Greater Columbus Convention Center - Columbus, OH, 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 | POSSICK Lola P. | - | - | 1% | 8% | 35% | 57% | |
2 | LU Vivian Y. | - | - | - | 1% | 10% | 38% | 51% |
3 | SHEALY Maggie | - | - | - | 1% | 7% | 34% | 58% |
3 | LEE Alexandra B. | - | - | - | 3% | 15% | 40% | 42% |
5 | BEVACQUA Aria F. | - | 1% | 8% | 23% | 35% | 26% | 7% |
6 | GREENBAUM Atara R. | - | - | - | 2% | 14% | 42% | 42% |
7 | SHEARER Natalie E. | 2% | 12% | 30% | 35% | 19% | 4% | |
8 | FEIG Sela | 2% | 14% | 32% | 33% | 16% | 3% | - |
9 | SHOMAN Jenna | - | - | - | - | 4% | 27% | 69% |
10 | SULLIVAN Siobhan R. | - | - | - | 4% | 20% | 43% | 33% |
11 | LEE Hannah | - | 1% | 4% | 16% | 33% | 33% | 13% |
12 | KRASTEV Minna | - | 4% | 17% | 33% | 31% | 13% | 2% |
13 | LIU Sophie | - | 1% | 8% | 32% | 47% | 12% | |
14 | CARVALHO Isabela A. | - | - | 2% | 13% | 35% | 37% | 12% |
15 | SCHIMINOVICH Sophia I. | - | 1% | 8% | 24% | 38% | 25% | 3% |
16 | JUNG Irene | - | 1% | 8% | 25% | 36% | 24% | 6% |
17 | ANDRES Charmaine G. | - | 1% | 5% | 21% | 37% | 29% | 7% |
18 | XIAO julie | 1% | 7% | 24% | 37% | 25% | 6% | |
19 | PAUL Lila | - | 1% | 6% | 20% | 35% | 29% | 9% |
20 | YUCEL Emine I. | - | - | 3% | 14% | 34% | 37% | 12% |
21 | KOVACS Sophia | - | - | - | 5% | 33% | 62% | |
22 | TSUI Natalie | 1% | 7% | 25% | 38% | 24% | 5% | |
23 | SOURIMTO Valeria | 3% | 15% | 33% | 32% | 14% | 2% | |
24 | SANZ Madeline A. | - | 2% | 11% | 29% | 36% | 19% | 4% |
25 | VADASZ Ibla P. | - | 2% | 9% | 24% | 34% | 24% | 7% |
26 | DELSOIN Chelsea C. | - | - | - | 2% | 11% | 36% | 51% |
27 | YANG Angelina LeLe | - | 4% | 19% | 38% | 29% | 9% | 1% |
28 | ANDRES Katherine A. | - | 2% | 12% | 32% | 37% | 16% | |
29 | CHEN Ashley | 1% | 6% | 24% | 39% | 26% | 4% | |
30 | LIU Yifei | 3% | 19% | 38% | 31% | 8% | - | |
31 | SAYLES Nina R. | - | 1% | 6% | 25% | 39% | 24% | 5% |
32 | KIM Marley I. | - | 5% | 19% | 34% | 29% | 11% | 1% |
33 | STRZALKOWSKI Aleksandra (Ola) M. | - | - | - | 1% | 9% | 40% | 50% |
34 | NATH Trisha | - | 1% | 10% | 29% | 38% | 20% | 3% |
35 | HWANG Gabriela M. | - | - | 2% | 12% | 31% | 37% | 16% |
35 | TABANGAY Heartlyn | 1% | 6% | 21% | 33% | 27% | 10% | 1% |
37 | WILLIAMS Jadeyn E. | - | - | - | 1% | 8% | 34% | 57% |
38 | HUANG Rachael | 6% | 23% | 35% | 25% | 9% | 2% | - |
39 | HILD Nisha | - | - | 4% | 20% | 43% | 33% | |
40 | SHI Julia | 1% | 8% | 24% | 34% | 24% | 8% | 1% |
41 | GHAYALOD reya | - | 2% | 9% | 25% | 36% | 23% | 5% |
42 | CHRISTOTHOULOU Olympia C. | 4% | 19% | 34% | 29% | 12% | 2% | - |
43 | KER Grace | - | 3% | 14% | 33% | 35% | 15% | |
