Golisano Training Center at Nazareth University - Rochester, 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 | KHANNA Adamantis | - | - | - | - | 5% | 31% | 63% |
2 | YUEN Caleb | - | 1% | 9% | 25% | 35% | 24% | 6% |
3 | MIAO Heqi | - | 2% | 12% | 34% | 41% | 12% | |
3 | SONG Aidan | - | - | 2% | 10% | 29% | 39% | 20% |
5 | SLAVNOV Anton | - | 1% | 5% | 17% | 32% | 32% | 13% |
6 | LEVY Daniel | - | 3% | 16% | 32% | 31% | 15% | 3% |
7 | HENDERSON Louis | - | 1% | 6% | 20% | 35% | 29% | 10% |
8 | D'AMELJ Edoardo | - | 5% | 20% | 37% | 30% | 7% | |
9 | ISAYENKO Daniel | - | - | 1% | 12% | 40% | 47% | |
10 | LIANG Morgan | 2% | 13% | 32% | 34% | 16% | 3% | |
11 | BEAL Colton | - | - | 3% | 15% | 32% | 35% | 15% |
12 | CHAVAN Aditya | - | 4% | 17% | 34% | 30% | 12% | 2% |
13 | CHEN Leo | 2% | 13% | 29% | 33% | 18% | 5% | - |
14 | KOZLOV Lucas | - | - | 3% | 17% | 41% | 38% | |
15 | AGARWAAL Yohan | - | 2% | 12% | 31% | 38% | 16% | |
16 | PARK Sean | 9% | 31% | 36% | 19% | 4% | - | |
17 | LIU Jeremy | - | 2% | 11% | 31% | 38% | 18% | |
18 | KOREN David | 2% | 14% | 31% | 32% | 17% | 4% | - |
19 | LAU Kyrus | - | 1% | 5% | 18% | 34% | 31% | 10% |
20 | LIM JUWANA Maximilian | - | 1% | 5% | 22% | 43% | 30% | |
21 | AVERY Marcus | - | 3% | 16% | 35% | 34% | 11% | |
22 | CHANG Ethan | - | - | 3% | 17% | 39% | 36% | 5% |
23 | HAO Johnny | - | 5% | 22% | 37% | 28% | 7% | |
24 | MAKLIN David | 11% | 35% | 35% | 16% | 3% | - | |
25 | BRADY Jack | 4% | 19% | 36% | 30% | 10% | 1% | |
26 | KOREN George | - | 2% | 12% | 32% | 37% | 16% | |
27 | SHAPIRO Leo | - | 4% | 16% | 31% | 31% | 15% | 3% |
28 | RINALDI Benigno | 2% | 13% | 33% | 34% | 15% | 3% | |
29 | LI kevin | 17% | 38% | 32% | 11% | 2% | - | |
30 | VIDREVICH David | 2% | 10% | 26% | 32% | 22% | 7% | 1% |
31 | TITOV Zachary | - | 6% | 22% | 34% | 26% | 10% | 1% |
32 | BADMUS David | 3% | 16% | 34% | 31% | 14% | 3% | - |
33 | YANG LOUIS | 3% | 16% | 30% | 30% | 16% | 4% | - |
34 | YI Andrew | - | - | 3% | 15% | 33% | 35% | 13% |
35 | WANG Harrison | 8% | 29% | 38% | 20% | 4% | - | - |
35 | ALUF Brendon | - | 5% | 19% | 34% | 29% | 11% | 2% |
37 | CHEN Brian | 4% | 21% | 37% | 28% | 9% | 1% | |
38 | ZALETAEV Jacob | 3% | 16% | 35% | 32% | 13% | 2% | |
39 | ARTETA-CHEVALIER Ulysse | - | 5% | 18% | 32% | 30% | 13% | 2% |
40 | LEIGH Brayden | 2% | 14% | 32% | 33% | 15% | 3% | - |
41 | SUN Stephen | 1% | 5% | 21% | 37% | 28% | 8% | - |
42 | HU Simon | - | 5% | 21% | 37% | 29% | 8% | |
43 | MOTOV Max | 3% | 19% | 37% | 30% | 9% | 1% | |
44 | DAI Ethan | 30% | 43% | 22% | 5% | - | - | |
45 | LI Lucas | 13% | 38% | 33% | 13% | 2% | - | - |
46 | BURENKOV Matthew | 4% | 25% | 37% | 25% | 8% | 1% | - |
47 | IP Hunter | - | 2% | 11% | 28% | 35% | 21% | 5% |
48 | ZHANG Weihang | 11% | 33% | 35% | 17% | 4% | - | |
49 | LAN Jasper | 23% | 41% | 27% | 8% | 1% | - | |
50 | LEE Aiden | 18% | 40% | 30% | 10% | 1% | - | |
51 | KELLY Collin | 1% | 11% | 30% | 36% | 19% | 3% | |
51 | ROSE Parker | 5% | 25% | 40% | 25% | 6% | - | |
53 | MAUREL Louis | 7% | 29% | 38% | 21% | 4% | - | |
54 | LEE Shane Gunn | 3% | 16% | 34% | 32% | 13% | 2% | |
55 | PARK Layne | 2% | 14% | 30% | 31% | 17% | 5% | 1% |
56 | LIU Caleb | 1% | 11% | 28% | 34% | 20% | 6% | 1% |
57 | WU Dylan | 21% | 39% | 29% | 10% | 2% | - | - |
58 | HUANG Lucas | 37% | 41% | 18% | 4% | - | - | - |
59 | MURDOCH Leo | 2% | 12% | 29% | 32% | 18% | 5% | 1% |
60 | REINHART Rowan | 1% | 15% | 33% | 32% | 15% | 3% | - |
61 | LI Jayden | 32% | 42% | 20% | 5% | - | - | |
62 | SABINO Bennett | 22% | 41% | 27% | 8% | 1% | - | |
63 | CHEN Tyler | 63% | 31% | 6% | 1% | - | - | - |
63 | CHEN Ethan | 21% | 39% | 28% | 10% | 2% | - | - |
65 | DALY Ryan | 1% | 14% | 42% | 32% | 9% | 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.