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 |
|---|---|---|---|---|---|---|---|
| 49.00% | 649 | 1.7 | 573 | 10,069 | 42.1% | 54.2% | |
| 49.43% | 528 | 6.2 | 903 | 13,451 | 47.2% | 50.8% | |
| 54.27% | 527 | 1.6 | 636 | 10,083 | 54.9% | 53.7% | |
| 50.52% | 479 | 1.8 | 542 | 10,282 | 41.8% | 56.5% | |
| 51.52% | 460 | 1.5 | 608 | 10,072 | 47.6% | 54.8% | |
| 50.70% | 426 | 5.3 | 714 | 11,673 | 49.5% | 51.7% | |
| 50.74% | 408 | 1.5 | 576 | 10,134 | 49.5% | 51.8% | |
| 50.93% | 375 | 5.9 | 752 | 12,686 | 52.2% | 50.0% | |
| 49.86% | 363 | 2.3 | 640 | 11,205 | 52.6% | 48.3% | |
| 49.17% | 301 | 1.6 | 613 | 9,976 | 46.0% | 51.9% | |
| 51.54% | 293 | 1.7 | 656 | 11,080 | 53.0% | 50.6% | |
| 46.21% | 264 | 1.5 | 621 | 9,786 | 44.5% | 47.8% | |
| 45.83% | 264 | 1.5 | 590 | 9,927 | 52.0% | 40.4% | |
| 46.90% | 258 | 1.6 | 597 | 10,682 | 47.0% | 46.8% | |
| 50.40% | 250 | 1.5 | 643 | 9,759 | 48.8% | 52.1% | |
| 51.05% | 239 | 1.5 | 576 | 9,917 | 50.5% | 51.5% | |
| 44.54% | 238 | 6.1 | 816 | 13,010 | 48.2% | 41.3% | |
| 51.69% | 236 | 5.3 | 773 | 12,422 | 53.6% | 50.0% | |
| 49.78% | 229 | 6.0 | 766 | 12,656 | 52.1% | 48.1% | |
| 54.39% | 228 | 5.8 | 806 | 12,885 | 46.8% | 59.7% | |
| 48.85% | 217 | 1.9 | 565 | 10,898 | 46.5% | 50.4% | |
| 55.56% | 216 | 1.6 | 617 | 10,193 | 57.7% | 53.6% | |
| 50.00% | 214 | 2.1 | 680 | 10,923 | 60.5% | 44.2% | |
| 53.52% | 213 | 1.6 | 536 | 10,015 | 58.6% | 49.1% | |
| 52.13% | 188 | 1.7 | 622 | 10,191 | 56.5% | 48.5% | |
| 56.91% | 188 | 1.5 | 673 | 10,283 | 52.2% | 61.5% | |
| 61.08% | 185 | 1.7 | 613 | 10,771 | 54.4% | 65.0% | |
| 50.28% | 181 | 1.8 | 781 | 9,848 | 55.0% | 45.6% | |
| 53.33% | 180 | 1.5 | 577 | 9,684 | 51.1% | 55.8% | |
| 55.37% | 177 | 1.5 | 650 | 10,268 | 59.3% | 51.6% | |
| 52.02% | 173 | 1.8 | 591 | 10,372 | 41.2% | 59.0% | |
| 51.77% | 141 | 6.0 | 828 | 13,063 | 49.3% | 54.3% | |
| 49.62% | 131 | 6.0 | 826 | 13,414 | 58.2% | 43.4% | |
| 55.73% | 131 | 2.5 | 645 | 11,090 | 57.1% | 54.9% | |
| 49.12% | 114 | 1.5 | 716 | 10,662 | 54.2% | 45.5% | |
| 56.76% | 111 | 1.4 | 580 | 9,719 | 63.6% | 50.0% | |
| 50.91% | 110 | 1.6 | 656 | 10,324 | 57.4% | 44.6% | |
| 54.46% | 101 | 6.1 | 840 | 12,523 | 54.5% | 54.4% | |
| 48.45% | 97 | 1.6 | 676 | 10,286 | 60.8% | 34.8% | |
| 56.25% | 96 | 6.3 | 818 | 12,917 | 61.4% | 51.9% | |
| 57.45% | 94 | 1.5 | 640 | 10,309 | 62.5% | 53.7% | |
| 47.25% | 91 | 6.0 | 808 | 13,295 | 52.6% | 43.4% | |
| 63.64% | 88 | 1.6 | 701 | 10,828 | 58.5% | 68.1% | |
| 47.13% | 87 | 5.1 | 613 | 11,494 | 52.5% | 42.5% | |
| 53.57% | 84 | 1.8 | 597 | 10,845 | 40.0% | 63.3% | |
