% | |
| 48.84% | 43 | 5.2 | 711 | 12,328 | 27.8% | 64.0% | |
| 50.00% | 40 | 5.9 | 794 | 12,839 | 33.3% | 60.0% | |
| 42.50% | 40 | 6.2 | 892 | 13,248 | 44.4% | 40.9% | |
| 54.29% | 35 | 2.7 | 739 | 11,301 | 46.1% | 59.1% | |
| 32.35% | 34 | 2.8 | 633 | 11,327 | 33.3% | 31.8% | |
| 56.67% | 30 | 2.1 | 601 | 10,615 | 50.0% | 61.1% | |
| 56.67% | 30 | 4.9 | 726 | 11,767 | 68.8% | 42.9% | |
| 36.67% | 30 | 5.9 | 827 | 11,479 | 27.8% | 50.0% | |
| 61.54% | 26 | 1.7 | 653 | 10,231 | 38.5% | 84.6% | |
| 37.50% | 24 | 1.8 | 629 | 10,015 | 45.5% | 30.8% | |
| 60.87% | 23 | 1.8 | 585 | 10,955 | 50.0% | 69.2% | |
| 50.00% | 22 | 3.1 | 829 | 11,055 | 25.0% | 64.3% | |
| 45.45% | 22 | 2.0 | 586 | 9,968 | 45.5% | 45.5% | |
| 45.45% | 22 | 1.5 | 578 | 9,480 | 60.0% | 33.3% | |
| 47.62% | 21 | 1.8 | 549 | 10,309 | 44.4% | 50.0% | |
| 47.62% | 21 | 5.7 | 902 | 12,310 | 40.0% | 54.5% | |
| 52.63% | 19 | 2.1 | 656 | 12,071 | 57.1% | 50.0% | |
| 52.63% | 19 | 2.9 | 621 | 11,704 | 80.0% | 42.9% | |
| 52.94% | 17 | 5.4 | 760 | 10,327 | 58.3% | 40.0% | |
| 47.06% | 17 | 2.7 | 780 | 12,569 | 100.0% | 40.0% | |
| 60.00% | 15 | 4.4 | 662 | 11,308 | 66.7% | 55.6% | |
| 60.00% | 15 | 3.3 | 943 | 14,365 | 50.0% | 63.6% | |
| 26.67% | 15 | 5.3 | 678 | 12,923 | 28.6% | 25.0% | |
| 66.67% | 15 | 4.2 | 743 | 11,354 | 66.7% | 66.7% | |
| 26.67% | 15 | 1.6 | 563 | 9,818 | 33.3% | 22.2% | |
| 50.00% | 14 | 5.7 | 811 | 10,559 | 40.0% | 55.6% | |
| 46.15% | 13 | 2.5 | 837 | 9,804 | 57.1% | 33.3% | |
| 46.15% | 13 | 2.4 | 824 | 12,315 | 40.0% | 50.0% | |
| 53.85% | 13 | 1.2 | 668 | 9,569 | 42.9% | 66.7% | |
| 30.77% | 13 | 5.1 | 921 | 10,544 | 33.3% | 28.6% | |
| 41.67% | 12 | 1.6 | 566 | 8,802 | 50.0% | 25.0% | |
| 27.27% | 11 | 4.4 | 697 | 10,212 | 0.0% | 33.3% | |
| 54.55% | 11 | 4.3 | 676 | 8,934 | 57.1% | 50.0% | |
| 18.18% | 11 | 3.6 | 520 | 7,413 | 16.7% | 20.0% | |
| 63.64% | 11 | 1.6 | 737 | 10,968 | 75.0% | 57.1% | |
| 54.55% | 11 | 4.8 | 861 | 12,049 | 100.0% | 37.5% | |
| 50.00% | 10 | 4.9 | 718 | 13,326 | 66.7% | 42.9% | |
| 40.00% | 10 | 5.0 | 733 | 9,121 | 57.1% | 0.0% | |
| 80.00% | 10 | 1.1 | 660 | 9,701 | 83.3% | 75.0% | |
| 80.00% | 10 | 2.1 | 714 | 9,313 | 80.0% | 80.0% | |
| 50.00% | 10 | 2.1 | 714 | 13,204 | 0.0% | 50.0% | |
| 55.56% | 9 | 4.3 | 1,032 | 15,519 | 0.0% | 62.5% | |
| 44.44% | 9 | 4.9 | 710 | 11,822 | 0.0% | 57.1% | |
| 44.44% | 9 | 3.1 | 604 | 10,335 | 50.0% | 40.0% | |
| 55.56% | 9 | 3.8 | 911 | 12,113 | 75.0% | 40.0% | |
| 62.50% | 8 | 3.3 | 770 | 11,719 | 60.0% | 66.7% | |
| 50.00% | 8 | 2.9 | 610 | 12,225 | 50.0% | 50.0% | |
| 25.00% | 8 | 5.2 | 545 | 5,931 | 16.7% | 50.0% | |
| 62.50% | 8 | 3.6 | 836 | 12,624 | 66.7% | 60.0% | |
| 25.00% | 8 | 4.1 | 629 | 10,858 | 66.7% | 0.0% | |
| 62.50% | 8 | 4.7 | 783 | 12,337 | 33.3% | 80.0% | |
| 57.14% | 7 | 4.2 | 854 | 12,373 | 0.0% | 66.7% | |
