Suffern, NY - Suffern, NY, 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 | TOLBA Abdelrahman | - | - | - | 1% | 7% | 33% | 60% |
2 | GOOR Julian | - | - | - | 3% | 22% | 48% | 27% |
3 | PO Oliver | - | - | 5% | 24% | 45% | 26% | |
3 | WANG Jackson | - | 3% | 20% | 39% | 30% | 8% | |
5 | RUSADZE Nickolas | - | - | - | - | - | 11% | 88% |
6 | GARCIA Sebastian R. | - | - | 1% | 7% | 25% | 41% | 26% |
7 | LIN James G. | - | 1% | 10% | 33% | 40% | 16% | |
8 | AUGUSTINE Aaron A. | - | 1% | 8% | 27% | 40% | 23% | |
9 | MARX Jackson L. | - | - | - | 1% | 9% | 37% | 54% |
10 | LI Ayren | - | - | 5% | 24% | 42% | 25% | 3% |
11 | ZHAI Jeffrey | - | - | 3% | 15% | 34% | 36% | 11% |
12 | LI Yao (Liam) | - | 2% | 13% | 35% | 37% | 14% | |
13 | WANG Mason | 1% | 11% | 32% | 36% | 17% | 3% | |
14 | KOVACS Wyatt | 1% | 11% | 30% | 35% | 19% | 4% | - |
15 | XIANG Derrick | - | 1% | 7% | 25% | 39% | 25% | 4% |
16 | GENIESER Graydon | - | 1% | 8% | 27% | 38% | 22% | 4% |
17 | CATINO Brennen | - | - | 2% | 11% | 29% | 39% | 20% |
18 | WANG Julang | 1% | 11% | 30% | 35% | 18% | 3% | - |
19 | LEE Jacob J | - | 2% | 14% | 36% | 36% | 13% | |
20 | ZHEN Ethan | - | - | 6% | 27% | 45% | 22% | |
21 | TRAUGOT Owen G. | - | 1% | 9% | 33% | 41% | 17% | |
22 | LI Aaron | - | - | 1% | 7% | 29% | 47% | 16% |
23 | LOGAN Kai | - | 2% | 17% | 38% | 31% | 10% | 1% |
24 | ZHOU Leon | - | 3% | 22% | 43% | 26% | 5% | |
25 | LEE Jonah | - | 8% | 34% | 38% | 17% | 3% | |
26 | GUO Justin | - | - | 3% | 18% | 41% | 32% | 5% |
27 | NICOLL William | - | 3% | 16% | 33% | 32% | 14% | 2% |
28 | MATSAKH Philip | 1% | 6% | 22% | 34% | 26% | 9% | 1% |
29 | SEMAPAKDI-CHANG Kaiden | - | 1% | 13% | 36% | 37% | 13% | |
30 | OZBURN Will | 4% | 18% | 34% | 29% | 12% | 2% | - |
31 | ZENG Rick | 26% | 49% | 21% | 4% | - | - | |
32 | ZHANG Aaron | 1% | 10% | 28% | 35% | 20% | 6% | 1% |
33 | LIU Ryan | 5% | 26% | 41% | 23% | 4% | < 1% | - |
34 | PARK Joseph | 5% | 27% | 38% | 23% | 7% | 1% | - |
35 | XIAO Benjamin | - | 4% | 19% | 37% | 30% | 9% | 1% |
36 | SHIM Peter S. | 1% | 13% | 34% | 34% | 15% | 3% | - |
37 | AROUH Dylan | - | - | 4% | 18% | 35% | 32% | 10% |
38 | MILLER Jordan | - | 1% | 6% | 26% | 43% | 24% | 2% |
39 | XU Ethan | - | 2% | 14% | 33% | 35% | 15% | 1% |
40 | ZHUANG Chuanxuan | - | 3% | 17% | 35% | 33% | 12% | - |
41 | JIA Jing Yu | 47% | 39% | 12% | 2% | - | - | |
42 | ARCE Andrew W. | 28% | 52% | 18% | 2% | - | - | |
43 | ORLOV Dmitriy | 1% | 7% | 25% | 37% | 25% | 6% | |
44 | DECORLETO III Andrew (Tripp) J. | 5% | 28% | 39% | 22% | 6% | 1% | |
45 | LIEW Jeremy K. | - | 4% | 21% | 39% | 29% | 7% | |
46 | UNGERER Roger M. | 1% | 8% | 26% | 37% | 23% | 5% | - |
47 | GAO Payton | 1% | 9% | 29% | 38% | 20% | 3% | - |
48 | LEE Brendan | 2% | 14% | 31% | 33% | 17% | 4% | - |
48 | VISHAWADIA Jaimin | 4% | 24% | 40% | 25% | 6% | 1% | - |
50 | CHUNG Ian | 15% | 41% | 32% | 10% | 1% | - | - |
51 | HUANG Julian | 4% | 17% | 32% | 29% | 14% | 3% | - |
52 | HOSANAGAR Ninad | 72% | 24% | 3% | - | - | - | |
53 | LEWIS Nikhil I. | 47% | 44% | 8% | 1% | - | - | |
54 | KLOTZ Isaiah | 5% | 32% | 39% | 19% | 4% | - | - |
55 | LEE Eugene | 12% | 45% | 36% | 7% | 1% | - | - |
56 | BANG Ian | 49% | 40% | 11% | 1% | - | - | - |
57 | SHIN Jiho | 13% | 38% | 35% | 13% | 2% | - | - |
58 | CHA James | 1% | 7% | 24% | 38% | 25% | 6% | |
58 | AKYAMAC Bora | 42% | 45% | 12% | 1% | - | - | |
60 | BROOKS Matthew | 10% | 35% | 36% | 16% | 3% | - | - |
61 | BOBROW Silas | 1% | 9% | 37% | 38% | 14% | 2% | |
62 | LI Allen | 46% | 39% | 13% | 2% | - | - | - |
63 | HIGGASON Hugh | 7% | 63% | 26% | 4% | - | - | |
64 | WEI Qian | 29% | 43% | 23% | 5% | 1% | - | - |
65 | CHOI Eugene | 30% | 42% | 22% | 5% | 1% | - | - |
66 | BANG Sian | 67% | 29% | 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.