December NAC

Junior Women's Épée

Saturday, December 11, 2021 at 8:00 AM

Columbus, OH, USA

Probability density of pool victories

Reset

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 PIRKOWSKI Amanda L. - - 2% 14% 42% 41%
2 HUSISIAN Hadley N. - - - - 1% 18% 81%
3 KETKAR Ketki - - - 1% 8% 37% 55%
3 JOYCE Michaela - - - 1% 18% 80%
5 PARK Faith K. - - - 1% 8% 35% 55%
6 MCCUTCHEN Lauren (Lulu) - 3% 16% 36% 32% 12% 1%
7 TYLER Syd - - 1% 7% 26% 43% 23%
8 KHROL Jaclyn - - - 2% 12% 38% 48%
9 GANDHI Sedna S. - - - 1% 10% 38% 51%
10 WANG Karen - - - 2% 12% 39% 47%
11 MAZUR Yeva - 1% 11% 35% 39% 14%
12 CHU Audrey - - 2% 12% 33% 38% 15%
13 O'DONNELL Amanda A. - - 4% 22% 45% 29%
14 ZIGALO Elizabeth - - 3% 18% 37% 32% 9%
15 NING Emma - 3% 18% 39% 31% 7%
16 NGUYEN Tallulah - 1% 8% 27% 38% 22% 4%
17 JAKEL Sophia N. - 1% 8% 24% 35% 25% 6%
18 DROVETSKY Alexandra M. - - - 3% 20% 45% 32%
19 HU Grace - - 1% 10% 33% 43% 12%
20 WATRALL Christina - - 1% 7% 25% 41% 25%
21 GU Sarah - - 1% 6% 24% 43% 27%
22 MACHULSKY Leehi - - - 2% 11% 38% 49%
23 LUO Ashley - 2% 13% 32% 35% 16% 2%
24 PATURU Meghana - - - 4% 21% 43% 31%
25 LIN Katie Y. - - 1% 8% 29% 42% 21%
26 KIM Zoe L. 1% 5% 19% 33% 28% 12% 2%
26 MILLETTE Marie Frederique - - 1% 7% 25% 43% 24%
28 WADE-CURRIE Ava S. - 2% 12% 34% 38% 15%
29 LEE Sumin - 1% 9% 29% 41% 21%
30 MAO Amy - 2% 16% 41% 37% 4%
31 FALLON Kyle R. - - 1% 6% 25% 43% 26%
32 LU Shiqi - 2% 12% 31% 35% 17% 3%
33 CHIN Isabella - - - 4% 19% 43% 34%
34 KUZNETSOV Victoria - - 1% 8% 27% 41% 23%
35 BALAKRISHNAN Monica S. - 1% 5% 18% 34% 31% 11%
36 LEE yat ching 5% 22% 35% 27% 10% 1% -
37 RAUSCH Ariana (Ari) M. - - 1% 6% 27% 45% 21%
38 MUELLER Emma M. 4% 20% 36% 29% 10% 1% -
38 CHEN Lefu - - 4% 17% 37% 33% 10%
40 DYNER Karina - 4% 19% 39% 31% 7%
41 WEISS Talia L. - 2% 14% 36% 35% 12%
41 LAVERY Chloe K. - 8% 39% 38% 13% 1%
43 GAJJALA Sharika R. - 1% 5% 17% 34% 32% 12%
44 XUAN Nicole J. - 1% 8% 28% 39% 21% 3%
45 OXENREIDER Tierna A. - - 1% 6% 21% 41% 31%
46 REID Anousheh - 3% 14% 31% 34% 16% 2%
47 DAMRATOSKI Anna Z. - 5% 18% 33% 30% 12% 1%
48 LEE Michelle J. - - 3% 14% 30% 35% 17%
48 RUNIONS Emersyn 1% 8% 23% 34% 25% 8% 1%
50 BEZUGLAYA Varvara - 5% 29% 40% 21% 4% -
51 KHAMIS Yasmine A. - - - 1% 8% 35% 56%
52 WANG Nora - 1% 6% 22% 38% 27% 6%
53 CAPELLUA Mariasole - 2% 15% 35% 33% 12% 1%
53 LEUNG Natalie - 1% 8% 25% 38% 25% 4%
55 ZHANG Tina Tianyi - - 2% 13% 35% 36% 13%
56 SHEN Stephanie 1% 6% 23% 35% 26% 8% 1%
57 SEBASTIAN Felicity A. - 1% 13% 38% 36% 11%
58 WU Amelia - 2% 14% 36% 36% 12%
59 MYLER AnneMarie - 2% 11% 32% 39% 16%
60 CHEN Zhengnan(Janet) - - 1% 10% 33% 45% 11%
61 ALEXANDROV Katherine S. - 4% 17% 33% 30% 13% 2%
