The future of US Fencing is at stake!

For transparency, fairness, and athlete support, VOTE NOW for:
(1) Maria Panyi, (2) Andrey Geva, (3) Igor Chirashnya, and (4) Sue Moheb.

October NAC

Div I Women's Épée

Sunday, October 29, 2023 at 8:00 AM

Orange County Convention Center - Orlando, FL, USA

Probability density of pool victories

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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 7 8 9 10 11 12
1 CEBULA Anne - - 4% 15% 32% 34% 14%
2 GUZZI VINCENTI Margherita A. - - - 4% 18% 42% 37%
3 NIXON Catherine (Kasia) D. - - - 1% 10% 37% 51%
3 LIU Charlene (Kai) - - - 1% 7% 38% 54%
5 HOLMES Katharine (Kat) W. - - - - 5% 31% 63%
6 TOBY Natalia R. - - 1% 8% 25% 41% 25%
7 MACHULSKY Leehi - 1% 7% 25% 40% 25% 3%
8 KUZNETSOV Victoria - - - - 1% 3% 9% 19% 27% 24% 13% 4% 1%
9 WASHINGTON Isis - - 2% 13% 42% 43%
10 GRADY Miriam A. - - 1% 5% 22% 44% 29%
11 KHAMIS Yasmine A. - - - - - - - 1% 5% 16% 31% 32% 14%
12 GU Sarah - 1% 6% 21% 37% 28% 7%
13 OXENREIDER Tierna A. - - 1% 7% 27% 43% 22%
14 LIN Jessica Y. - - - 5% 27% 50% 17%
15 JOYCE Michaela - - - 4% 22% 44% 29%
16 WATRALL Christina - 4% 16% 32% 31% 14% 2%
17 YIN Julia 1% 7% 24% 37% 25% 7% 1%
18 HUSISIAN Hadley N. - - - 2% 12% 39% 47%
19 PIRKOWSKI Amanda L. - - 2% 10% 28% 39% 21%
20 FALLON Kyle R. - 2% 12% 29% 34% 19% 4%
21 PARK Faith K. - - 1% 7% 28% 44% 21%
22 RATZLAFF Jocelyn T. - - - - 1% 5% 14% 25% 28% 19% 7% 1%
23 GANDHI Sedna S. - - - - - 1% 5% 14% 24% 27% 19% 7% 1%
24 CHIN Isabella - 1% 5% 21% 38% 29% 6%
25 ZHENG Evelyn - 1% 3% 11% 22% 27% 21% 11% 4% 1% - -
26 XIAO Ruien - 1% 6% 22% 36% 28% 8%
27 YAMANAKA Mina - - - - 1% 5% 13% 22% 25% 20% 10% 3% -
28 BARG Daniella - 2% 7% 17% 25% 25% 16% 7% 2% - - - -
29 MILLETTE Marie Frederique - - - - - 1% 5% 16% 28% 30% 16% 4%
30 SEBASTIAN Felicity A. - - - 1% 5% 13% 22% 25% 20% 10% 3% 1% -
31 BEI Karen - - - - 1% 4% 11% 21% 27% 22% 11% 3% -
32 GAJJALA Sharika R. - 3% 16% 32% 32% 14% 2%
33 ZIGALO Elizabeth - 1% 7% 24% 39% 26% 3%
34 RAKHOVSKI Alexandra - - 1% 4% 11% 21% 26% 21% 11% 4% 1% - -
35 KORFONTA Jolie - 4% 17% 33% 31% 14% 2%
36 TYLER Syd - - - - - 2% 6% 15% 26% 27% 17% 6% 1%
37 KHARCHYNA Polina 1% 12% 30% 33% 18% 5% -
38 BASSA Francesca A. - - - - 3% 24% 72%
40 VAN MARION Kirsten C. - - - 1% 4% 11% 21% 27% 23% 11% 3% -
41 WU Fan - - - 1% 3% 9% 18% 25% 23% 14% 5% 1% -
42 O'DONNELL Amanda A. - - - - 1% 4% 11% 21% 27% 21% 11% 3% -
42 LEE Michelle J. - - - - 1% 4% 12% 22% 27% 21% 10% 3% -
44 FENG Ge - 3% 11% 22% 28% 22% 11% 3% 1% - - -
