National Championships, Junior Olympic Championships & July NAC

Cadet Women's Saber

Sunday, July 4, 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 MIKA Veronica - - 1% 10% 31% 41% 17%
2 TZOU Alexandra - - - 5% 32% 63%
3 KALRA Himani V. - - 3% 14% 33% 35% 14%
3 MARSEE Samantha - - - 2% 17% 44% 37%
5 SULLIVAN Siobhan R. - - - 1% 17% 81%
6 GHAYALOD reya - - 6% 25% 40% 25% 4%
7 FOUR-GARCIA Madison - - - - 4% 30% 66%
8 OISHI Megumi - - - - 5% 32% 62%
9 SHOMAN Jenna - - - 1% 14% 43% 42%
10 LEE Alexandra B. - - - 1% 8% 35% 56%
11 JOHNSON Lauren - - 1% 11% 33% 40% 15%
12 WILLIAMS Chloe C. - - - 1% 6% 32% 62%
13 CHANG Josephine S. - - - 4% 21% 44% 31%
14 GORMAN Victoria M. - - 2% 11% 35% 44% 9%
15 YONG Erika E. - - 4% 20% 43% 32%
16 KER Grace - - 2% 19% 42% 31% 5%
17 VADASZ Ibla P. - - 2% 13% 38% 39% 9%
18 SHEARER Natalie E. - 2% 16% 39% 35% 8%
19 HULSEBURG Kaitlyn - - 1% 8% 30% 42% 20%
19 OLSEN Natalie J. - 1% 7% 26% 39% 22% 4%
21 DELSOIN Chelsea C. - - - 3% 16% 41% 40%
22 ENGELMAN-SANZ Madeline A. - - 1% 5% 22% 43% 29%
23 DUCKETT Madison - 1% 9% 27% 37% 21% 4%
24 XI Shining - - 4% 18% 39% 33% 6%
25 ANDRES Katherine A. - - 3% 19% 45% 33%
26 ANDRES Charmaine G. - 2% 13% 35% 37% 12%
27 STONE Hava S. - - 3% 15% 35% 36% 12%
28 JULIEN Michelle - - 1% 7% 26% 42% 25%
29 HWANG Gabriela M. 1% 10% 28% 35% 20% 5% 1%
30 BEVACQUA Aria F. - - 7% 27% 38% 22% 5%
31 LIU Sophie 4% 21% 39% 27% 8% 1%
32 GREENBAUM Ella K. - < 1% 1% 7% 24% 42% 26%
33 TAO Hannah J. - - - 1% 11% 39% 48%
34 FREEDMAN Janna N. - - - 1% 11% 38% 49%
35 SADIK HANA - 6% 27% 41% 22% 4% -
36 WIGGERS Susan Q. - - 2% 12% 33% 38% 15%
37 MADA Skye 3% 18% 35% 30% 12% 2% -
38 CARVALHO Isabela A. - - 1% 7% 29% 43% 21%
38 MOZHAEVA MARIA - - 1% 8% 33% 43% 15%
40 FEARNS Zara A. - - 3% 17% 39% 33% 8%
41 PRIEUR Lauren - - 3% 17% 38% 35% 7%
42 TONG Kunling - - - 1% 9% 36% 54%
42 NGUYEN Ella 6% 24% 35% 25% 8% 1% -
44 MEYTIN Sophia E. 12% 35% 35% 15% 3% < 1% -
45 BARNOVITZ Maya 7% 28% 37% 22% 6% 1% -
46 WU Erica L. - 1% 9% 35% 45% 11%
47 LI Amanda C. - - 2% 14% 41% 43%
48 LU Amy - 2% 10% 27% 37% 22% 3%
49 JOHNSON Dagny L. - - 3% 21% 41% 29% 5%
49 NEWELL Alexia C. - - 3% 14% 32% 36% 15%
51 TIMOFEYEV Nicole - - - 4% 19% 43% 35%
52 HURST Kennedy - 2% 14% 32% 34% 15% 2%
53 HOLMES Emma 1% 11% 34% 35% 16% 3% -
54 BOIS Adele - - - 5% 24% 43% 26%
55 PAUL Lila - - 3% 20% 43% 29% 6%
56 NOVICK Mia J. 1% 14% 37% 33% 13% 2% -
57 ANTHONY Alexia B. 1% 6% 25% 40% 24% 5%
58 BILILIES Sophia 3% 19% 41% 29% 8% 1%
59 SPRINGER Ella 2% 18% 37% 30% 11% 2% -
60 DANK Dina - 3% 15% 32% 32% 15% 3%
61 KRASTEV Minna - 1% 5% 19% 35% 31% 10%
62 LIAO Siwen - 6% 28% 44% 20% 2%
