Liontree Arena (RIMAC) @ UC San Diego - La Jolla, CA, 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 | MOSES Alexander | - | - | 1% | 6% | 24% | 42% | 27% |
2 | MATTIS George | - | - | 1% | 7% | 23% | 40% | 28% |
3 | KIM Benjamin I. | - | - | - | 3% | 19% | 46% | 32% |
3 | LO Jake | - | - | - | 4% | 22% | 47% | 27% |
5 | HUANG Thomas | - | 1% | 9% | 28% | 40% | 21% | |
6 | SINGHA Orion | - | - | - | 4% | 19% | 42% | 34% |
7 | YAO Geoffrey B. | - | - | 2% | 11% | 31% | 38% | 17% |
8 | ZHU Max | - | - | 3% | 15% | 34% | 35% | 13% |
9 | WRIGHT Christopher | - | 2% | 12% | 31% | 37% | 17% | |
10 | ZI QIN Shang | 1% | 6% | 20% | 32% | 27% | 11% | 2% |
11 | ERLIKHMAN Adrian | 1% | 10% | 32% | 37% | 17% | 3% | - |
12 | KIM Nathan | - | 4% | 17% | 35% | 33% | 11% | |
13 | GAO Chaney C. | - | - | 2% | 10% | 29% | 40% | 20% |
14 | HIGGINS Branford | - | 1% | 10% | 30% | 36% | 19% | 3% |
15 | KIM Sullivan | 1% | 8% | 25% | 36% | 24% | 6% | |
16 | ZAYDMAN David M. | - | 1% | 5% | 21% | 37% | 28% | 7% |
17 | FU Leon | - | - | 2% | 11% | 31% | 39% | 17% |
18 | TANG William | 5% | 26% | 38% | 23% | 7% | 1% | - |
19 | SEO Shawn | - | 2% | 10% | 28% | 36% | 21% | 4% |
20 | WANG DEVON | - | 2% | 13% | 41% | 44% | ||
21 | PAK Elliot | 1% | 7% | 21% | 33% | 27% | 11% | 2% |
22 | ZHENG Haoran | - | - | 4% | 17% | 36% | 33% | 10% |
23 | JONES Caleb | - | 4% | 20% | 37% | 28% | 10% | 1% |
24 | MING Nathan | 1% | 8% | 26% | 36% | 22% | 6% | 1% |
25 | ZHOU Stanley Q. | 1% | 7% | 24% | 36% | 26% | 7% | |
26 | DAVOODIAN Christopher | - | 5% | 20% | 36% | 30% | 9% | |
27 | CASTELLY Luke | 1% | 5% | 18% | 32% | 29% | 13% | 2% |
28 | LIU Yikun | 5% | 21% | 34% | 27% | 11% | 2% | - |
29 | CHOI Kaiden I. | 4% | 18% | 35% | 30% | 11% | 2% | |
30 | JU Hanul | 2% | 13% | 32% | 33% | 16% | 3% | - |
31 | POSSON Luke | 43% | 42% | 14% | 2% | - | ||
32 | KIM Ian | 3% | 20% | 41% | 30% | 6% | ||
33 | GILLISON Edward L. | 1% | 7% | 24% | 36% | 25% | 7% | |
33 | LU Ivan | 1% | 6% | 21% | 36% | 28% | 8% | |
35 | WANG owen | 3% | 20% | 41% | 30% | 6% | ||
36 | EVERS Gabriel | - | 5% | 21% | 36% | 27% | 9% | 1% |
37 | CHIRASHNYA Adam | - | 1% | 9% | 26% | 37% | 23% | 4% |
38 | SCHROEDER Dylan | - | 3% | 14% | 32% | 33% | 15% | 2% |
39 | LEE Chun Po | 9% | 36% | 38% | 15% | 2% | ||
40 | LI Yunji | 9% | 33% | 36% | 17% | 4% | - | - |
41 | PARK Augustine | 6% | 28% | 38% | 21% | 5% | 1% | - |
42 | MULCAHY Olaf | 1% | 8% | 24% | 36% | 25% | 6% | |
43 | VILLALOBOSKOWALSKI Demetrious C. | 7% | 25% | 36% | 24% | 7% | 1% | |
44 | YAO Derek (Shunyu) | 4% | 19% | 35% | 29% | 11% | 2% | |
45 | CROSSMAN Brandon | 8% | 28% | 36% | 21% | 6% | 1% | |
46 | OBERDERFER Vladimir | 15% | 35% | 33% | 14% | 3% | - | |
47 | WESTON Tom | - | 1% | 9% | 30% | 40% | 17% | 2% |
48 | MENDOZA Zachari | 1% | 7% | 28% | 37% | 21% | 6% | 1% |
49 | HARR Carver | - | 2% | 12% | 30% | 35% | 17% | 3% |
50 | SHEN Jiayi | 43% | 41% | 13% | 2% | - | - | - |
51 | LEE Damien | 8% | 29% | 37% | 21% | 5% | 1% | - |
52 | KIM Teddy | 3% | 22% | 40% | 27% | 7% | 1% | - |
53 | LEE Jake (JiYuen) | 28% | 42% | 23% | 6% | 1% | - | |
54 | MIAO Kunqi | 14% | 35% | 33% | 15% | 3% | - | |
55 | KNUDSEN Travis | 10% | 33% | 35% | 17% | 4% | - | |
56 | LI Zerong | 22% | 41% | 27% | 8% | 1% | - | - |
57 | KIM Jayden | 3% | 15% | 30% | 31% | 16% | 4% | - |
58 | LIU Noah | 14% | 44% | 32% | 10% | 1% | - | - |
59 | PAINTER Noah | 52% | 38% | 9% | 1% | - | - | - |
60 | NALBANDIAN VAHAN P. | 14% | 34% | 32% | 16% | 4% | 1% | - |
61 | CHEN Bailey | 10% | 30% | 36% | 19% | 5% | - | |
62 | HOLLAND Thomas | 9% | 34% | 38% | 17% | 3% | - | - |
63 | FAN Joshua | 40% | 41% | 16% | 3% | - | - | - |
64 | GOROZA Eric | 38% | 42% | 17% | 3% | - | - | - |
65 | LIU Yueri | 11% | 33% | 35% | 16% | 4% | - | - |
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.