45 LEE Sumin - 2% 11% 30% 37% 18% 3%
46 XUAN Nicole J. - - - 1% 3% 10% 21% 28% 23% 11% 3% -
47 KETKAR Ketki - - 1% 8% 25% 40% 26%
47 WATTANAKIT Anda 1% 6% 17% 27% 25% 15% 6% 2% - - - -
49 MUELLER Emma M. 1% 6% 17% 28% 26% 15% 6% 1% - - - -
49 WITTER Catherine A. - - 1% 4% 12% 21% 26% 21% 11% 4% 1% - -
51 RAUSCH Ariana (Ari) M. - 3% 17% 40% 33% 7%
52 SHEFFIELD Lake Mawu - - - - - 1% 3% 11% 22% 29% 23% 10% 2%
53 BECKMAN Ana - 1% 6% 15% 24% 25% 18% 8% 2% - - -
54 HU Grace - - - - - 2% 7% 18% 29% 27% 14% 3% -
55 BOUDREAU Justine - - - - 1% 3% 9% 20% 28% 24% 12% 3% -
56 LURYE Sarah - - - 1% 3% 10% 20% 26% 22% 12% 4% 1% -
57 CHU Audrey - 4% 21% 37% 28% 9% 1%
58 SPRINGER Sierra - - - 1% 4% 12% 23% 27% 20% 9% 2% - -
59 JAKEL Sophia N. - 3% 13% 29% 33% 18% 4%
60 NIXON Caroline (Karolina) L. - - - - - - 1% 3% 12% 27% 33% 19% 3%
61 CHEN Lefu - - - - 2% 9% 19% 28% 25% 12% 3% -
62 CAFASSO Natalya 1% 5% 15% 24% 25% 18% 9% 3% 1% - - - -
62 JOYAL Anne-Sophie - 3% 11% 21% 27% 22% 11% 4% 1% - - -
64 DAMRATOSKI Anna Z. - - 1% 3% 8% 18% 25% 24% 15% 6% 1% - -
65 LIN Waiyuk - - - 2% 7% 16% 25% 26% 17% 6% 1% -
66 NGUYEN Tallulah - 4% 19% 34% 29% 12% 2%
67 XIONG Angelica 3% 13% 26% 28% 19% 8% 2% - - - - -
68 WADE-CURRIE Ava S. - - - - - 3% 8% 19% 27% 25% 14% 4% -
69 YAO Yilin - 2% 10% 23% 29% 22% 11% 3% - - -
70 WANG Elizabeth - 3% 17% 39% 33% 8%
71 LEE REGINA - - - - 2% 8% 18% 27% 25% 14% 5% 1% -
72 AI Amy - 1% 5% 13% 23% 26% 19% 10% 3% 1% - - -
73 FURMAN Maria - 2% 7% 19% 27% 25% 14% 5% 1% - - - -
74 CAMPBELL Eva 10% 28% 32% 20% 8% 2% < 1% - - - - -
75 KOZLOWSKI Maya M. - 1% 6% 16% 24% 25% 17% 8% 2% - - - -
76 GUO Luxi 2% 11% 23% 28% 21% 10% 3% 1% - - - -
77 MONTOYA Kimberlee C. - - - 1% 4% 11% 21% 26% 21% 11% 3% 1% -
78 WEBER Nora - 1% 4% 12% 23% 27% 21% 10% 3% 1% - -
79 AICARDI GONZALEZ Alessandra Valeria - 3% 9% 20% 26% 22% 13% 5% 1% - - - -
80 YANG Alisa - - 1% 4% 11% 23% 28% 21% 9% 2% - -
81 WANG Karen - 3% 15% 32% 33% 15% 2%
82 GAO Judy - 1% 6% 17% 26% 26% 16% 6% 2% - - - -
83 TOLSMA Chloe (CJ) - - 2% 8% 19% 28% 25% 14% 4% 1% -
84 PORADA Yarena 11% 28% 31% 19% 8% 2% - - - - - -
85 KETKAR Mallika - - - - 1% 5% 13% 23% 27% 19% 8% 2% -
86 LORD Sarah-Eve 1% 7% 18% 27% 24% 15% 6% 2% - - - -
86 PROFIS Liora 1% 5% 15% 26% 27% 17% 7% 2% - - - - -
88 YAO Melinda - 2% 8% 19% 26% 24% 14% 6% 1% - - -
89 NGUYEN Kira - - - - 1% 5% 15% 27% 28% 17% 6% 1% -
90 CARRIER Meredith - 1% 7% 20% 30% 25% 12% 4% 1% - - -
91 CHERNIS Zoe C. 1% 6% 19% 29% 25% 13% 4% 1% - - - - -
