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November NAC

Junior Women's Épée

Monday, November 13, 2023 at 8:00 AM

Fort Worth Convention Center - Fort Worth, TX, 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
1 OXENREIDER Tierna A. - - - - 4% 28% 68%
2 GU Sarah - - - 1% 6% 31% 63%
3 KHAMIS Yasmine A. - - - - 6% 32% 61%
3 GAJJALA Sharika R. - - - 1% 7% 35% 57%
5 MEHROTRA Anya - - 1% 6% 22% 41% 30%
6 DAMRATOSKI Anna Z. - 1% 6% 21% 37% 29% 6%
7 DOROSHKEVICH Victoria - - 1% 7% 26% 42% 24%
8 PROFIS Liora 1% 10% 29% 38% 19% 3%
9 HONG Elaine - - 3% 19% 40% 30% 8%
10 CHIN Isabella - - - - 2% 23% 75%
11 MACHULSKY Leehi - - - - 4% 28% 67%
12 TYLER Syd - - - 6% 35% 59%
13 GANDHI Sedna S. - - - 1% 9% 36% 54%
14 PEHLIVANI Zara - - 1% 6% 27% 47% 20%
15 PADHYE Tanishka - - 2% 16% 38% 34% 9%
16 BEZUGLAYA Varvara - 5% 22% 40% 28% 5%
17 SEBASTIAN Felicity A. - - - 2% 13% 40% 45%
18 JOYCE Michaela - - - 1% 18% 80%
19 JAKEL Sophia N. - - - 1% 7% 33% 59%
20 FALLON Kyle R. - - - - 6% 34% 60%
21 YOUNG VIVIAN - 4% 21% 40% 28% 7% -
22 LEE REGINA - - 1% 7% 27% 42% 23%
23 WANG Elizabeth - - - - 5% 30% 65%
24 POTAPENKO Margarita D. - - 3% 15% 39% 35% 7%
25 FENG Ge - 1% 10% 31% 37% 18% 3%
26 WANG Karen - - - 2% 14% 43% 41%
27 SONG Angela - 1% 9% 25% 36% 23% 5%
28 GEBALA Natalie Brooke A. - - - 4% 19% 43% 34%
29 CHEN Zhengnan(Janet) - - - 3% 20% 47% 31%
30 LUO Ashley - - - 3% 15% 41% 41%
31 BUSH emma - 3% 15% 33% 33% 14% 1%
32 ZHANG Yixuan 1% 6% 21% 35% 27% 9% 1%
33 YIN Julia - - - 4% 21% 44% 31%
34 YU Nicole J. - - 1% 7% 26% 42% 24%
35 KETKAR Ketki - - - - 1% 17% 81%
35 ZIGALO Elizabeth - - - 1% 9% 40% 50%
37 RAKHOVSKI Alexandra - - 1% 9% 32% 46% 12%
38 ZHANG Victoria R. - - - 4% 19% 43% 34%
39 BARG Daniella - 2% 18% 42% 32% 6%
40 WADE-CURRIE Ava S. - - - 3% 21% 47% 29%
41 LIN Elaine - 1% 8% 29% 42% 19% 3%
42 LEE Sumin - - - 2% 12% 39% 47%
42 NGUYEN Tallulah - - 1% 6% 23% 43% 28%
42 AI Amy - - 5% 20% 37% 30% 8%
45 REID Anousheh - - 2% 14% 34% 36% 13%
46 LIANG Jingjing 1% 12% 32% 34% 16% 3% -
47 PARK Faith K. - - - - 5% 31% 64%
48 TOLSMA Chloe (CJ) - - 3% 16% 37% 34% 10%
49 KIM Zoe L. - - - 5% 24% 44% 27%
50 LEE Olivia - 3% 16% 36% 35% 10%
51 YANG Alisa - 3% 15% 33% 35% 14%
52 RUNIONS Emersyn 1% 7% 28% 40% 22% 3%
53 HAFEEZ Hania - - 5% 22% 40% 28% 5%
54 LIU Christina A. - - 4% 18% 40% 35% 3%
55 POHREBNA Yeva - 1% 9% 29% 37% 19% 3%
56 KHARCHYNA Polina - - 1% 7% 26% 42% 24%
57 KIM Elizabeth Y. - - 1% 12% 34% 39% 14%
58 SMUK Alexandra S. - 1% 9% 30% 37% 19% 4%
59 LI Olivia 2% 15% 33% 32% 15% 3% -
