Arlington ESports Stadium - Arlington, TX, USA
Explore the pool victory probability density for each fencer, with their actual victories highlighted in a box. Learn more.
# | Name | Number of victories | ||||||
---|---|---|---|---|---|---|---|---|
0 | 1 | 2 | 3 | 4 | 5 | 6 | ||
1 | VAID Luke | - | - | - | 2% | 16% | 43% | 38% |
2 | CHON Collin | - | - | 2% | 13% | 33% | 38% | 13% |
3 | GAY Jono | - | - | 2% | 10% | 29% | 39% | 20% |
3 | ZLATINSKI Jason | - | 1% | 8% | 25% | 37% | 24% | 6% |
5 | HENDERSON Lucas | - | - | 5% | 24% | 45% | 26% | |
6 | GONZALEZ Jake | - | 2% | 12% | 34% | 41% | 11% | |
7 | BELL III Alfred (Tripp) R. | - | - | - | 1% | 9% | 34% | 55% |
8 | WEI Rian | - | 1% | 13% | 39% | 36% | 10% | |
9 | KANG evan R. | - | - | - | 1% | 11% | 54% | 33% |
10 | LIU Daniel | 2% | 11% | 27% | 33% | 20% | 6% | 1% |
11 | MEADE Liam R. | 1% | 11% | 33% | 36% | 16% | 3% | - |
12 | KITSON Chase | - | 1% | 8% | 29% | 40% | 19% | 3% |
13 | URSU Marcel T. | - | - | 1% | 10% | 38% | 51% | |
14 | KANG Matthew | - | - | 5% | 25% | 49% | 20% | |
15 | CHAMBERS Miles | - | - | 1% | 9% | 41% | 49% | |
16 | LI AYDEN | - | - | 3% | 13% | 31% | 36% | 16% |
17 | GUREVICH Benjamin | - | 1% | 8% | 24% | 35% | 25% | 7% |
18 | ZHANG Kaixuan | 1% | 8% | 24% | 34% | 24% | 8% | 1% |
19 | BOSITA Brennan | 1% | 7% | 25% | 37% | 24% | 6% | - |
20 | CLARK Aram | - | - | - | 2% | 12% | 37% | 49% |
21 | KWON Kenneth | 1% | 9% | 25% | 34% | 24% | 8% | 1% |
22 | SUN Andrew | - | 1% | 6% | 23% | 37% | 26% | 7% |
23 | CHEN Kevin | - | 4% | 15% | 29% | 31% | 17% | 4% |
24 | LI Huangziyue | 9% | 34% | 39% | 15% | 2% | - | |
25 | BOLLU Viren | 7% | 27% | 38% | 23% | 5% | - | |
26 | ZHAO Royce | - | 1% | 7% | 30% | 44% | 19% | |
27 | YUEN Caleb | 7% | 26% | 35% | 23% | 8% | 1% | - |
28 | NAMBIAR Navin | 9% | 30% | 37% | 20% | 4% | - | |
29 | RAJMOHAN Arya | 1% | 9% | 26% | 34% | 22% | 6% | 1% |
30 | KIM Yusung | 9% | 27% | 34% | 22% | 7% | 1% | - |
31 | CAO Donald | - | 3% | 14% | 30% | 33% | 17% | 3% |
32 | HUANG Caleb | 17% | 39% | 32% | 10% | 1% | - | |
33 | XUE Leo | 1% | 9% | 28% | 37% | 21% | 4% | - |
34 | LUO Leonard | - | 5% | 19% | 33% | 29% | 12% | 2% |
35 | WANG Alex | 1% | 11% | 28% | 34% | 20% | 5% | - |
36 | SIDDAMSHETTY Ishaan | 4% | 18% | 32% | 29% | 13% | 3% | - |
37 | XIA Matthew | 6% | 27% | 41% | 22% | 4% | - | |
38 | CAUTHRON Oliver | 3% | 14% | 30% | 32% | 17% | 4% | - |
39 | KANG Jeremy | - | - | 1% | 10% | 32% | 42% | 15% |
40 | BADMUS Joshua | 17% | 38% | 30% | 12% | 2% | - | - |
41 | SLAVNOV Anton | 1% | 10% | 26% | 33% | 22% | 7% | 1% |
42 | LIN Alex | 11% | 44% | 35% | 9% | 1% | - | |
43 | KU Collin | 50% | 38% | 11% | 1% | - | - | - |
44 | DAI Zihou | 1% | 7% | 23% | 35% | 25% | 8% | 1% |
45 | WONG Ron | 1% | 10% | 26% | 33% | 22% | 7% | 1% |
46 | TANG Morgan | - | 2% | 10% | 26% | 35% | 23% | 5% |
47 | WANG tiger | - | 3% | 15% | 32% | 32% | 15% | 3% |
48 | MILLER Joseph | - | 1% | 7% | 22% | 35% | 27% | 8% |
49 | PAUL James | 2% | 15% | 35% | 32% | 14% | 3% | - |
49 | RINALDI Savio | 7% | 29% | 37% | 21% | 6% | 1% | - |
51 | LIU Guanyu | 28% | 42% | 23% | 6% | 1% | - | - |
52 | BROOKS Drake | 1% | 10% | 25% | 33% | 23% | 7% | 1% |
53 | KAMURA Kosei | 3% | 25% | 45% | 23% | 4% | - | |
54 | ROBINSON Ezra | 10% | 32% | 37% | 18% | 3% | - | |
55 | BROOKS Isaac | 16% | 40% | 31% | 11% | 2% | - | - |
56 | BAERENWALD Tybalt Wolfram | 1% | 7% | 23% | 34% | 26% | 9% | 1% |
57 | WILLIAMS Grayson | 49% | 40% | 10% | 1% | - | - | - |
58 | ZHAO Aidan | 12% | 33% | 34% | 16% | 4% | - | - |
59 | LUCAS William | - | 3% | 15% | 33% | 34% | 14% | 1% |
60 | BROOKS Theo | 13% | 41% | 33% | 11% | 2% | - | - |
61 | SONG Aidan | 1% | 9% | 31% | 38% | 18% | 3% | - |
62 | LI Ryan | 12% | 34% | 36% | 16% | 3% | - | |
63 | SENTHIL Gatik | 58% | 35% | 6% | - | - | - | |
64 | KEMP Austin | 5% | 30% | 45% | 18% | 2% | - | |
65 | REILLEY Brogan | 34% | 41% | 20% | 5% | 1% | - | - |
66 | THOTAKURA Sreyas | 7% | 34% | 38% | 17% | 4% | - | - |
67 | KAYITHI Nikhil | 4% | 27% | 39% | 22% | 6% | 1% | - |
The heatmap in this table provides a visual representation of the victory probability distribution for each fencer in their respective pools:
This heatmap visualization offers an immediate understanding of each fencer's expected performance compared to their actual results.