63 FERREIRA Alejandra E. - 4% 16% 34% 32% 13% 2%
64 XIKES Katherine E. 1% 7% 27% 38% 22% 5% -
65 FANG Victoria W. - - 4% 27% 44% 23% 2%
66 POSSICK Lola P. - - - 1% 7% 35% 58%
67 SCALAMONI-GOLDSTEIN Charlotte S. - - 2% 13% 34% 37% 15%
68 YANG Ashley M. - - 3% 14% 34% 36% 13%
69 CHIOLDI Mina - - 2% 12% 31% 38% 17%
70 SZETO Chloe - - 4% 18% 37% 32% 8%
71 NATH Trisha 1% 12% 33% 34% 16% 3% -
72 SHOMAN Miriam - 1% 6% 28% 45% 20%
73 CODY Alexandra C. - - 3% 18% 40% 31% 8%
74 HILD Nisha - - 1% 10% 34% 41% 14%
74 CALLAHAN Chase J. - - 4% 18% 37% 32% 8%
76 HE Lizbeth - 3% 16% 36% 33% 12% 1%
77 KONG Carys H. - - 4% 20% 39% 29% 7%
78 BUHAY Rachel T. - - 6% 25% 39% 24% 5%
79 ENDO Miyuki N. - 1% 11% 38% 36% 13% 2%
80 CHIN Sophia J. - 5% 19% 34% 29% 11% 2%
80 SINHA Anika - - 3% 19% 41% 30% 7%
82 JOHNSON Lydia - 11% 33% 36% 17% 3% -
83 YANG Lea 2% 18% 40% 30% 9% 1% -
84 BLUM Leah I. - - - - 6% 35% 58%
85 KRYLOVA Valery 1% 6% 23% 36% 26% 8% 1%
86 SATHE Mehek S. - 4% 18% 35% 30% 11% 1%
87 CHANG Audrey 2% 13% 34% 34% 15% 3% -
88 NYSTROM Sofia C. - 4% 19% 36% 30% 10% 1%
89 LUKASHENKO Angelina - 3% 21% 42% 29% 6%
90 ULIBARRI Nevaeh L. 2% 15% 36% 34% 12% 1%
91 NEIBART Fiona 1% 8% 28% 40% 22% 1%
92 NAYAK Indra 2% 21% 44% 26% 5% -
93 ERIKSON Kira R. 1% 8% 26% 36% 23% 6% -
94 LIN Audrey J. - - 1% 11% 34% 40% 14%
95 GUTHIKONDA Sunanya 1% 21% 40% 29% 9% 1% -
95 SHI Cathleen - 4% 21% 39% 28% 8% 1%
97 LIGH Erenei J. - 4% 19% 36% 29% 10% 1%
98 SLOBODSKY Sasha L. - 1% 15% 40% 33% 10% 1%
99 KIM Marley I. - 3% 16% 35% 32% 12% 1%
99 KANTIPUDI Shrika - 5% 38% 39% 15% 2% -
101 ATLURI Sara V. - 2% 11% 29% 37% 20% 2%
101 YANG Angelina LeLe - - 6% 25% 42% 24% 3%
103 PATEL Riya 1% 8% 31% 38% 18% 4% -
104 HUANG MADELINE - 5% 28% 41% 21% 4% -
105 CHEN Xinyan - 1% 13% 34% 36% 14% 1%
106 SOURIMTO Valeria - - 5% 30% 43% 20% 2%
107 DAVIS Charlotte 23% 43% 26% 7% 1% - -
108 ZHANG Sophie 1% 12% 39% 36% 11% 1% -
109 CHIN Erika J. - - - < 1% 6% 32% 61%
109 ALFARACHE Gabriella C. 2% 16% 36% 32% 12% 2% -
111 MARYASH Samantha 5% 23% 38% 26% 8% 1% -
112 SCHIMINOVICH Sophia I. - 3% 16% 34% 32% 12% 2%
113 TONG Jessie 12% 40% 36% 11% 1% - -
114 MANSPERGER Leena - 1% 12% 33% 36% 16% 2%
115 ZINNI Kaylyn M. - 4% 20% 41% 27% 7% 1%
116 BAKER Audrey C. - 5% 26% 42% 23% 4%
117 CHAGARES Sarah M. 10% 34% 37% 16% 3% -
118 ALCEBAR Kayla - 1% 6% 21% 37% 29% 8%
119 LEE Hannah - 1% 11% 32% 37% 16% 2%
120 YUAN Greta 1% 6% 22% 36% 27% 8% 1%
121 SUBRAMANIAN Nitika - 3% 15% 35% 33% 13% 2%
122 BALAKUMARAN Maya - - 5% 20% 38% 30% 6%
123 NAYAK Mira 14% 52% 29% 5% - - -
124 FANG sophie 3% 29% 50% 16% 2% - -
125 LEMUS-IAKOVIDOU ALEXANDRA 2% 14% 33% 34% 15% 2% -
