June NAC

Junior Women's Saber

Monday, June 7, 2021 at 8:45 AM

, - Richmond, VA, 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 SKARBONKIEWICZ Magda - - - - 4% 29% 67%
2 LEE Alexandra B. - 1% 7% 26% 43% 24%
3 SULLIVAN Siobhan R. - - - 4% 19% 43% 34%
3 KONG Vera - - - 1% 11% 40% 47%
5 OISHI Megumi - - - 3% 16% 42% 39%
6 PAK Kaitlyn - - 3% 16% 41% 40%
7 GREENBAUM Atara R. - - 4% 19% 43% 35%
8 SHEALY Maggie - - 3% 15% 36% 35% 11%
9 KOVACS Sophia - - 1% 9% 28% 40% 22%
10 LU Vivian Y. - - 1% 7% 25% 42% 25%
11 KIM Zoe - - 2% 15% 42% 40%
12 STRZALKOWSKI Aleksandra (Ola) M. - - - 3% 14% 40% 43%
13 TIMOFEYEV Nicole - - 3% 18% 37% 32% 10%
14 SHOMAN Jenna - - 2% 17% 50% 31%
15 TZOU Alexandra - 1% 9% 30% 41% 19%
16 GREENBAUM Ella K. - 4% 19% 38% 31% 8%
17 AVAKIAN Mikaela - - - 1% 9% 37% 54%
18 ENGELMAN Madeline A. - 1% 9% 28% 36% 21% 5%
19 TUCKER Iman R. - - 7% 28% 41% 20% 3%
20 LUKASHENKO Angelina - 2% 22% 42% 27% 7% 1%
21 DELSOIN Chelsea C. - 1% 8% 26% 41% 24%
22 NAZLYMOV Tatiana F. - 2% 11% 31% 39% 16%
23 ANDRES Katherine A. - 4% 18% 37% 33% 9%
24 BLUM Leah I. - 4% 16% 34% 34% 13%
25 TONG Kunling - 2% 12% 33% 39% 14%
26 KALRA Himani V. - 1% 12% 33% 36% 16% 2%
27 BROWN Emma - 1% 6% 25% 38% 24% 5%
28 CAO Stephanie X. - - 2% 13% 37% 40% 8%
29 SHEARER Natalie E. 7% 26% 36% 23% 7% 1%
30 CHANG Josephine S. - - 2% 15% 38% 35% 9%
31 CALLAHAN Chase J. - 4% 17% 34% 32% 12% 2%
32 MIKA Veronica - 1% 8% 26% 37% 23% 5%
33 LI Amanda C. - - 2% 13% 35% 38% 11%
34 SZETO Chloe - 1% 9% 26% 36% 22% 5%
35 WILLIAMS Jadeyn E. - - - 1% 11% 40% 47%
36 FREEDMAN Janna N. - - 3% 14% 33% 35% 14%
37 FOUR-GARCIA Madison - - 4% 19% 43% 34%
38 XI Shining 1% 12% 32% 35% 17% 3%
39 HARRISON Imogen N. - 1% 7% 25% 42% 25%
40 SHOMAN Miriam 1% 10% 29% 37% 19% 3%
41 BUHAY Rachel T. - 2% 15% 37% 33% 11% 1%
42 DANK Dina 4% 19% 33% 28% 12% 2% -
43 HULSEBURG Kaitlyn - 1% 7% 26% 38% 24% 5%
44 NEWELL Alexia C. - 2% 10% 28% 36% 20% 4%
45 SECK Chejsa-Kaili F. - - 1% 8% 30% 44% 18%
46 GORMAN Victoria M. 2% 14% 35% 34% 13% 2%
47 TAO Hannah J. - 3% 17% 38% 33% 9%
48 GUTHIKONDA Nithya - 2% 12% 31% 37% 17%
49 GHAYALOD reya 5% 26% 39% 23% 6% -
50 HILD Nisha - 5% 22% 38% 27% 7% 1%
51 WILLIAMS Chloe C. - - - 3% 18% 44% 34%
52 YUN Maya - 1% 8% 28% 38% 21% 4%
53 CHANG Emily 1% 10% 31% 35% 18% 4% -
54 JULIEN Michelle - 1% 8% 23% 36% 26% 5%
55 SATHYANATH Kailing - - 5% 21% 36% 28% 8%
56 ENDO Miyuki N. 3% 16% 32% 31% 15% 3% -
57 WEINBERG Alexandra L. - - 3% 16% 38% 36% 8%
58 LIGH Erenei J. 2% 17% 36% 32% 12% 2% -
59 SUBRAMANIAN Nitika 1% 11% 31% 35% 18% 3%
60 FEARNS Zara A. 1% 7% 29% 45% 17% 2%
61 LI Victoria J. 2% 11% 31% 36% 17% 3%
62 WIGGERS Susan Q. 1% 10% 30% 37% 18% 3%
63 KER Grace 6% 27% 38% 23% 6% -
64 ALCEBAR Kayla 3% 21% 39% 28% 8% 1%
65 CARVALHO Isabela A. - - 5% 21% 38% 28% 7%
66 SCALAMONI-GOLDSTEIN Charlotte S. - 1% 7% 28% 40% 21% 3%
67 POSSICK Lola P. - - 1% 12% 47% 40%
68 MARSEE Samantha 1% 6% 24% 38% 26% 5%
69 ANTHONY Alexia B. - 6% 27% 39% 23% 4% -