| 46.84% | 79 | 5.7 | 648 | 11,232 | 42.5% | 51.3% | |
| 47.44% | 78 | 5.7 | 802 | 11,369 | 48.8% | 45.7% | |
| 46.75% | 77 | 2.4 | 607 | 10,367 | 43.8% | 48.9% | |
| 37.84% | 74 | 1.8 | 620 | 10,995 | 29.6% | 42.5% | |
| 54.41% | 68 | 6.4 | 826 | 12,636 | 48.5% | 60.0% | |
| 46.03% | 63 | 6.4 | 815 | 12,817 | 41.4% | 50.0% | |
| 65.00% | 60 | 1.6 | 689 | 11,287 | 73.9% | 59.5% | |
| 47.46% | 59 | 6.5 | 831 | 11,801 | 47.2% | 47.8% | |
| 61.82% | 55 | 3.2 | 673 | 11,350 | 50.0% | 68.6% | |
| 49.09% | 55 | 5.5 | 750 | 12,203 | 41.7% | 54.8% | |
| 51.92% | 52 | 1.5 | 629 | 10,194 | 60.0% | 44.4% | |
| 52.00% | 50 | 5.9 | 863 | 13,887 | 30.8% | 59.5% | |
| 50.00% | 50 | 2.3 | 679 | 10,614 | 57.1% | 44.8% | |
| 53.19% | 47 | 1.4 | 696 | 9,994 | 70.0% | 40.7% | |
| 47.83% | 46 | 4.9 | 695 | 12,172 | 29.4% | 58.6% | |
| 57.78% | 45 | 2.3 | 621 | 10,406 | 61.1% | 55.6% | |
| 40.91% | 44 | 2.5 | 676 | 11,271 | 40.0% | 41.4% | |
| 41.03% | 39 | 5.6 | 783 | 12,962 | 14.3% | 56.0% | |
| 43.59% | 39 | 6.1 | 893 | 13,546 | 50.0% | 38.1% | |
| 39.47% | 38 | 5.4 | 755 | 12,613 | 41.2% | 38.1% | |
| 45.45% | 33 | 2.5 | 640 | 11,710 | 54.5% | 40.9% | |
| 56.25% | 32 | 2.2 | 582 | 10,686 | 58.3% | 55.0% | |
| 58.06% | 31 | 5.4 | 775 | 12,135 | 70.6% | 42.9% | |
| 61.29% | 31 | 2.8 | 765 | 12,150 | 50.0% | 66.7% | |
| 28.57% | 28 | 6.1 | 795 | 11,013 | 22.2% | 40.0% | |
| 48.00% | 25 | 1.9 | 628 | 10,646 | 45.5% | 50.0% | |
| 54.17% | 24 | 2.5 | 838 | 10,837 | 30.0% | 71.4% | |
| 58.33% | 24 | 1.7 | 666 | 9,665 | 23.1% | 100.0% | |
| 50.00% | 24 | 1.6 | 601 | 10,207 | 50.0% | 50.0% | |
| 40.00% | 20 | 2.0 | 646 | 10,902 | 50.0% | 33.3% | |
| 65.00% | 20 | 1.9 | 594 | 10,267 | 60.0% | 70.0% | |
| 57.89% | 19 | 3.3 | 932 | 13,838 | 57.1% | 58.3% | |
| 47.37% | 19 | 1.8 | 535 | 10,267 | 50.0% | 45.5% | |
| 52.63% | 19 | 6.0 | 920 | 12,734 | 42.9% | 58.3% | |
| 61.11% | 18 | 4.4 | 659 | 10,835 | 62.5% | 60.0% | |
| 50.00% | 18 | 3.0 | 744 | 12,169 | 100.0% | 35.7% | |
| 64.71% | 17 | 5.2 | 768 | 10,501 | 63.6% | 66.7% | |
| 50.00% | 16 | 2.3 | 676 | 12,122 | 66.7% | 40.0% | |
| 46.67% | 15 | 2.6 | 742 | 9,423 | 42.9% | 50.0% | |
| 73.33% | 15 | 1.5 | 703 | 9,488 | 62.5% | 85.7% | |
| 53.33% | 15 | 2.9 | 611 | 11,990 | 66.7% | 50.0% | |
| 50.00% | 14 | 5.8 | 827 | 10,711 | 50.0% | 50.0% | |
| 57.14% | 14 | 3.8 | 686 | 10,740 | 50.0% | 62.5% | |
| 42.86% | 14 | 6.2 | 684 | 14,504 | 20.0% | 55.6% | |
| 42.86% | 14 | 2.1 | 713 | 12,074 | 40.0% | 44.4% | |
| 28.57% | 14 | 1.7 | 568 | 9,494 | 33.3% | 25.0% | |
| 76.92% | 13 | 1.9 | 659 | 9,248 | 71.4% | 83.3% | |
