National Championships, Junior Olympic Championships & July NAC

Junior Women's Foil

Monday, July 5, 2021 at 1:30 PM

Philadelphia, PA - Philadelphia, PA, 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 RHODES Zander - - - - 1% 13% 86%
2 SHEN Sophia H. - 1% 7% 30% 44% 18%
3 KONG Chin-Yi - 1% 6% 26% 44% 23%
3 HOOSHI Erica S. - - - 4% 25% 45% 25%
5 KOO Haley B. - - - - 4% 30% 65%
6 TAN Helen - - - 1% 8% 36% 55%
7 QIAN Crystal - - 5% 23% 44% 27%
8 FERRARI Christina M. - - - 3% 15% 41% 42%
9 HE Elizabeth W. - - - - 3% 25% 72%
10 CHO Sabrina N. - - - 1% 10% 39% 50%
11 LI Phoebe J. - - 1% 14% 37% 36% 11%
12 CHUSID Mikayla - - - 4% 22% 47% 27%
13 YAROSHENKO Karina - - - 1% 8% 36% 56%
14 CONWAY Josephina (JoJo) J. - - - 4% 23% 46% 26%
15 KOO Rachel A. - - - 3% 21% 48% 27%
16 HUNG Juliana K. - - 10% 35% 40% 15%
17 ZHENG Ivy - - - 2% 17% 46% 35%
18 BREKER Anika - - - 3% 20% 46% 31%
19 ZHENG Vivian - - - 3% 19% 46% 32%
19 JING Emily - - - 1% 10% 44% 45%
21 LEE Brianna J. - - 1% 11% 36% 43% 9%
22 KIM Rachael - - 5% 25% 45% 24%
23 PARK Rowan M. - - 1% 7% 26% 43% 23%
24 JING Alexandra - - - 1% 7% 35% 57%
24 GRIFFIN Emma G. - - 3% 16% 37% 36% 8%
26 SERBAN Samantha M. - 1% 8% 29% 42% 20%
27 FLANAGAN Catherine H. - - 1% 5% 20% 42% 33%
28 LUONG Paige K. - - 3% 18% 44% 35%
29 WANG Ellen - 2% 12% 35% 40% 11%
30 OUYANG Bridgette Z. 1% 9% 32% 38% 17% 2%
31 LI Rachel Y. - 1% 13% 37% 36% 12% 1%
32 KOENIG Charlotte R. 1% 9% 34% 42% 16%
33 STAMOS Maria - - - 7% 37% 56%
34 NOVOSELTSEVA Anna V. - - 1% 11% 39% 49%
35 APELIAN Katherine - - 1% 5% 23% 43% 28%
36 GALAVOTTI Claire Teresa - - 1% 9% 33% 44% 14%
37 CHOI Lenna K. - - - 4% 25% 46% 25%
38 LEE Alina - - - 4% 19% 43% 34%
39 LUNG Katerina - - - 1% 11% 41% 47%
40 KHOO Lauren A. - 1% 9% 29% 39% 19% 2%
41 ZHANG Alina C. - - 2% 13% 38% 41% 6%
42 SEAL Grace (Gracie) C. - - 6% 27% 42% 22% 3%
43 CHUSID Renata M. - - - 2% 14% 41% 43%
44 JO Mia C. - - 3% 21% 41% 28% 6%
45 LEE Paulina - - 1% 9% 34% 47% 10%
46 REN Olivia Y. - - 2% 12% 33% 39% 15%
47 CASTANEDA Erika L. - - 3% 18% 37% 33% 9%
48 LEE Ariana - 4% 24% 41% 26% 5% -
49 CHENG Evelyn - - - - 3% 29% 68%
50 CAO Arianna L. - - 9% 34% 41% 16%
51 CHEN Jia P. - - 5% 24% 44% 26%
52 LIU Jaelyn A. 1% 11% 38% 38% 12%
53 PEVZNER Victoria - - - 3% 19% 51% 26%
54 LIAO Lu Jia (Lucy) - 2% 13% 31% 35% 17% 3%
55 CEPERO Rosabel - 3% 15% 32% 33% 15% 2%
56 ZHAO Sophie L. - 4% 21% 38% 28% 8% 1%
56 CHEN Allison V. - - 4% 38% 41% 15% 2%
58 KLINE Melissa C. - 1% 7% 24% 37% 25% 6%
59 LOCKE Savannah 1% 8% 27% 38% 21% 5% -
60 SHEN Lydia - - 1% 18% 43% 30% 7%
61 KIM Katherine - 1% 8% 28% 38% 21% 4%
62 HO Brianna W. - - 1% 6% 26% 44% 24%