70 BOIS Adele - 1% 7% 25% 37% 24% 6%
71 HURST Kennedy 1% 16% 39% 31% 11% 2% -
72 YONG Erika E. - - 4% 18% 36% 33% 9%
73 HOLMES Emma 10% 37% 37% 13% 2% - -
74 OLSEN Natalie J. - 11% 35% 37% 15% 2%
75 ANDRES Charmaine G. 2% 13% 33% 35% 15% 2%
76 MOYA Keona L. - - 3% 17% 42% 38%
77 JUNG Irene 8% 32% 38% 19% 4% -
78 ROGERS Pauline E. 25% 42% 26% 7% 1% -
79 CODY Alexandra C. - 8% 30% 39% 20% 3%
80 CHIN Erika J. - - - 5% 23% 43% 29%
81 LU Amy - 4% 32% 41% 19% 3% -
82 NEIBART Fiona 2% 18% 36% 30% 12% 2% -
83 WU Erica L. - 3% 14% 33% 34% 14% 2%
84 PRIEUR Lauren 1% 8% 24% 34% 24% 8% 1%
85 LU Elaine 1% 8% 25% 36% 24% 7% 1%
86 VESTEL Mira B. - 1% 12% 33% 36% 16% 2%
87 KRYLOVA Valery 4% 22% 37% 27% 9% 1% -
88 NI Sharon 1% 11% 34% 35% 15% 3% -
89 LIAO Siwen 1% 31% 43% 21% 4% - -
90 ALFARACHE Gabriella C. 2% 33% 41% 19% 4% - -
91 SINHA Anika 18% 38% 31% 12% 2% -
91 BEVACQUA Aria F. 8% 30% 37% 20% 5% -
93 DEPEW Charlotte R. 27% 42% 24% 6% 1% -
94 GORMLEY Arwen E. - 5% 22% 37% 28% 7%
95 BILILIES Sophia 15% 41% 34% 9% 1% -
96 BALAKUMARAN Maya 7% 27% 38% 22% 6% 1%
97 TURNOF Kayla M. 7% 28% 38% 22% 5% -
98 JOHNSON Lauren 1% 9% 28% 38% 21% 4%
99 LIU Rachel 4% 18% 34% 30% 12% 2%
99 SHI Cathleen 19% 40% 30% 10% 1% -
101 ZIELINSKI Isabella G. 12% 35% 35% 15% 3% -
101 YANG Lea 24% 45% 26% 5% - -
103 SCHIMINOVICH Sophia I. 5% 24% 38% 25% 8% 1%
104 TODD Phoebe 16% 42% 34% 9% 1% -
105 STONE Hava S. - 2% 13% 33% 35% 14% 2%
106 CHIN Elise 37% 44% 17% 3% - - -
107 BHATTACHARJEE Rhea - 6% 27% 39% 23% 5% -
108 LIU Sophie 4% 25% 38% 25% 7% 1% -
109 ATLURI Sara V. - 4% 22% 39% 28% 7% -
110 SLOBODSKY Sasha L. 4% 22% 42% 25% 6% 1% -
111 BAKER Audrey C. - 18% 42% 29% 9% 1% -
111 BAKER Amelia M. 22% 46% 26% 6% - - -
113 ULIBARRI Nevaeh L. 8% 31% 37% 19% 5% 1% -
114 JEAN Olympe G. 4% 21% 38% 27% 9% 1% -
115 GRAFF Sophie 5% 21% 34% 27% 11% 2% -
116 HUANG MADELINE 20% 46% 27% 6% 1% - -
117 HASSANEIN Toqa 1% 28% 42% 23% 5% -
118 HONE Katarina G. 1% 11% 30% 37% 18% 3%
119 LEE Hannah 4% 21% 38% 28% 8% 1%
120 CHEN Xinyan 10% 34% 36% 17% 3% -
121 BARNOVITZ Maya 45% 40% 13% 2% - -
122 YANG Ashley M. 3% 18% 34% 30% 12% 2%
123 CHIOLDI Mina - 1% 11% 32% 36% 17% 3%
124 MATAIEV Natalie S. 1% 11% 31% 36% 18% 3% -
125 DHAR Aamina 7% 31% 40% 18% 4% - -
126 WEI Vivian W. 10% 30% 34% 19% 5% 1% -
127 D'ORAZIO Sofia V. 52% 37% 10% 1% - - -
127 FANG sophie 61% 33% 6% - - - -
129 ALANGAD Rhea 73% 26% 2% - - - -
130 OBRADOVIC Ana 5% 38% 39% 15% 3% - -
131 MORAN Rhea 41% 42% 15% 2% - - -
132 BENOIT Adelaide L. 8% 29% 37% 20% 5% -
133 CHANG Audrey 44% 40% 13% 2% - -
134 WANG Jianning 37% 42% 18% 3% - -
135 HENRY Soraya S. 42% 41% 14% 2% - - -
135 ALTIRS Kate 47% 39% 12% 2% - - -
137 NOVICK Mia J. 11% 43% 34% 11% 2% - -
137 TONG Jessie 16% 63% 19% 2% - - -
139 TUNG Renee 34% 45% 18% 3% - - -
140 LIGH Karis 76% 22% 2% - - - -
141 LIN Selena 36% 42% 18% 3% - -
142 CHEN Athena 90% 9% - - - -
143 HORMEL Molly 89% 10% - - - - -
144 NEELEY Leilani 97% 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.