62 GAO Judy - 3% 21% 40% 28% 7% 1%
63 LIN Waiyuk 1% 6% 20% 33% 28% 11% 1%
64 GUMAGAY Erika L. 4% 22% 41% 26% 7% 1%
65 KORFONTA Jolie - 1% 7% 26% 40% 24% 3%
66 DOROSHKEVICH Victoriia - - 2% 13% 37% 42% 5%
67 WEBER Nora - 5% 25% 40% 25% 5% -
68 MILEWSKI Nicole - 1% 11% 34% 38% 15% 2%
69 GEBALA Natalie Brooke A. - - 3% 15% 36% 35% 11%
70 LU Junyao 1% 9% 27% 36% 22% 5%
71 ZUHARS Renee A. - 3% 17% 34% 31% 13% 2%
72 LU Samantha R. 4% 17% 31% 29% 14% 4% -
73 LIN Jessica Y. - - - - 4% 30% 66%
73 MALLAVARPU Aarthi C. - 4% 17% 36% 33% 10% -
75 MALDONADO Pilar I. - - 3% 15% 34% 35% 13%
76 MCLANE Lauren - - 2% 10% 28% 40% 21%
77 JAKEL Alysa C. 16% 37% 31% 13% 3% - -
77 KALE Anika A. 1% 10% 26% 34% 22% 7% 1%
79 MING Cynthia 3% 17% 34% 32% 13% 2% -
80 SUN Renee R. 3% 16% 33% 31% 14% 3% -
81 ZHANG Victoria R. - 5% 19% 34% 29% 11% 2%
82 CHAN Elizabeth - 1% 12% 34% 36% 15% 2%
83 KETKAR Mallika - 1% 4% 17% 34% 32% 11%
84 XU Grace (XinYi) - 1% 8% 26% 36% 23% 5%
85 WITTE Vera 3% 15% 30% 31% 17% 5% -
86 TEMIRYAEV Anna M. - 4% 17% 33% 31% 13% 2%
86 WANG Elizabeth - - 2% 12% 34% 38% 14%
88 FAN Yun Cian - 2% 10% 26% 35% 22% 5%
89 PINNAMANENI Drithi 4% 37% 40% 15% 3% - -
90 XIAO Ruien 1% 7% 23% 34% 25% 9% 1%
91 YAO Melinda 2% 15% 38% 35% 10% -
92 MEHROTRA Anya 1% 10% 29% 36% 20% 4%
93 BEI Karen - 1% 8% 26% 40% 24%
94 LIU Christina A. - 2% 13% 36% 38% 12%
95 MUN Brianna K. 3% 20% 39% 29% 9% 1% -
96 HAFEEZ Hiba - 8% 32% 38% 18% 4% -
97 DOUGLAS Julia F. - - 4% 20% 40% 30% 6%
98 KORKIN Alice 1% 19% 42% 28% 8% 1% -
99 YOU Emily 3% 18% 35% 31% 12% 1% -
100 MYERS Jeanelle Christina A. 2% 14% 31% 32% 16% 4% -
101 WITTER Catherine A. 7% 28% 35% 22% 7% 1% -
102 YAO KATHARINE 4% 20% 37% 28% 10% 1% -
102 LONADIER Keira - 4% 17% 33% 31% 13% 2%
104 LEE Olive 1% 10% 28% 36% 20% 5% -
105 JOYAL Anne-Sophie 6% 23% 36% 25% 9% 1% -
106 WHITTEMORE Lucy K. 1% 5% 18% 33% 30% 12% 2%
107 SMOTRITSKY Mia - 5% 19% 33% 29% 12% 2%
108 REID Sobia 2% 12% 28% 33% 19% 5% 1%
109 DESAI Meera P. - - 6% 26% 40% 24% 4%
110 LEE Yedda - 7% 30% 40% 20% 4% -
111 POIRIER Ariane 5% 22% 36% 27% 9% 1%
112 SWENSON Nikita G. 10% 37% 38% 13% 2% -
113 KIM Elizabeth Y. 3% 16% 34% 32% 13% 2%
114 YIN Julia - 2% 15% 37% 34% 11% 1%
114 LEUNG Wan Kiu Hayley 2% 11% 27% 33% 21% 6% 1%
116 CALDERA Lexi I. - 1% 11% 32% 36% 17% 3%
117 AHUJA Arianna - 4% 18% 33% 31% 12% 1%
118 ANDERSON Claire 21% 38% 28% 11% 2% - -
119 ZHU Serene M. 4% 23% 37% 26% 8% 1% -
120 HAFEEZ Hania 1% 12% 34% 36% 15% 3% -
121 YU Nicole J. 1% 8% 25% 34% 23% 8% 1%
122 PADHYE Tanishka - 3% 18% 35% 30% 12% 2%
123 NEMETH Katherine 3% 17% 33% 30% 14% 3% -
124 LEE Olivia 11% 32% 35% 18% 4% - -
125 ZENG Katrina 7% 34% 39% 17% 3% - -