60 PINNAMANENI Drithi 1% 7% 25% 37% 23% 6% 1%
61 CAPELLUA Mariasole - - 3% 18% 42% 36%
62 ELSTON Sophia - 1% 9% 27% 37% 22% 4%
63 AZMEH nour - 4% 18% 34% 31% 12% 1%
64 MUELLER Emma M. 1% 11% 28% 35% 20% 4%
65 PECK Maia A. - - 3% 18% 40% 33% 5%
66 KORFONTA Jolie - - - 1% 6% 33% 60%
67 ZHU Chenxi (Heidi) - - 1% 12% 39% 48%
68 DESAI Meera P. 1% 6% 22% 36% 27% 8%
69 CHI Chelsea - 4% 20% 38% 30% 8% < 1%
70 JOYAL Anne-Sophie - 1% 9% 27% 37% 22% 3%
71 NGUYEN Kira - - 3% 15% 35% 35% 12%
72 CAFASSO Natalya - 1% 5% 20% 38% 30% 6%
73 XIAO Nancy 2% 13% 31% 34% 17% 4% -
74 LEE Scarlett - - 6% 31% 49% 14%
75 CHEN Lefu - 1% 5% 22% 43% 30%
76 XUAN Nicole J. - - 1% 10% 39% 50%
77 LEWIS Rachel 22% 41% 28% 8% 1% -
78 DAHER Yasmine - 7% 31% 38% 19% 4% -
79 CHISHOLM Phoebe C. - 2% 12% 33% 37% 14% 2%
79 GAO Judy - 2% 14% 34% 34% 14% 2%
81 PHUKAN Indra 1% 11% 32% 37% 16% 2% -
82 SWENSON Nikita G. - 1% 9% 29% 40% 18% 2%
83 SMOTRITSKY Mia - - 2% 13% 33% 38% 14%
84 NEMETH Katherine - 1% 9% 29% 38% 20% 4%
85 KETKAR Mallika - - 1% 10% 30% 42% 17%
86 TEMIRYAEV Anna M. - - 2% 12% 36% 38% 12%
87 SMUK Daria A. - - 5% 22% 42% 27% 4%
88 SEMIKIN Julia - - 2% 12% 37% 41% 8%
89 YAO Melinda - - 4% 18% 37% 32% 9%
90 NELSON-LOVE Lily B. - 4% 18% 34% 31% 12% 1%
91 SUN Renee R. - 3% 16% 36% 33% 11% 1%
92 YOU Emily - 1% 9% 30% 39% 19% 2%
93 WONG Alexandra R. - 6% 25% 39% 24% 5% -
94 CHERNIS Zoe C. 1% 8% 27% 36% 22% 6% 1%
95 ZHEREBCHEVSKA Veronika 2% 14% 36% 34% 13% 1%
96 DUBEAU Alexa 8% 35% 39% 16% 2% -
97 WANG Jessie - 5% 27% 46% 20% 2%
98 LISCUM Vivian 28% 42% 23% 6% 1% -
99 LAN Alice S. - 2% 12% 33% 39% 15%
100 ZHU Serene M. 1% 8% 25% 36% 24% 6% -
101 YILMAZ Pinar 1% 6% 23% 38% 26% 6% -
102 SMOTRITSKY Liat 6% 27% 38% 23% 6% 1% -
103 PRESMAN Aerin 3% 21% 38% 28% 9% 1% -
104 KUMAR Eva - 4% 17% 34% 32% 11% 1%
105 SHIV Avni - 3% 14% 32% 34% 15% 2%
106 SPRINGER Sierra - - 4% 21% 42% 29% 4%
107 NEELAM Navya 2% 19% 37% 29% 10% 2% -
108 KIM Jayna 1% 7% 26% 38% 24% 5% -
108 MISHIMA Audrey 5% 24% 38% 25% 8% 1% -
110 EDWARDS Auprell - 1% 10% 30% 37% 19% 3%
111 CALDERA Lexi I. - 1% 8% 28% 39% 21% 3%
112 CHA Eugenie 1% 8% 27% 38% 22% 5% -
113 GUO Luxi 1% 7% 23% 36% 26% 8% 1%
114 SU Evelyn 1% 8% 26% 36% 23% 6% -
115 MUN Brianna K. - 5% 23% 41% 25% 6% -
116 LEE Camilla 1% 7% 28% 37% 21% 5% -
117 HAUSHEER Kuncen 17% 39% 31% 11% 2% - -
118 TRAN Helena 2% 20% 46% 27% 5% -
119 SUN Hanya 26% 41% 25% 7% 1% -
120 CARRIER Meredith - 1% 9% 27% 37% 21% 4%
121 ZANGA Kaitlyn - 4% 18% 35% 31% 11% 1%
122 PRIHODKO Nina - 6% 23% 36% 26% 8% 1%
