The future of US Fencing is at stake!

For transparency, fairness, and athlete support, VOTE NOW for:
(1) Maria Panyi, (2) Andrey Geva, (3) Igor Chirashnya, and (4) Sue Moheb.

January NAC

Div I Women's Saber

Monday, January 6, 2020 at 10:00 AM

Charlotte, NC - Charlotte, NC, 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 AKSAMIT Monica - - 2% 10% 28% 38% 21%
2 SHELTON Aleksandra - - - 2% 14% 40% 44%
3 RUSSO Francesca - - - 3% 15% 41% 41%
3 THOMPSON Kamali A. - - 1% 6% 23% 42% 29%
5 KONG Vera - 2% 8% 23% 34% 25% 8%
6 JOHNSON Honor B. - - 2% 13% 40% 45%
7 WOZNIAK Dagmara I. - 1% 8% 24% 34% 25% 7%
8 PLUNKETT Kerry A. - 3% 12% 28% 33% 19% 4%
9 CHAMBERLAIN Maia C. - - - 2% 11% 37% 51%
10 WOZNIAK Kelli - 1% 5% 19% 35% 31% 10%
11 WALTER Zsofia R. 14% 36% 34% 14% 3% < 1%
12 FOX-GITOMER Chloe N. - - - - 4% 27% 69%
13 GREENBAUM Atara R. - 2% 10% 26% 35% 22% 5%
14 MILLER Sky - 1% 7% 27% 44% 21%
15 MERZA Sarah 1% 6% 24% 38% 26% 5%
16 YUN Joy - - 4% 18% 36% 33% 8%
17 BURKE Nora S. - - - 2% 11% 38% 49%
18 JENKINS Ryan J. - - 5% 22% 44% 28%
18 SKARBONKIEWICZ Magda - - 5% 21% 44% 29%
20 STRZALKOWSKI Aleksandra (Ola) M. - 1% 5% 20% 35% 30% 10%
21 WHANG Rebecca - 1% 6% 22% 39% 28% 3%
22 HIRSCH Sydney R. - - 4% 18% 37% 32% 9%
23 FOUR-GARCIA Madison - - 4% 18% 38% 33% 7%
24 SHEA Erin - 5% 18% 33% 29% 12% 2%
25 KIM Zoe - 3% 16% 35% 34% 12%
26 OISHI Megumi - 1% 8% 25% 39% 24% 3%
27 SINGLETON-COMFORT Leanne - - - 1% 6% 32% 62%
28 WITEK Sophie B. 6% 24% 37% 25% 7% 1%
29 LU Vivian Y. 1% 10% 29% 37% 20% 3%
30 PARKER Abigale B. 10% 32% 36% 18% 4% -
31 KOVACS Sophia 1% 6% 20% 33% 28% 11% 2%
32 LASOTA Marta 7% 27% 37% 22% 7% 1% -
33 TAO Hannah J. 1% 10% 27% 34% 21% 6% 1%
34 JOHNSON Edith (Tori) V. - - 1% 5% 21% 41% 32%
35 TARTAKOVSKY Elizabeth - - 1% 7% 26% 43% 24%
36 HOFFMAN Ilsa L. - 3% 13% 28% 33% 19% 4%
37 SATHYANATH Kailing 1% 11% 29% 35% 20% 4% -
38 WILLIAMS Jadeyn E. - 2% 11% 31% 38% 18%
39 WEINBERG Alexandra L. - 2% 13% 30% 34% 17% 3%
40 ANGLADE Alexis C. - - 1% 5% 22% 43% 30%
41 MORALES Jessica Y. - 2% 10% 29% 37% 19% 3%
42 STONE Hava S. 6% 22% 34% 26% 10% 2% -
43 DOHERTY Maverick L. - 3% 16% 34% 32% 12% 1%
44 LEE Alexandra B. - - 3% 16% 36% 34% 11%
45 SECK Chejsa-Kaili F. - 3% 12% 28% 34% 19% 4%