44 | ENDO Miyuki N. | 4% | 21% | 37% | 28% | 10% | 1% | |
44 | FESTA Carina | 5% | 26% | 38% | 24% | 7% | 1% | |
46 | MARYASH Samantha | 2% | 13% | 30% | 33% | 18% | 4% | - |
47 | HAMBAZAZA Liisa | 5% | 21% | 34% | 27% | 11% | 2% | - |
48 | KHAN Alissa | 2% | 11% | 28% | 33% | 20% | 5% | - |
49 | MELNYCHUK Yelyzaveta | - | - | 1% | 8% | 29% | 45% | 17% |
50 | KONDEV Elizabeth | 5% | 21% | 35% | 28% | 10% | 1% | - |
51 | JEONG Katie | 1% | 7% | 22% | 33% | 26% | 10% | 2% |
52 | HUAI Delilah | - | 4% | 14% | 29% | 32% | 18% | 4% |
53 | CALLAHAN Chase J. | - | 1% | 8% | 25% | 37% | 25% | 4% |
54 | CARTER Keely | 15% | 36% | 32% | 14% | 3% | - | - |
55 | JOHNSON Dagny L. | - | 4% | 17% | 35% | 32% | 12% | 1% |
56 | DRAGON Rainer | - | 3% | 15% | 34% | 35% | 13% | |
57 | GORMAN Victoria M. | 1% | 7% | 25% | 37% | 25% | 6% | |
58 | CHAVAN Arya | 16% | 39% | 32% | 11% | 1% | - | |
58 | COLTER Aurora | 19% | 38% | 30% | 11% | 2% | - | |
60 | SENOGLU Irmak | 4% | 19% | 34% | 30% | 12% | 2% | - |
61 | MALEK Zolie | 6% | 23% | 36% | 25% | 9% | 1% | - |
62 | LIN Nicole | 1% | 9% | 25% | 33% | 23% | 8% | 1% |
63 | BLUM Leah I. | - | - | 3% | 14% | 32% | 36% | 16% |
63 | WANG yining | 5% | 21% | 35% | 27% | 10% | 1% | - |
65 | BOYNTON Ainsley | 3% | 18% | 34% | 29% | 13% | 3% | - |
66 | MANN Sophia J. | 8% | 32% | 39% | 18% | 3% | - | - |
67 | MANKOVA Varvara | 2% | 12% | 29% | 34% | 19% | 4% | - |
68 | ANTHONY Alexia B. | - | 2% | 10% | 25% | 34% | 23% | 6% |
69 | XU Emily T. | 13% | 33% | 33% | 17% | 5% | 1% | - |
70 | LUKER Sophia | 1% | 6% | 20% | 32% | 27% | 11% | 2% |
71 | DUCKETT Madison | - | - | 2% | 12% | 32% | 37% | 16% |
71 | WEI JoyAnn | 2% | 13% | 31% | 33% | 17% | 4% | - |
73 | YU Holly | 5% | 21% | 35% | 28% | 10% | 1% | - |
74 | WANG Elysia | 2% | 15% | 34% | 34% | 13% | 1% | |
75 | FREEDMAN Janna N. | - | 1% | 6% | 23% | 41% | 29% | |
76 | WU Helen | 1% | 10% | 28% | 36% | 21% | 5% | |
77 | ZHANG XUANYI | 1% | 7% | 24% | 36% | 25% | 6% | |
78 | MCKEE Brynnley | - | 3% | 16% | 37% | 34% | 10% | |
79 | JOHNSON Lauren | - | 4% | 19% | 35% | 29% | 11% | 1% |
80 | SHI Cathleen | - | 1% | 7% | 25% | 39% | 24% | 4% |
81 | GEYER Carolina M. | 1% | 7% | 23% | 35% | 25% | 8% | 1% |
82 | FAVO Isabella | 10% | 32% | 35% | 18% | 4% | - | - |
83 | OISHI Megumi | - | - | 1% | 6% | 23% | 42% | 29% |
84 | ATTIA Jasmine | 7% | 26% | 36% | 23% | 7% | 1% | - |
85 | MUND Ruth | 2% | 12% | 29% | 34% | 19% | 5% | - |
86 | YANG Lea | 2% | 14% | 30% | 32% | 17% | 4% | - |
87 | TAN Adelyn | 9% | 28% | 35% | 22% | 7% | 1% | - |
88 | BARNOVITZ Maya | 1% | 8% | 23% | 33% | 25% | 9% | 1% |
89 | LEE Sophia | 5% | 27% | 38% | 23% | 7% | 1% | - |