63 MEI Sarah 5% 31% 40% 20% 4% - -
64 HECKMANN Emma - 2% 11% 29% 36% 19% 3%
65 LI Grace Q. - 4% 23% 45% 28%
66 JANG Kimberley - 2% 11% 31% 37% 17% 2%
67 SHAW Kayla M. - - 3% 17% 40% 34% 6%
68 CHO Gracie L. - - 8% 31% 42% 17% 2%
69 SADAN Jordan E. - 3% 14% 33% 35% 14% 1%
70 YU Lauren C. - 3% 44% 42% 10% 1%
71 LI Meilin - 7% 27% 40% 22% 4%
72 SENIC Adeline - 2% 31% 43% 21% 3%
73 EYER Hailey M. - 4% 24% 43% 24% 4%
74 LEE Allison (Allie) - - - 4% 23% 44% 29%
75 SU Michelle 1% 24% 42% 26% 7% 1% -
76 KOKES Gabrielle - - 4% 20% 39% 30% 6%
77 OH Erin H. - 2% 11% 30% 35% 18% 3%
78 SHITAMOTO Audrey F. - 6% 32% 40% 18% 3% -
79 DAVIA Daniella V. - - 4% 19% 38% 31% 7%
80 YE Eileen - 4% 21% 37% 28% 9% 1%
81 CHO Cameron S. - 1% 10% 34% 39% 15% 1%
82 DING Abigail - 1% 11% 34% 39% 14% 1%
83 FERRETTI Anna Rebecca - - 5% 25% 43% 23% 4%
84 DEBACK Greta I. - 3% 14% 32% 33% 15% 2%
84 DU Hannah - 5% 23% 39% 26% 7% 1%
84 SUN Chien-Yu 3% 17% 35% 30% 12% 2% -
87 SULEIMAN Alysa J. - 2% 20% 43% 27% 6% -
88 ACHILOVA Feyza 1% 6% 23% 36% 25% 8% 1%
89 SARTORI Taylor M. - 4% 24% 42% 25% 5%
90 KNIGHT Skylar - - 5% 24% 45% 25%
91 FREEDMAN Miranda W. - - 4% 27% 52% 17%
92 YHIP Mikaela M. 1% 11% 34% 37% 15% 2%
93 NEWHARD Zelia "Zizi" 1% 13% 40% 34% 11% 1%
94 SUN Ruoxi 5% 24% 39% 26% 6% -
95 PRIETO Sofia M. 5% 28% 41% 21% 4% -
96 BATRA Chaahat - 2% 17% 42% 31% 7% 1%
97 YEH Samantha - - 5% 26% 43% 22% 3%
98 MILLER Naomi E. - - 5% 28% 41% 22% 4%
99 RENTON Samantha 1% 8% 30% 38% 20% 4% -
100 WU Julianna Y. - 6% 25% 39% 24% 6% -
101 COSTELLO Angeline S. - 3% 18% 41% 30% 7% -
101 HALL Velma - 2% 13% 33% 36% 15% 2%
101 PAHLAVI Dahlia - 3% 20% 39% 29% 9% 1%
104 HUANG NATALIE 2% 18% 37% 30% 10% 1% -
105 GUERRA Sofia E. - 2% 12% 32% 36% 16% 2%
105 WEBB Ella 7% 30% 37% 20% 5% 1% -
107 KOSTELNY Alexis - 6% 23% 37% 27% 7% -
108 CHO Taylor S. - 5% 23% 38% 26% 7% 1%
109 ADAMS KIM Natalie - 2% 19% 41% 30% 8% 1%
110 MASSICK Laine - - 3% 16% 37% 36% 9%
111 XUE Alanna L. - 2% 12% 33% 39% 13% 1%
112 GONG Christina S. - - 8% 32% 42% 18%
113 TONG Ophelia - 1% 27% 49% 20% 2%
114 ATLURI Srija 1% 12% 40% 35% 11% 1%
115 PENG Amber L. 18% 40% 31% 10% 1% -
116 KONG Olivia - 3% 16% 35% 33% 13% 2%
117 DRAGNE Alexis D. 2% 15% 37% 33% 11% 1% -
118 PERLMAN Talia - 4% 18% 35% 32% 11% -
119 VOHRA Anusha - 4% 22% 41% 27% 5% -
120 ASCHETTINO Aurora 15% 46% 32% 7% 1% - -
121 GU EMILY 1% 13% 36% 36% 13% 2% -
122 RANDOLPH Piper 7% 31% 39% 19% 4% - -
123 TALWALKAR Apoorva 1% 10% 29% 36% 20% 4% -
124 NAMGALAURI Mariam 1% 12% 32% 35% 16% 3% -
125 MCKEE Alexandra K. 3% 22% 45% 25% 5% - -
125 KOROL Dana - 4% 21% 41% 29% 6% -
127 KOROL Neta 2% 17% 37% 31% 11% 2% -
128 DUAN Konnie - 3% 23% 39% 27% 8% 1%