46 EDGINGTON Grace 6% 25% 36% 24% 7% 1% -
47 TONG Kunling 1% 7% 22% 33% 26% 10% 1%
48 LINDER Kara E. - 1% 8% 27% 41% 23%
49 HEE Malia K. 2% 13% 33% 34% 15% 2%
50 SULLIVAN Siobhan R. 1% 7% 24% 37% 25% 6%
51 CHAN Casey - - 2% 12% 31% 38% 16%
51 HARRISON Imogen N. - 1% 6% 23% 38% 26% 6%
53 BROWN Emma 2% 13% 29% 32% 18% 5% 1%
54 TZOU Alexandra - 2% 12% 30% 36% 18% 2%
55 KUDRIAVTSEVA Daria - 2% 9% 24% 35% 24% 7%
56 MOYA Keona L. - 2% 10% 25% 34% 23% 6%
57 PINCUS Emma Y. 11% 33% 36% 17% 4% - -
58 GORMAN Alexandra C. 1% 6% 20% 33% 27% 11% 2%
59 MARSEE Samantha 6% 25% 37% 24% 7% 1% -
60 TANG Annie L. - 3% 13% 29% 34% 18% 3%
61 LIANG Megan 1% 6% 22% 37% 27% 7%
62 GREENBAUM Ella K. 1% 7% 24% 36% 25% 7% -
63 MERZA Celina - - 4% 15% 32% 34% 14%
64 SHIN Andrea Y. 14% 36% 33% 14% 3% - -
65 CHIN Erika J. - 1% 8% 26% 37% 23% 4%
66 POSSICK Lola P. - 3% 13% 30% 34% 17% 3%
67 TANG Catherine H. 9% 28% 35% 21% 7% 1% -
68 YUN Maya 13% 35% 34% 15% 3% -
69 PAK Kaitlyn 1% 11% 30% 36% 18% 3%
70 HINDS Eva R. 4% 18% 32% 30% 14% 3% -
70 CHEN Erin Y. - - 2% 14% 35% 36% 12%
72 HARRILL Gillian N. - - 3% 16% 35% 34% 11%
73 WILSON Sienna 1% 11% 30% 35% 19% 4% -
73 GUTHIKONDA Nithya - 1% 8% 24% 35% 24% 6%
75 LARGAESPADA Fatima 6% 25% 37% 25% 7% 1%
76 TURNER Zoe Y. 2% 13% 31% 34% 17% 3%
77 BUCHMANN Vivien 3% 16% 31% 30% 15% 4% -
78 WIGGERS Susan Q. 1% 9% 25% 34% 23% 8% 1%
79 WILLIAMS Chloe C. - 3% 12% 28% 33% 20% 5%
80 JULIEN Michelle 5% 20% 33% 28% 12% 2% -
81 GOUHIN Chloe - - 2% 12% 30% 38% 18%
82 MANUBAG Amanda R. 21% 41% 28% 8% 1% - -
83 FREEDMAN Janna N. - 4% 16% 33% 32% 13% 2%
84 HOOGENDOORN Sterre - 5% 21% 37% 27% 8% 1%
85 TOMASZEWSKI Alicja C. 7% 28% 38% 21% 5% 1% -
85 KUZNETSOVA Nastassja 5% 22% 34% 27% 10% 2% -
87 KOBOZEVA Tamara V. 12% 31% 33% 18% 5% 1% -
88 LI Victoria J. 3% 17% 34% 30% 13% 2% -
89 SHOMAN Miriam 16% 38% 32% 12% 2% - -
90 KATZ Anat 9% 30% 36% 20% 5% -
91 HONE Katarina G. 15% 37% 32% 13% 2% -
92 SHEALY Maggie 4% 19% 36% 30% 10% 1%
92 THEODORE Maria A. - 1% 9% 29% 41% 19%
94 TIMOFEYEV Daniella - 4% 19% 37% 32% 7%
95 ROH Rachel E. 3% 18% 36% 31% 11% 1%
96 CHANG Josephine S. 6% 24% 37% 25% 8% 1%
97 TIMOFEYEV Nicole - 4% 16% 34% 32% 13% 1%
98 HOOGENDOORN Levi 5% 23% 36% 26% 9% 1% -