90 | NGUYEN Siena | 2% | 13% | 31% | 34% | 17% | 3% | - |
91 | FAN Grace | 17% | 38% | 31% | 12% | 2% | - | - |
92 | LU Elaine | 1% | 6% | 20% | 34% | 28% | 10% | 1% |
93 | JOHNSON Lydia | 5% | 21% | 36% | 28% | 10% | 1% | |
94 | LI YING CHU | 28% | 42% | 23% | 6% | 1% | - | |
95 | PABIAN Emilia | 9% | 32% | 37% | 18% | 4% | - | |
96 | LI Alexis | 39% | 41% | 17% | 3% | - | - | |
97 | VINOGOROVA Sofiia | 8% | 30% | 38% | 20% | 4% | - | |
98 | STAPLETON Lindsay K. | - | 5% | 19% | 34% | 30% | 11% | 1% |
98 | LI Amanda C. | - | 4% | 17% | 34% | 32% | 12% | 1% |
100 | LIM Jaslene | 3% | 18% | 34% | 30% | 12% | 2% | - |
101 | ALFARACHE Gabriella C. | 2% | 11% | 28% | 34% | 20% | 5% | 1% |
102 | ZOLLER Noelle | 16% | 36% | 31% | 14% | 3% | - | - |
103 | LIU Sydney | 2% | 13% | 29% | 32% | 18% | 5% | - |
103 | DAI Olivia | 8% | 27% | 35% | 22% | 7% | 1% | - |
105 | MARTURANO Bridget H. | - | 1% | 7% | 22% | 37% | 27% | 5% |
106 | DONG Angel | 13% | 35% | 35% | 14% | 3% | - | - |
106 | ZOU Yelin | 2% | 12% | 28% | 33% | 20% | 5% | - |
108 | TSE Angelina | 1% | 6% | 20% | 33% | 28% | 12% | 2% |
109 | ZHANG Chenfei | 6% | 23% | 35% | 26% | 9% | 1% | - |
110 | GUVEN Coco | 45% | 40% | 13% | 2% | - | - | - |
111 | LIGH Erenei J. | 4% | 21% | 38% | 29% | 9% | 1% | |
112 | SO Catelyn | 3% | 18% | 34% | 30% | 12% | 2% | |
113 | LAURI Keira | 10% | 33% | 38% | 17% | 3% | - | |
114 | LEOU Korina | 30% | 43% | 22% | 5% | - | - | |
115 | DHAR Layla | 19% | 39% | 29% | 10% | 2% | - | |
116 | RAMIREZ Mirka A. | 14% | 37% | 34% | 12% | 1% | - | |
117 | HUANG MADELINE | 6% | 27% | 39% | 23% | 6% | - | |
118 | SPEARS Mya B | 8% | 27% | 36% | 22% | 7% | 1% | - |
119 | GUGALA Hanna | 17% | 38% | 30% | 12% | 2% | - | - |
120 | SCOTT Eve | 3% | 17% | 34% | 31% | 13% | 2% | - |
121 | SAYSON Andrea | 12% | 33% | 34% | 17% | 4% | - | - |
122 | MERCHANT Aishwarya | 18% | 40% | 30% | 10% | 2% | - | - |
123 | DANTULURI Shalini | 11% | 34% | 36% | 16% | 3% | - | - |
124 | HU Anna | 8% | 33% | 39% | 17% | 3% | - | - |
125 | GOMERMAN Sophia | 10% | 30% | 34% | 19% | 6% | 1% | - |
126 | YAO Rainie | 16% | 38% | 32% | 12% | 2% | - | |
127 | MEDVINSKY Alexandra | 18% | 38% | 31% | 12% | 2% | - | - |
128 | TENG EMMA | 39% | 43% | 16% | 2% | - | - | - |
129 | NI Sharon | 3% | 20% | 37% | 28% | 10% | 2% | - |
129 | ZHANG Sophie | 14% | 35% | 33% | 15% | 3% | - | - |
129 | HU Michelle | 12% | 32% | 34% | 17% | 5% | 1% | - |
132 | ZHENG Valentina | 15% | 35% | 32% | 14% | 3% | - | - |
133 | WU Yuwei | 25% | 40% | 26% | 8% | 1% | - | - |
134 | BERNARD Kathryn | 19% | 37% | 30% | 12% | 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.