Rockland Community College, Eugene Levy Field House - 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 | WONG Max | - | - | 3% | 21% | 43% | 29% | 3% |
2 | LOO Jason | - | 3% | 17% | 36% | 33% | 11% | |
3 | DAI Zihou | - | 1% | 5% | 19% | 34% | 31% | 11% |
3 | JI Johnson | - | - | 1% | 5% | 22% | 44% | 28% |
5 | CHAMBERS Miles | - | - | - | - | 4% | 28% | 68% |
5 | LEVY Daniel | - | 5% | 19% | 33% | 29% | 12% | 1% |
7 | SALDARINI Glenn | - | - | 3% | 18% | 40% | 32% | 7% |
8 | LEVIN Jacob | 1% | 6% | 20% | 33% | 27% | 11% | 2% |
9 | AGARWAAL Yohan | - | - | 1% | 7% | 26% | 45% | 22% |
10 | BELAND Riley James "RJ" | - | - | 1% | 7% | 25% | 42% | 26% |
11 | LIN Brendan | - | - | 1% | 8% | 28% | 42% | 20% |
12 | TASIKAS Peter | - | - | 4% | 21% | 38% | 29% | 8% |
13 | ROSADO Keviel | - | - | - | 1% | 9% | 38% | 53% |
14 | ISAYENKO Daniel | - | - | 4% | 19% | 43% | 34% | |
15 | NAYAGAM Nishant | 1% | 10% | 27% | 33% | 21% | 6% | 1% |
16 | SUH Leo | - | 2% | 11% | 30% | 37% | 18% | 2% |
17 | KOZLOV Lucas | - | - | 2% | 15% | 44% | 39% | |
18 | ROPER F. Elijah | - | - | - | 4% | 20% | 44% | 31% |
19 | ORIE Sohan | - | 2% | 10% | 25% | 34% | 23% | 6% |
20 | DOSTAL Maximilian | - | 5% | 22% | 39% | 27% | 6% | |
21 | MIAO Heqi | - | 2% | 15% | 34% | 35% | 13% | |
22 | BEAL Colton | - | 1% | 13% | 39% | 37% | 10% | |
23 | LEE Damian | 1% | 7% | 21% | 32% | 26% | 11% | 2% |
24 | KOSMIN Ivan | 1% | 14% | 33% | 33% | 16% | 4% | - |
25 | TAYCHER Aaron | - | 3% | 15% | 31% | 32% | 16% | 3% |
26 | OREN Daniel | 1% | 8% | 23% | 33% | 24% | 9% | 1% |
27 | MELE Gianni | 2% | 12% | 29% | 32% | 19% | 5% | 1% |
28 | KOREN George | - | 1% | 11% | 37% | 39% | 11% | |
29 | WANG Theodore | 1% | 11% | 32% | 36% | 18% | 3% | |
30 | ZWAKA Jonas | - | 2% | 13% | 33% | 37% | 15% | |
31 | SO Morgan | - | - | 3% | 16% | 35% | 34% | 11% |
32 | SUBA Mason | - | 3% | 13% | 29% | 33% | 18% | 4% |
33 | LUCAS William | - | - | 3% | 12% | 29% | 37% | 20% |
34 | WONG Mac | - | 2% | 11% | 28% | 34% | 20% | 4% |
35 | SAYAR Luke | - | 1% | 9% | 28% | 39% | 20% | 2% |
36 | MARTINSON Torm | - | 4% | 15% | 31% | 31% | 16% | 3% |
37 | WONG Reagan | - | 7% | 26% | 38% | 24% | 5% | |
38 | NG Oliver | - | - | 3% | 17% | 36% | 33% | 11% |
39 | DAYAMA Ronak | - | 3% | 14% | 32% | 34% | 15% | 2% |
40 | TITOV Zachary | 1% | 7% | 23% | 33% | 25% | 9% | 1% |
41 | MATTOO Dhruv | - | 1% | 9% | 29% | 37% | 20% | 4% |
42 | WEI Hunter | - | 6% | 23% | 37% | 26% | 7% | 1% |
43 | CHAVAN Aditya | - | 3% | 14% | 33% | 33% | 14% | 2% |
44 | YI Andrew | - | 4% | 20% | 38% | 30% | 7% | |
45 | LIANG Morgan | - | 2% | 12% | 32% | 38% | 16% | |
46 | HENDERSON Louis | 1% | 7% | 25% | 37% | 24% | 6% | |
47 | GRIGORYAN Sevak | - | 5% | 20% | 34% | 28% | 11% | 2% |
48 | LAU Kyrus | - | 1% | 8% | 23% | 34% | 26% | 8% |
49 | BROOKS Drake | - | 4% | 19% | 36% | 30% | 10% | 1% |
50 | SUN Youning | 5% | 19% | 32% | 28% | 13% | 3% | - |