129 DE LA CRUZ Eden 1% 9% 27% 35% 22% 6% 1%
130 WANG Ashley 1% 20% 42% 29% 7% 1% -
131 YU Seneca 2% 15% 36% 34% 12% 1%
132 OLIVEIRA Lavinia M. 22% 50% 24% 4% - -
133 HSIEH Rebecca 44% 52% 4% - - -
134 FERNANDES Thea - 2% 14% 41% 33% 9% 1%
135 HIRSCH Sophie A. 1% 12% 53% 28% 6% - -
136 BOLES Sophia 2% 20% 43% 28% 7% 1% -
137 HWANG Alison 1% 12% 45% 33% 9% 1% -
138 SHIH Diane 1% 9% 29% 37% 20% 4% -
139 YEH Marissa E. - 2% 14% 38% 35% 11% 1%
140 JIANG Yangying (Amanda) 1% 8% 33% 39% 17% 2% -
141 PANT Anisha 3% 21% 38% 28% 9% 1% -
142 MAESTRADO Ashley R. 2% 31% 57% 10% 1% - -
143 ZULUETA Catherine 12% 47% 32% 8% 1% - -
144 DO Leila 22% 54% 21% 3% - - -
145 CHARALEL Jessica 11% 38% 38% 11% 1% - -
146 WEINTRAUB Io H. 1% 12% 43% 34% 9% 1% -
147 CHEN Jasmine 19% 44% 30% 6% - - -
148 CUI Amy 11% 44% 34% 9% 1%
149 WU Irene M. 6% 31% 40% 19% 4% -
150 KENNEDY Elizabeth 50% 38% 10% 1% - -
151 SHUM Elizabeth 45% 42% 12% 2% - -
152 NIKOLIC Alexandra 14% 50% 29% 6% - -
153 PHILLIPS Hattie 13% 74% 12% 1% - -
154 MORADI Raiyan N. 12% 36% 34% 14% 3% - -
155 YIN Helen - 17% 40% 31% 10% 1% -
156 PAVE Claire 7% 42% 38% 12% 1% - -
157 LEE Fiona E. 29% 48% 20% 3% - - -
157 PARK Leah 60% 35% 4% - - - -
159 JENKINS Hannah G. 3% 33% 42% 19% 3% - -
160 NAM Cassie 27% 43% 23% 6% 1% - -
161 WILSON Anna S. 18% 47% 28% 7% 1% - -
161 YANG Lingting 18% 41% 29% 9% 1% - -
163 KETTELLE Molly 16% 56% 25% 3% - - -
164 ZGOMBIC Emily 22% 56% 19% 3% - - -
165 SLASKI Caroline O. 6% 60% 29% 5% - - -
165 LIPKOVITZ Rivka 9% 57% 31% 2% - - -
167 SCARLETT Skye 61% 32% 6% - - - -
168 DATLA Medha 30% 57% 12% 1% - - -
169 MEYER Claudia 20% 56% 21% 3% - - -
170 HAYES Alyssa R. 31% 43% 21% 5% 1% - -
171 CHON Sydney 16% 44% 31% 8% 1% -
172 LIU Siyuan 19% 40% 30% 10% 1% -
173 RODRIGUEZ Akemi 47% 42% 10% 1% - -
174 HSIUNG Samantha 60% 34% 6% - -
175 QIAN Zhiyan 61% 34% 5% - - -
175 YANG Liu (Willow) 48% 48% 3% - - -
177 ZARE Yasmin 67% 30% 3% - - - -
178 LEVY Avery 30% 46% 21% 3% - - -
178 FURST Chloe 47% 39% 12% 2% - - -
178 SCHMIDT Victoria 47% 41% 10% 1% - - -
181 BHAN Zala 50% 38% 11% 1% - - -
182 GIARD Paige 85% 15% - - - -
183 HUNT Abigail S. 35% 46% 16% 2% - - -
184 OETZEL Taylor 57% 39% 4% - - - -
185 ZAMELIS Madelyn 64% 32% 4% - - - -
185 WALL Sophia 57% 34% 8% 1% - - -
185 FRANCIS Annette 26% 42% 25% 7% 1% - -
188 ANTAL Chandini 55% 38% 7% - - - -
189 ROHRING Anna 70% 27% 3% - - - -
190 NARDONE Anya 82% 17% 1% - - - -
190 MOSE Anastasia E. 62% 34% 4% - - - -
192 WIERENGA Esther 93% 7% - - - - -
193 MORENO Francesca 79% 20% 1% - - - -
194 OWINGS Anna 87% 12% - - - - -

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.