92 SHIV Avni - 2% 8% 19% 26% 24% 14% 6% 1% - - - -
93 GORNOVSKY Abigail - 1% 7% 17% 26% 25% 15% 6% 2% - - - -
94 PRIHODKO Nina - 1% 4% 13% 24% 27% 19% 9% 3% - - - -
95 CHEN Jingyun 5% 19% 31% 26% 13% 4% 1% - - - - - -
96 LIN Elaine - - 3% 9% 18% 25% 23% 14% 5% 1% - -
97 WANG Zoe - 3% 11% 23% 28% 21% 10% 3% 1% - - - -
98 PINNAMANENI Drithi 3% 15% 28% 28% 17% 7% 2% - - - - -
99 SMUK Alexandra S. - 5% 21% 35% 28% 10% 1%
100 IYER Ishana 12% 39% 37% 11% 1% -
101 SWENSON Nikita G. 1% 6% 22% 35% 26% 9% 1%
102 PEHLIVANI Zara - 2% 10% 28% 36% 21% 4%
103 KOWALSKY Rachel A. - - 2% 11% 30% 39% 19%
104 EDWARDS Auprell 1% 10% 29% 36% 20% 4%
105 SMOTRITSKY Mia - 2% 13% 32% 37% 16%
106 QI Jarynne Valerie 2% 15% 32% 33% 15% 3%
107 HONG Elaine 1% 8% 26% 35% 23% 7% 1%
108 BEZUGLAYA Varvara - 5% 18% 33% 30% 12% 1%
109 ZHANG Victoria R. - 1% 6% 21% 37% 29% 7%
109 LEE yat ching 2% 13% 30% 33% 17% 4% -
111 HEPLER Sarah 1% 8% 22% 32% 25% 10% 2%
111 CAPELLUA Mariasole - - 3% 14% 34% 37% 12%
113 LEE Claire 3% 16% 33% 31% 14% 3% -
114 CALDERA Lexi I. - 4% 17% 33% 31% 13% 2%
114 PADHYE Tanishka - 2% 13% 30% 34% 18% 3%
116 MISHIMA Audrey 20% 40% 29% 10% 2% - -
117 STERR Isabella M. 9% 28% 34% 21% 7% 1% -
118 YOU Emily 2% 13% 29% 32% 18% 5% -
118 LIU Baihan 4% 23% 37% 26% 8% 1% -
120 AZMEH nour 6% 33% 38% 18% 4% 1% -
121 CHENG Ava 1% 6% 21% 34% 27% 10% 1%
122 WANG Jessie 15% 35% 32% 15% 3% -
123 DOROSHKEVICH Victoria - 3% 13% 32% 36% 16%
124 ELSTON Sophia 9% 30% 36% 19% 5% -
125 SENYUVA Su 11% 32% 34% 17% 4% -
126 LUO Ashley - 1% 7% 27% 44% 20%
127 SEMIKIN Julia 1% 7% 23% 36% 27% 7%
128 SONG Angela - 3% 14% 32% 35% 16% 1%
129 SUN Hanya 11% 31% 33% 19% 6% 1% -
130 ANDERSON Claire 6% 23% 35% 26% 10% 2% -
131 FORNARIS Susana - - - 4% 23% 44% 28%
132 CHISHOLM Phoebe C. 1% 5% 20% 34% 28% 11% 1%
133 RICHARDSON Meredith 11% 32% 35% 18% 4% - -
134 LIANG Jingjing 19% 39% 29% 10% 2% - -
135 XU Grace (XinYi) - - 3% 14% 32% 35% 15%
136 KIM Zoe L. - 1% 6% 21% 36% 29% 9%
137 NOVOJILOV Anastasia 14% 35% 33% 15% 3% - -
138 POTAPENKO Margarita D. 1% 13% 34% 36% 14% 2% -
138 LEE Olive 2% 11% 27% 32% 21% 7% 1%
140 WELLS Tesla M. 1% 7% 23% 36% 25% 8% 1%
140 LI Zhenni (Jenny) 5% 25% 40% 24% 6% 1% -
142 LU Samantha R. 1% 10% 27% 35% 21% 5% -
143 SU Evelyn 4% 21% 36% 28% 10% 2% -
143 SHANKERDAS Shreeya 21% 43% 28% 8% 1% - -
145 BROWN Hannah 8% 33% 36% 18% 4% - -
146 SYKES Elynor 2% 12% 30% 34% 18% 4% -
147 MEHROTRA Anya - - 1% 8% 25% 40% 25%
147 HSIU Elizabeth 2% 15% 35% 33% 13% 2% -
149 PULLEN Ayah 12% 32% 34% 18% 4% 1% -