126 SHIH Christina - 8% 30% 38% 20% 4% -
127 TODD Phoebe 1% 13% 42% 34% 9% 1% -
128 JEAN Olympe G. - 4% 16% 35% 33% 10% 1%
129 HAMBAZAZA Liisa 8% 31% 38% 19% 4% - -
130 BARTON Mele 6% 28% 38% 21% 5% 1% -
131 TABANGAY Heartlyn - - 3% 19% 41% 31% 6%
132 D'ORAZIO Sofia V. 33% 46% 18% 3% - -
133 NAYAK Anika 32% 43% 21% 4% - -
134 WEI Vivian W. - 5% 27% 43% 21% 4% -
135 SHAPONA Lillian 43% 45% 11% 1% - - -
136 ALTIRS Kate 5% 29% 42% 20% 4% - -
137 LUKER Sophia 3% 15% 32% 32% 15% 3% -
138 WANG Jianning 7% 33% 39% 17% 3% - -
139 BAWA Anahat 7% 25% 36% 24% 8% 1% -
140 GOMES Diana C. 1% 14% 48% 30% 7% 1% -
141 BENOIT Adelaide L. - 3% 14% 31% 34% 15% 2%
142 CHAPMAN-LAYLAND Astrid M. - 3% 32% 41% 20% 4% -
143 WANG Zidan 8% 30% 37% 20% 5% 1% -
144 JAVERI Amaya 7% 32% 41% 17% 3% - -
144 NEELEY Leilani 45% 48% 7% - - - -
146 JOHNSTON Lily 8% 32% 37% 18% 4% - -
147 GRAFF Sophie - 3% 18% 36% 30% 11% 1%
148 MESSICK Maya 14% 51% 30% 4% - - -
149 BENTOLILA Thalia - 8% 27% 37% 22% 6% 1%
150 JUNG Irene 1% 10% 36% 38% 14% 2%
151 YAN Ava 15% 51% 27% 5% - -
152 KOLL-BRAVMANN Ryder S. 60% 34% 5% - - -
153 FREY Sarah E. 59% 34% 6% - - -
154 JENKINS Scotland 27% 44% 23% 5% - -
155 HU Michelle 11% 41% 35% 12% 2% - -
156 HENRY Soraya S. 5% 31% 41% 19% 3% - -
157 TSAI Anna A. 4% 21% 38% 27% 8% 1% -
158 CHIN Elise 12% 33% 34% 17% 4% - -
158 GEIGER Abigail 6% 40% 38% 14% 2% - -
160 ADAMS Morrigan B. 15% 38% 32% 13% 2% - -
161 HSU Mia Y. 26% 51% 20% 3% - - -
162 BOLTON Eleksi M. 8% 29% 37% 20% 5% 1% -
162 BAKER Amelia M. 12% 39% 35% 12% 2% - -
164 PADOS Anna 40% 49% 10% 1% - - -
165 KOCIS Julia 26% 49% 21% 3% - - -
166 LIN Grace 75% 23% 3% - - - -
167 PATEL Karitsa 61% 37% 2% - - - -
168 PI Sophia 39% 41% 16% 3% - - -
169 HAMILTON Ciera 39% 42% 16% 3% - - -
170 CHO Michelle 71% 26% 3% - - - -
171 BROWN Delaney 11% 45% 35% 9% 1% -
172 HUNG Anna 3% 17% 37% 33% 11% -
173 DRAEKER Margaret 25% 46% 23% 4% - -
174 TODD Peregrine 18% 41% 30% 9% 1% -
175 YAN Lena 26% 42% 24% 7% 1% - -
176 COLBY Mercer 42% 43% 14% 2% - - -
177 YEN Natalie 20% 40% 29% 10% 1% - -
178 MORAN Rhea 28% 43% 23% 6% 1% - -
179 ELNATAN Mica A. 24% 43% 26% 7% 1% - -
179 DAMDINSUREN Sophie 56% 36% 7% 1% - - -
179 DEANGELO Annabelle 46% 41% 12% 1% - - -
182 MCNALLY Teagan 38% 42% 16% 3% - - -
182 OPPY Eve 44% 44% 11% 1% - - -
184 CANDEUB Lucy 62% 34% 5% - - - -
184 GOSAVI Aabolee 93% 7% - - - - -
184 POLEN Layne 19% 37% 29% 12% 3% - -
187 CHEN Athena 57% 35% 7% 1% - - -
188 WU Selina 42% 52% 6% - - - -
188 KIM Elyssa 64% 31% 4% - - - -
190 BLUMSTEIN Alannah 32% 61% 7% - - - -
190 OPPY Mia 38% 50% 11% 1% - - -

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.