| 71.43% | 7 | 2.3 | 803 | 12,458 | 50.0% | 80.0% | |
| 28.57% | 7 | 4.6 | 647 | 10,265 | 33.3% | 25.0% | |
| 33.33% | 6 | 4.8 | 722 | 11,022 | 50.0% | 25.0% | |
| 50.00% | 6 | 5.1 | 820 | 10,232 | 33.3% | 66.7% | |
| 66.67% | 6 | 4.3 | 923 | 12,183 | 100.0% | 33.3% | |
| 66.67% | 6 | 2.2 | 573 | 9,793 | 60.0% | 100.0% | |
| 60.00% | 5 | 3.7 | 830 | 13,253 | 100.0% | 50.0% | |
| 80.00% | 5 | 1.6 | 669 | 12,540 | 100.0% | 66.7% | |
| 25.00% | 5 | 3.4 | 897 | 13,619 | 0.0% | 33.3% | |
| 60.00% | 5 | 1.9 | 650 | 11,233 | 0.0% | 100.0% | |
| 100.00% | 5 | 2.8 | 748 | 10,032 | 100.0% | 100.0% | |
| 60.00% | 5 | 1.3 | 577 | 9,788 | 60.0% | 0.0% | |
| 60.00% | 5 | 4.7 | 628 | 11,445 | 0.0% | 75.0% | |
| 20.00% | 5 | 3.6 | 674 | 10,822 | 33.3% | 0.0% | |
| 20.00% | 5 | 6.5 | 1,081 | 8,434 | 0.0% | 50.0% | |
| 20.00% | 5 | 1.4 | 517 | 7,984 | 33.3% | 0.0% | |
| 20.00% | 5 | 1.7 | 424 | 8,396 | 33.3% | 0.0% | |
| 40.00% | 5 | 2.4 | 484 | 9,113 | 33.3% | 50.0% | |
| 60.00% | 5 | 4.0 | 668 | 10,804 | 66.7% | 50.0% | |
Pomóż nam utrzymać dokładność! Jeśli zauważysz nieprawidłowe statystyki, brakujące dane lub jakiekolwiek problemy, Twoja opinia bezpośrednio poprawia jakość naszych danych dla całej społeczności.
Matchupy Senna - Czesto zadawane pytania
Jakie sa najlepsze matchupy Senna w League of Legends?
Najlepsze matchupy Senna w patchu 26.10 to Seraphine, Nami, and Smolder. Senna ma najwyzsze wskazniki zwyciestwa przeciwko tym czempionom i moze dominowac na linii, gdy sie z nimi mierzy. Wybierz dowolnego przeciwnika z tabeli matchupow, aby zobaczyc szczegolowe statystyki.
Jakie sa najgorsze matchupy Senna?
Najgorsze matchupy Senna to Xin Zhao, Ekko, and Nasus. Ci czempioni maja korzystne wskazniki zwyciestwa przeciwko Senna i moga wykorzystac slabosci Senna na linii. Kliknij nazwe czempiona w tabeli, aby zobaczyc pelny rozklad matchupu.
Jak sprawdzic dane matchupow Senna?
Mozesz sprawdzic dane matchupow Senna wlasnie tutaj na tej stronie. Tabela matchupow pokazuje wskazniki zwyciestwa i statystyki przeciwko kazdemu czempionowi. Kliknij dowolna nazwe czempiona, aby zobaczyc szczegolowy rozklad, w tym najlepszy build, runy, statystyki linii i analize early vs late game dla tego konkretnego matchupu Senna.
Kogo kontruje Senna w League of Legends?
Senna kontruje Seraphine, Nami, and Smolder w patchu 26.10. To sa najbardziej korzystne matchupy Senna, gdzie Senna ma najwyzsze wskazniki zwyciestwa i najsilniejsza wydajnosc na linii. Uzyj selektora matchupow powyzej, aby zbadac dowolny konkretny matchup Senna w szczegolach.
Kto kontruje Senna na linii?
Xin Zhao, Ekko, and Nasus kontruja Senna na linii w patchu 26.10. Ci czempioni maja najlepsze wskazniki zwyciestwa przeciwko Senna. Sprawdz zakladke kontr lub kliknij czempiona w tabeli, aby zobaczyc szczegolowe strategie matchupow i polecane buildy.