126 LIN Elaine 2% 15% 38% 35% 10% -
127 GUJJA Misha 31% 42% 22% 5% 1% -
128 AI Amy 23% 45% 26% 6% 1% -
129 WONG Alexandra R. 4% 19% 34% 29% 12% 2% -
129 DONDISCH Sophia - 4% 30% 40% 21% 5% -
131 FENG Kelly L. - 1% 9% 26% 37% 22% 5%
132 CHANG Ella 41% 41% 15% 3% - - -
133 SANTA MARIA Luisa F. 7% 26% 35% 23% 8% 1% -
134 TRAN Helena 2% 15% 33% 33% 14% 2% -
135 TAYLOR-CASAMAYOR Maia 4% 21% 39% 27% 8% 1%
136 CHEN Jingyun 29% 44% 22% 5% - -
137 ANDREEV Victoria 23% 45% 27% 5% - - -
138 SMUK Daria A. 1% 8% 25% 35% 23% 7% 1%
139 BAJAJ Nikita K. 15% 35% 32% 14% 3% - -
140 STOECKEL Sofia I. 13% 46% 31% 9% 1% - -
141 WU Fan - 1% 10% 30% 37% 19% 3%
141 FAN Elizabeth 12% 37% 37% 12% 2% - -
143 KIM Erika S. 6% 29% 39% 21% 5% - -
144 PORADA Yarena 25% 58% 16% 2% - - -
145 YOON Katherine 25% 40% 26% 8% 1% - -
146 KIZILBASH Zara 3% 23% 40% 25% 7% 1% -
147 NAKA Karen 9% 30% 36% 19% 4% - -
148 HONG Elaine 5% 23% 35% 25% 9% 1% -
149 LI Zhenni (Jenny) 26% 45% 24% 5% - -
150 LI Alisha 26% 44% 24% 5% - -
151 MIINEA Elena 39% 43% 16% 2% - -
152 ZHAO Ivy 37% 49% 13% 1% - -
153 LIN Ashley 24% 45% 25% 5% - -
154 PEELER Julia 9% 30% 37% 19% 4% - -
155 PARKS Eliana 38% 41% 17% 3% - - -
156 LIU Nicole 17% 37% 31% 13% 3% - -
157 ROBERTSON Lily 1% 6% 21% 35% 27% 9% 1%
158 LEE kyungmin - 1% 11% 32% 37% 17% 2%
159 POPA Catherine 19% 42% 30% 8% 1% - -
160 BARON Sabina 3% 16% 33% 32% 14% 2% -
161 WANG Angelina 44% 40% 14% 2% - - -
162 MACEY Hadley 30% 58% 11% 1% - - -
162 FABBRO Izabela 4% 24% 40% 25% 6% 1% -
164 LIANG Yuanfeng 53% 37% 9% 1% - - -
165 SCHAFF Marlene M. 5% 26% 37% 24% 7% 1% -
165 BELAOUSSOFF Kira 2% 16% 34% 32% 13% 2% -
167 SAAL Anna 8% 25% 34% 23% 9% 2% -
168 GUO Amanda 46% 42% 11% 1% - - -
169 DILLE Carolina G. 7% 49% 35% 9% 1% - -
169 GILKES Sanojah Ruby 18% 37% 30% 12% 2% - -
171 PAPADAKIS Lily - 1% 11% 35% 37% 14% 2%
172 XIE Fiona 74% 23% 3% - - - -
173 MOK Chloe R. 14% 49% 29% 7% 1% - -
173 FURMAN Maria 6% 24% 36% 25% 8% 1% -
175 NELSON-LOVE Lily B. 3% 15% 30% 31% 17% 4% -
176 KIM Jayna 6% 29% 38% 21% 6% 1% -
177 PRIHODKO Nina 9% 36% 40% 13% 2% -
178 GOLDBERG Sophie C. 9% 29% 35% 20% 6% 1% -
179 SCHULTZ Gillian 6% 27% 37% 22% 6% 1% -
179 GORNOVSKY Abigail 3% 16% 32% 31% 15% 3% -
181 LI Yuhe 2% 15% 34% 32% 14% 3% -
182 HICKS Grace 18% 43% 30% 8% 1% -
182 LAJOUX Debora 27% 45% 22% 4% - -
184 SHERTZ Kira E. 26% 41% 25% 7% 1% - -
185 DONDISCH Andrea 78% 20% 2% - - - -
186 LEWIS Rachel 55% 36% 8% 1% - - -
187 YANG Tiffany 55% 37% 8% 1% - - -
188 RAMANATHAN Eesha 61% 33% 5% - - - -
189 KUMAR Anusha 57% 37% 5% - - - -
190 NGUYEN Julia 36% 42% 18% 4% - - -

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.