51 | CHANG Timothy | - | 4% | 17% | 35% | 32% | 11% | 1% |
52 | SAGE Nikolai | - | - | 3% | 14% | 32% | 35% | 15% |
52 | PANCHERI Matteo | - | 2% | 15% | 39% | 33% | 10% | 1% |
54 | LIU Ryan | - | - | 1% | 10% | 31% | 39% | 18% |
55 | AVERY Marcus | - | 1% | 7% | 22% | 35% | 27% | 8% |
56 | LIM JUWANA Maximilian | - | 2% | 9% | 24% | 34% | 24% | 7% |
57 | LEIGH Brayden | 1% | 10% | 31% | 36% | 18% | 4% | - |
58 | WANG Muzhou | 1% | 8% | 28% | 38% | 21% | 4% | |
59 | MHLEY Gavin | 12% | 39% | 34% | 13% | 2% | - | |
60 | EARLEY Jack | 29% | 43% | 23% | 5% | 1% | - | |
61 | ZHANG YIXUAN | - | 5% | 18% | 32% | 29% | 13% | 2% |
62 | ZHANG Weihang | 5% | 29% | 39% | 22% | 5% | - | |
63 | CIECIEREGA MATTHEW | 4% | 18% | 32% | 29% | 14% | 3% | - |
64 | ABELTSAI Hauke | 15% | 39% | 32% | 12% | 2% | - | - |
65 | AWAD Omar | - | 4% | 16% | 31% | 30% | 15% | 3% |
66 | LEE Ryan | - | 6% | 20% | 33% | 27% | 11% | 2% |
67 | FOUX Jonathan | 1% | 9% | 28% | 36% | 21% | 5% | - |
68 | KURIYAMA Marcus | 16% | 39% | 32% | 12% | 2% | - | - |
69 | LI Michael | 4% | 25% | 44% | 23% | 4% | - | |
70 | WAXLER Alex | 4% | 21% | 38% | 28% | 9% | 1% | |
71 | ZHERENOVSKY Alan | 20% | 38% | 29% | 11% | 2% | - | - |
72 | DAI Ethan | 9% | 33% | 39% | 16% | 3% | - | - |
73 | WU Vincent | - | 4% | 15% | 30% | 31% | 16% | 3% |
74 | GAIDA Ashton | 2% | 15% | 34% | 32% | 15% | 3% | - |
75 | SHAPIRO Leo | - | 5% | 17% | 31% | 30% | 14% | 3% |
76 | NARAYAN Rishi | 1% | 8% | 27% | 38% | 22% | 5% | - |
77 | XIANG Austin | 16% | 41% | 32% | 9% | 1% | - | - |
78 | HE Eric | 15% | 39% | 33% | 12% | 2% | - | - |
78 | JARRETT Benjamin | 32% | 43% | 20% | 4% | - | - | - |
80 | CUSSON William | 1% | 15% | 36% | 32% | 13% | 2% | - |
81 | SOCHNIKOV Jacob | 34% | 44% | 19% | 3% | - | - | - |
82 | LEE Jeffrey | 20% | 47% | 27% | 5% | - | - | |
83 | LI Lucas | 13% | 38% | 35% | 12% | 2% | - | - |
84 | HUANG Anthony | 25% | 43% | 25% | 7% | 1% | - | - |
85 | CHEN Anson | 4% | 20% | 37% | 28% | 10% | 2% | - |
86 | PATEL Kiran | 72% | 25% | 3% | - | - | - | - |
87 | ZHENG Lucas | 8% | 26% | 34% | 22% | 8% | 1% | - |
88 | HUANG Lucas | 29% | 43% | 22% | 5% | 1% | - | - |
89 | BURNS Carson | 20% | 40% | 29% | 10% | 2% | - | - |
90 | CHEN Brian | 9% | 29% | 34% | 20% | 6% | 1% | - |
90 | SONG Jerry | 3% | 18% | 36% | 31% | 11% | 2% | - |
92 | HE Nolan | 8% | 33% | 42% | 15% | 2% | - | - |
93 | LEE Ivan | 14% | 39% | 33% | 11% | 2% | - | |
94 | ZHAO Owen | 38% | 42% | 17% | 3% | - | - | |
95 | GAO Francis | 48% | 38% | 12% | 2% | - | - | - |
95 | LI Kent | 37% | 45% | 16% | 2% | - | - | - |
97 | WANG Harrison | 2% | 22% | 39% | 27% | 8% | 1% | - |
98 | RAJMOHAN Syon | 65% | 29% | 5% | - | - | - | - |
99 | DY Azriel | 62% | 32% | 6% | - | - | - | |
99 | KULKARNI Ishir | 42% | 44% | 13% | 1% | - | - | |
101 | SHVETS Zakhar | 2% | 14% | 31% | 33% | 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.