122 SUICO Kyubi Emmanuelle 7% 35% 39% 17% 3% - -
124 SCHMITT Harper 2% 18% 39% 30% 10% 1% -
125 LIN Victoria T. 10% 33% 36% 17% 3% - -
126 SHU Youshan - 7% 29% 38% 21% 4% -
127 QI Jarynne Valerie - 3% 16% 33% 33% 14% 1%
128 YAO Yilin - 3% 21% 42% 29% 5%
129 LIU Baihan 1% 8% 26% 37% 23% 6% -
130 LIU Nicole - 5% 21% 39% 28% 7% -
131 LEE Claire - 3% 16% 35% 33% 11% 1%
132 SCHERK Veronica 9% 36% 38% 14% 2% - -
133 KOZLOWSKI Maya M. - 1% 5% 20% 38% 29% 7%
134 AIRES Julia 5% 25% 37% 25% 8% 1% -
135 WANG Zoe - 6% 33% 41% 17% 2%
136 WATTANAKIT Anda 1% 13% 37% 37% 11% -
137 XIONG Angelica 4% 19% 37% 29% 10% 1%
138 SYKES Elynor - 1% 10% 31% 39% 17% 2%
139 BALAKRISHNAN Trisha 1% 10% 30% 37% 19% 3% -
140 KORKIN Alice 1% 8% 30% 40% 19% 3% -
141 WANG Ziqi (yoyo) - 2% 12% 30% 34% 18% 3%
142 HAFEEZ Hiba 1% 8% 27% 37% 22% 4% -
143 MALLAVARPU saanvi 1% 7% 23% 35% 26% 8% 1%
144 REID Sobia - - 2% 14% 36% 39% 8%
145 ALEXANDROV Katherine S. - - 1% 9% 31% 44% 15%
146 BECKMAN Ana - - 4% 17% 36% 33% 9%
146 LI Fei - 1% 10% 31% 38% 18% 1%
148 TANG Elaine 25% 46% 24% 5% - - -
149 DALEY Keira 9% 34% 37% 17% 3% - -
150 FAN Elizabeth 1% 17% 41% 30% 9% 1% -
151 WALLER DEL VALLE Alexandra 7% 32% 41% 16% 3% - -
152 DEPOMMIER Isabelle 4% 23% 37% 26% 9% 1% -
152 LI Zhenni (Jenny) - 5% 22% 36% 27% 9% 1%
154 SENYUVA Su 2% 12% 31% 34% 18% 4% -
154 ENRILE Erica 3% 18% 35% 30% 12% 2% -
156 MARTYNOVA Diana 1% 11% 29% 34% 19% 5% -
157 CHANG Celine A. - 6% 24% 37% 25% 7% 1%
158 LIN Ariel 2% 16% 35% 32% 12% 2% -
159 WITTER Catherine A. - - 6% 25% 42% 25% 3%
160 CAMAMA Tessa 3% 19% 42% 28% 8% 1% -
161 CHUNG Penelope 10% 48% 33% 8% 1% - -
162 SOBUS Yanka 6% 25% 38% 24% 7% 1%
163 LEE Natasha - 2% 15% 41% 39% 4%
164 RANDLEMAN Teresa 2% 15% 33% 32% 15% 3%
165 ORTEGA Ivanna S. - - 2% 12% 33% 38% 15%
166 LU Samantha R. - 5% 19% 35% 30% 10% 1%
166 ZHAO Alina 9% 28% 35% 21% 6% 1% -
168 VAN VACTER Madelynn 4% 20% 38% 29% 9% 1% -
169 SCANLAN Claire 17% 38% 31% 12% 2% - -
170 GUAN Isabella 12% 35% 34% 16% 3% - -
171 NAKA Emily 3% 18% 35% 30% 12% 2% -
172 KOVALCHUK Erika S. 10% 37% 36% 15% 3% - -
172 REKEDA Anna 5% 41% 39% 13% 2% - -
174 CHIRASHNYA Mika 31% 42% 21% 5% 1% - -
175 KALGAONKAR Arohi 20% 41% 29% 9% 1% - -
176 XU Celina 9% 32% 38% 18% 3% - -
177 PEARSON Heila 1% 10% 29% 34% 20% 5% 1%
178 MOLLINIER Angel 9% 32% 37% 18% 4% - -
179 TANG Ellen 35% 43% 18% 3% - - -
180 PULLEN Ayah 2% 19% 40% 29% 9% 1% -
180 SHELIN Chelsea - 5% 20% 35% 29% 10% 1%
182 YOU Isabel B. 10% 40% 36% 12% 2% - -
183 BARG Margaret 11% 34% 36% 16% 3% -