99 REDDY Shreya 5% 21% 35% 27% 10% 2% -
100 LACSON Sarah 3% 17% 33% 30% 13% 3% -
101 DANAHY Ellen D. 15% 38% 32% 12% 2% - -
102 SWALLOW Abigail R. 7% 25% 35% 24% 9% 1% -
103 MENKE Kavya I. 21% 42% 28% 8% 1% - -
104 MATAIEV Natalie S. 27% 41% 24% 7% 1% - -
105 LIU Rachel 5% 24% 36% 25% 8% 1% -
105 SHOMAN Jenna - 2% 11% 30% 35% 18% 3%
107 SCALAMONI-GOLDSTEIN Charlotte S. 3% 17% 35% 31% 11% 2% -
108 LAMBERT Jasmine M. 3% 17% 33% 30% 14% 3% -
108 KOLMYKOVA Aleksandra 4% 19% 34% 29% 12% 3% -
110 FLOREZ Melissa 7% 25% 35% 24% 8% 1% -
111 ZEGERS Anneke E. - 1% 5% 19% 35% 30% 10%
112 ZEGERS Gabrielle N. 14% 38% 33% 13% 2% - -
112 KOO Samantha 7% 27% 36% 22% 7% 1% -
114 DRAGON Rainer 2% 12% 29% 33% 19% 5% 1%
115 HANADARI-LEVY Amit 1% 10% 26% 34% 22% 6% 1%
116 GORMAN Victoria M. 5% 23% 37% 25% 8% 1% -
117 VALADEZ Emily T. 15% 37% 33% 13% 3% - -
118 PINCUS Lucy Y. 24% 42% 26% 7% 1% -
119 ANDRES Katherine A. 8% 30% 37% 20% 4% -
120 DELSOIN Chelsea C. 9% 31% 37% 18% 3% -
121 GHOSH Priyanka 16% 38% 33% 12% 2% -
122 OLSEN Natalie J. 12% 35% 35% 15% 3% -
123 WU Erica L. 18% 39% 30% 11% 2% -
124 SAYLES Nina R. 15% 37% 32% 13% 2% -
124 KIM Catherine 15% 37% 33% 13% 2% -
124 DI PERNA Chiara I. - < 1% 3% 16% 41% 40%
127 WEBER Juliana I. 14% 37% 34% 13% 2% -
128 HILADO Sarah 6% 24% 35% 25% 9% 1% -
129 LAWLOR Gillian M. 3% 16% 31% 30% 15% 4% -
130 CHEN Crystal 18% 37% 30% 12% 3% - -
130 LIN Audrey J. 1% 7% 26% 37% 23% 6% -
132 HE Charlotte 2% 13% 29% 32% 19% 5% -
133 BLUM Leah I. 1% 6% 22% 36% 26% 8% 1%
134 KALRA Himani V. 4% 17% 32% 30% 14% 3% -
135 VAN ATTA Grace Y. 15% 34% 32% 15% 4% - -
136 BOIS Adele 1% 9% 27% 37% 21% 5% -
137 DEPEW Charlotte R. 19% 40% 30% 10% 1% - -
138 BERMAN Stella 1% 6% 22% 36% 26% 8% 1%
139 YURT Leyla 25% 41% 25% 7% 1% - -
140 CHEN Xinyan 24% 40% 26% 8% 1% - -
141 ZHOU Rebecca M. 16% 36% 31% 13% 3% - -
142 TURNOF Kayla M. 18% 38% 31% 11% 2% - -
143 BENOIT Adelaide L. 5% 24% 38% 25% 7% 1% -
144 BAE EMMELINE 17% 37% 31% 12% 2% - -
145 SHAY-TANNAS Zoe 14% 36% 34% 14% 2% - -
146 NEIBART Fiona 19% 45% 27% 7% 1% - -
147 ZIELINSKI Isabella G. 18% 37% 30% 12% 2% - -
148 DUNLAP Allison N. 19% 37% 29% 12% 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.