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 | BALAZS Luca | - | - | 1% | 10% | 33% | 45% | 11% |
2 | ZHENG Erin | 1% | 6% | 21% | 33% | 27% | 11% | 2% |
3 | DHAIYA Tanya | - | 1% | 5% | 19% | 34% | 31% | 10% |
3 | XU Amy(Chenyu) | - | 5% | 21% | 38% | 28% | 7% | |
5 | QI Julieanne | - | - | - | - | 5% | 32% | 63% |
6 | LEE Gloria Y. | - | - | 1% | 8% | 29% | 42% | 20% |
7 | TAM Connie | - | - | 4% | 15% | 32% | 35% | 14% |
8 | OLELE Ifechi | - | 3% | 14% | 31% | 33% | 15% | 3% |
9 | WANG Sophie Y. | - | - | 1% | 6% | 25% | 43% | 25% |
10 | WANG Chloe | - | 1% | 14% | 37% | 36% | 12% | |
11 | YU Eva | - | 4% | 18% | 38% | 32% | 8% | |
12 | WANG Selina | - | 3% | 12% | 29% | 34% | 18% | 3% |
13 | WANG Cecilia | - | - | 5% | 23% | 45% | 26% | |
14 | WU Michelle | - | - | 1% | 6% | 25% | 46% | 23% |
15 | CHEN Alina | - | 2% | 12% | 31% | 36% | 17% | 3% |
16 | LEE Kate | 9% | 32% | 37% | 18% | 4% | - | |
17 | WEI Sherry | - | - | 1% | 10% | 42% | 47% | |
18 | DESANTIS-IBANEZ Elena | - | - | 1% | 5% | 20% | 41% | 33% |
19 | FURMAN Elizabeth | 2% | 14% | 33% | 34% | 15% | 2% | - |
20 | KONG Mila W. | - | 4% | 23% | 41% | 27% | 6% | |
21 | LI Caroline | - | - | 4% | 15% | 33% | 34% | 12% |
22 | KANE Alexa | - | 4% | 18% | 38% | 30% | 9% | 1% |
23 | WONG Sydney | - | - | 4% | 23% | 45% | 28% | |
24 | BOROTKO Katerina | - | - | 4% | 21% | 46% | 29% | |
25 | DU Andria | - | 3% | 16% | 36% | 33% | 11% | 1% |
26 | LI Nicole | 6% | 25% | 36% | 24% | 8% | 1% | - |
27 | LIU Chloe | 1% | 10% | 29% | 36% | 20% | 5% | - |
28 | LIN Alexis | 9% | 28% | 34% | 21% | 7% | 1% | - |
29 | BI Michelle | - | - | 4% | 23% | 51% | 23% | |
30 | YANG Eleanor | 9% | 32% | 37% | 18% | 4% | - | |
31 | KOUAME Candice | 16% | 39% | 33% | 11% | 2% | - | - |
32 | GOH Cayla | < 1% | - | 1% | 9% | 27% | 40% | 22% |
33 | MENG YIFAN | - | - | - | 2% | 16% | 45% | 36% |
34 | NING Miranda | - | 2% | 10% | 26% | 35% | 22% | 5% |
35 | XU Mulan | 12% | 33% | 34% | 17% | 4% | - | - |
36 | ADYANTHAYA Anika | - | - | 4% | 20% | 43% | 32% | |
36 | YOUN Emily | 1% | 10% | 38% | 40% | 11% | 1% | |
38 | JIANG chenxi | 4% | 27% | 42% | 23% | 4% | - | |
39 | BURT Emmalyne Grace | 1% | 7% | 22% | 34% | 26% | 9% | 1% |
40 | CORNFIELD Emily | 4% | 19% | 34% | 28% | 12% | 2% | - |
41 | CHOI Arianna | 2% | 12% | 29% | 33% | 19% | 5% | - |
42 | XU Emily | 2% | 13% | 30% | 33% | 17% | 4% | - |
43 | TISHKOVA-ROBERTS Daria | 1% | 10% | 40% | 38% | 10% | 1% | |
44 | LIANG Carina | 1% | 9% | 32% | 39% | 17% | 2% | |
45 | JU Jennifer | 5% | 30% | 41% | 20% | 4% | - | |
46 | IVANOV Angela-Sophie | 22% | 49% | 24% | 4% | - | - | |
47 | YAN Ximei (Alicia) | 2% | 14% | 33% | 34% | 15% | 2% | - |
47 | DIETIKER Claire | 31% | 42% | 21% | 5% | 1% | - | - |
49 | CHAKRAPANI Tara | 8% | 32% | 37% | 18% | 4% | - | - |
49 | CHEN Laila | 7% | 30% | 38% | 20% | 5% | 1% | - |
51 | HALE Reagan | 5% | 23% | 35% | 26% | 10% | 2% | - |
52 | TIAN Victoria | 2% | 11% | 27% | 33% | 20% | 6% | 1% |
53 | JIN Alice | 49% | 42% | 8% | 1% | - | - | |
54 | SULLIVAN Adela | 23% | 45% | 27% | 4% | - | - | |
55 | KROHN Daphne | 3% | 18% | 35% | 31% | 12% | 2% | |
56 | SHIN Jamie | 26% | 47% | 23% | 4% | - | - | |
57 | KHANNA Bhairavi | 55% | 36% | 8% | 1% | - | - | |
58 | LEE Eden | 2% | 16% | 36% | 32% | 12% | 2% | - |
59 | HOWARD Katherine | 18% | 40% | 31% | 10% | 1% | - | - |
60 | DING Iris Siyue | 11% | 35% | 37% | 15% | 3% | - | - |
61 | REDWINE Louise | 18% | 37% | 30% | 12% | 2% | - | - |
62 | BURROWS Beatrice | 24% | 42% | 26% | 7% | 1% | - | |
63 | ORDORICA Abra | 1% | 6% | 23% | 38% | 27% | 6% | - |
64 | HAN Emma | 28% | 41% | 24% | 7% | 1% | - | - |
65 | PINCH Elise | 46% | 40% | 13% | 2% | - | - | - |
66 | RAJPUT Mahek | 6% | 23% | 35% | 26% | 9% | 2% | - |
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.