150 NGUYEN Audrey 2% 17% 36% 31% 12% 2%
151 BUSH emma 3% 17% 37% 32% 10% 1%
152 HAMILTON Pauline S. - 1% 6% 23% 42% 28%
153 BALAKRISHNAN Trisha 30% 42% 22% 5% 1% -
154 KIM Jayna 8% 28% 37% 21% 5% 1%
155 RUNIONS Emersyn - 3% 13% 28% 32% 19% 5%
156 HAFEEZ Hania - 2% 9% 24% 35% 24% 6%
157 XIAO Nancy 1% 10% 30% 37% 18% 3% -
158 DORVAL Anne-Marie - 1% 8% 24% 36% 25% 7%
159 JAKEL Alysa C. 3% 15% 31% 31% 16% 4% -
160 REID Sobia 1% 8% 28% 36% 21% 6% 1%
161 TEMIRYAEV Anna M. - 1% 7% 23% 36% 26% 7%
162 NING Emma - - 2% 18% 53% 26%
163 LI Fei 1% 8% 23% 32% 25% 10% 2%
164 HAFEEZ Hiba 6% 24% 35% 25% 8% 1% -
165 WANG Victoria 16% 35% 31% 14% 3% - -
166 MILEWSKI Nicole - 2% 10% 27% 35% 21% 4%
167 KORKIN Alice 3% 16% 33% 31% 14% 2% -
167 CANNING Charlotte 1% 10% 26% 33% 22% 7% 1%
169 WANG Ziqi (yoyo) - 3% 15% 32% 34% 15% 1%
170 LIU Christina A. - 1% 5% 20% 36% 30% 9%
170 SCHMITT Harper 18% 39% 30% 11% 2% - -
172 MUN Brianna K. 8% 26% 34% 22% 8% 1% -
173 KUMAR Anusha 8% 28% 35% 21% 6% 1% -
173 RODRÍGUEZ Abigaíl 7% 30% 37% 20% 6% 1% -
175 WANG Angelina 7% 26% 35% 23% 8% 1% -
176 DESAI Meera P. 1% 8% 23% 32% 24% 9% 1%
177 NIX Reagan 3% 15% 32% 31% 15% 3% -
178 SMUK Daria A. 4% 19% 34% 29% 12% 2%
178 SHU Youshan 4% 23% 38% 26% 8% 1%
180 GUJJA Misha 9% 28% 36% 21% 6% 1%
181 REID Anousheh 4% 18% 35% 30% 12% 2%
181 SHELIN Chelsea 15% 35% 33% 14% 3% -
183 LEE Natasha - 4% 17% 34% 33% 12%
184 NEMETH Katherine 2% 14% 31% 33% 16% 3%
185 PECK Maia A. 3% 16% 33% 31% 14% 2%
186 YU Nicole J. - 4% 19% 36% 31% 9%
187 SEREGIN Katya 39% 42% 16% 2% - - -
188 ZHU Serene M. 6% 25% 37% 24% 7% 1% -
188 YAO KATHARINE 5% 22% 35% 27% 10% 2% -
190 SAYAGUES Isabella 48% 38% 12% 2% - - -
191 DUMAS Marie 11% 33% 35% 17% 4% - -
192 PHUKAN Indra 8% 32% 39% 18% 3% - -
193 BASRALIAN Azniv 8% 34% 41% 15% 2% -
194 WONG Alexandra R. 1% 7% 25% 36% 24% 7% 1%
194 LEE Olivia - 4% 16% 30% 31% 16% 3%
196 DEPOMMIER Isabelle 14% 35% 32% 14% 3% - -
197 LEWIS Rachel 29% 41% 23% 6% 1% - -
198 MONOVA Lilyana 65% 30% 5% - - - -
199 UNGURIANU Nika 43% 40% 14% 2% - - -
200 REKEDA Anna 44% 40% 14% 2% - - -
201 LEE Camilla 13% 34% 33% 15% 4% - -
202 BOTNER Olivia 5% 21% 33% 27% 11% 2% -
203 CHUANG Ramona 57% 34% 8% 1% - -
204 WALLER DEL VALLE Alexandra 40% 43% 15% 2% - -
205 SUN Renee R. 7% 28% 39% 22% 5% -
205 FERREIRA DE MELO Adriana 10% 33% 36% 17% 4% -
207 WALLER DEL VALLE Andrea 22% 42% 27% 8% 1% - -
208 DONGES Anna 16% 36% 32% 13% 3% - -

Explanation

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.