| 41.67% | 12 | 4.7 | 824 | 10,630 | 57.1% | 20.0% | |
| 41.67% | 12 | 4.3 | 643 | 9,021 | 50.0% | 25.0% | |
| 50.00% | 12 | 2.5 | 754 | 12,964 | 0.0% | 54.5% | |
| 41.67% | 12 | 5.1 | 939 | 11,494 | 40.0% | 42.9% | |
| 72.73% | 11 | 1.1 | 616 | 9,483 | 66.7% | 80.0% | |
| 50.00% | 10 | 3.3 | 586 | 12,163 | 50.0% | 50.0% | |
| 60.00% | 10 | 1.9 | 762 | 11,608 | 50.0% | 66.7% | |
| 50.00% | 10 | 5.2 | 746 | 12,323 | 0.0% | 62.5% | |
| 60.00% | 10 | 5.1 | 776 | 14,281 | 66.7% | 57.1% | |
| 30.00% | 10 | 4.0 | 699 | 11,173 | 0.0% | 33.3% | |
| 70.00% | 10 | 1.6 | 740 | 11,985 | 100.0% | 57.1% | |
| 22.22% | 9 | 4.1 | 590 | 7,514 | 16.7% | 33.3% | |
| 22.22% | 9 | 3.6 | 616 | 10,796 | 66.7% | 0.0% | |
| 55.56% | 9 | 5.2 | 911 | 14,060 | 100.0% | 50.0% | |
| 37.50% | 8 | 3.1 | 629 | 10,729 | 33.3% | 40.0% | |
| 62.50% | 8 | 3.4 | 742 | 11,010 | 60.0% | 66.7% | |
| 50.00% | 8 | 4.8 | 624 | 10,617 | 33.3% | 60.0% | |
| 50.00% | 8 | 4.3 | 819 | 11,814 | 0.0% | 66.7% | |
| 12.50% | 8 | 1.7 | 381 | 8,137 | 20.0% | 0.0% | |
| 50.00% | 8 | 4.3 | 846 | 13,716 | 50.0% | 50.0% | |
| 50.00% | 8 | 4.3 | 897 | 9,042 | 40.0% | 66.7% | |
| 62.50% | 8 | 3.4 | 607 | 11,846 | 80.0% | 33.3% | |
| 71.43% | 7 | 3.1 | 677 | 11,959 | 100.0% | 33.3% | |
| 57.14% | 7 | 4.7 | 874 | 14,933 | 50.0% | 60.0% | |
| 71.43% | 7 | 2.2 | 732 | 10,038 | 66.7% | 75.0% | |
| 14.29% | 7 | 4.2 | 862 | 8,817 | 0.0% | 50.0% | |
| 33.33% | 6 | 4.8 | 722 | 11,022 | 50.0% | 25.0% | |
| 50.00% | 6 | 1.5 | 728 | 10,698 | 66.7% | 33.3% | |
| 66.67% | 6 | 4.0 | 789 | 13,008 | 100.0% | 50.0% | |
| 83.33% | 6 | 2.6 | 555 | 7,612 | 66.7% | 100.0% | |
| 33.33% | 6 | 4.2 | 732 | 12,658 | 0.0% | 50.0% | |
| 50.00% | 6 | 4.9 | 615 | 10,941 | 0.0% | 75.0% | |
| 50.00% | 6 | 4.2 | 465 | 7,615 | 50.0% | 0.0% | |
| 40.00% | 5 | 4.0 | 572 | 11,434 | 0.0% | 50.0% | |
| 20.00% | 5 | 3.9 | 806 | 9,711 | 0.0% | 50.0% | |
| 20.00% | 5 | 1.4 | 517 | 7,984 | 33.3% | 0.0% | |
| 40.00% | 5 | 3.8 | 571 | 8,705 | 25.0% | 100.0% | |
| 40.00% | 5 | 6.0 | 849 | 9,671 | 33.3% | 50.0% | |
| 40.00% | 5 | 6.0 | 751 | 9,206 | 50.0% | 33.3% | |
| 60.00% | 5 | 4.0 | 512 | 12,761 | 0.0% | 75.0% | |
| 60.00% | 5 | 3.0 | 515 | 9,442 | 100.0% | 33.3% | |
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, Smolder, and Nami. 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 Orianna, Olaf, and Renekton. 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, Smolder, and Nami 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?
Orianna, Olaf, and Renekton 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.