184 CHEN Alicia 24% 54% 19% 2% - -
185 KENT Elizabeth J. 2% 19% 40% 30% 8% -
185 LIN Isabel 53% 37% 9% 1% - -
187 MCKENNA Analise 55% 39% 6% - - -
188 STERR Isabella M. 10% 37% 36% 14% 2% -
189 GAN Shelby 55% 37% 7% - - -
190 PULLARA Ashley 7% 26% 36% 23% 7% 1% -
190 CHANG Chloe 21% 43% 28% 8% 1% - -
192 MONOVA Lilyana 5% 29% 39% 21% 5% 1% -
193 WALLER DEL VALLE Alanis 2% 15% 33% 33% 15% 3% -
194 ANDERSON Claire - 5% 21% 38% 29% 7% -
195 WANG Sophie Y. 19% 45% 29% 6% 1% - -
196 WANG Ziqiao (Claire) 6% 26% 39% 23% 5% - -
197 LAI Amanda 7% 39% 37% 14% 2% - -
198 NIX Reagan 2% 17% 35% 31% 13% 3% -
199 ILYAS Ayah 21% 47% 27% 5% - - -
200 WANG Angelina 4% 20% 37% 29% 9% 1% -
201 WANG Victoria 10% 33% 35% 17% 4% - -
202 FURMAN Maria - 4% 21% 39% 28% 8% 1%
203 MYRAH Vivienne 1% 12% 33% 36% 15% 2% -
203 PANG Ashley 50% 39% 10% 1% - - -
205 HSIU Elizabeth 2% 18% 40% 30% 8% 1% -
206 PEELER Julia 1% 9% 28% 36% 21% 5% -
207 JAKEL Alysa C. - 2% 14% 38% 34% 12% 1%
208 YUMIACO Nylah 32% 45% 19% 3% - - -
209 VARAN Kateryna 18% 42% 30% 9% 1% - -
209 BASRALIAN Azniv 3% 19% 41% 29% 8% 1% -
211 FREEMAN Kit 12% 42% 34% 11% 2% - -
211 MCQUEEN Morgan 12% 43% 33% 10% 1% - -
211 LEE Yeriel 35% 43% 19% 4% - - -
214 ZHENG Linden 6% 26% 39% 23% 6% - -
214 CHANG chaehee 55% 37% 8% 1% - - -
216 JIN Zhengtian 25% 42% 25% 7% 1% - -
217 SHARMA Sanvi 8% 31% 38% 19% 4% - -
218 LI Yunxuan (Joy) 31% 44% 21% 4% - - -
219 BHATT Anisha 26% 42% 24% 7% 1% - -
220 MIHILL Margaret 35% 43% 19% 4% - - -
220 HERNANDEZ-CHENG Isabel 56% 34% 8% 1% - - -
222 TANG RUIRUI 4% 22% 40% 26% 7% 1% -
223 AWALEGAONKAR Saina 54% 37% 8% 1% - - -
224 CAMPBELL Eva 7% 28% 38% 21% 5% -
225 BEAVER Ava 4% 22% 38% 27% 8% 1%
226 NELSON Grace E. 28% 43% 24% 6% 1% - -
226 NGUYEN Ella 37% 43% 17% 3% - - -
228 KANASKAR Ila 13% 35% 34% 15% 3% - -
229 ZHANG Helen 61% 33% 6% - - - -
230 CHUANG Ramona 48% 39% 11% 1% - -
231 HESS Heidi J. 5% 23% 36% 26% 9% 1%
232 YAO KATHARINE 5% 24% 40% 25% 6% 1% -
233 HOAGLAND Sally 40% 44% 14% 2% - - -
233 LI Clara 58% 34% 7% 1% - - -
235 YOUSSEF Caroline 67% 29% 4% - - - -
236 BAWA Jenya 36% 41% 18% 4% - - -
236 SUN Joanna 71% 27% 3% - - - -
238 WALLER DEL VALLE Andrea 16% 49% 29% 6% - -
239 LOZIER Grace 54% 36% 9% 1% - - -
240 MOORADIAN Anya 41% 41% 15% 3% - - -
241 ROSENBERG India 12% 36% 35% 14% 3% - -
242 MARTIN Adriana 38% 42% 17% 3% - - -
242 LEE Claudia 78% 21% 2% - - - -
244 CHANG Abigail 33% 46% 18% 3% - - -
245 BARDIN Kira 43% 41% 14% 2% - - -

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.