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.

December NAC

Cadet Women's Saber

Sunday, December 12, 2021 at 12:00 PM

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 POSSICK Lola P. - - - 2% 15% 48% 35%
2 LEE Alexandra B. - - - 1% 6% 31% 62%
3 LEE Hannah 1% 11% 29% 35% 20% 4%
3 SHOMAN Jenna - - - - 4% 27% 68%
5 SZETO Chloe - - 2% 11% 31% 40% 16%
6 MIKA Veronica - - 2% 10% 29% 39% 20%
7 CALLAHAN Chase J. 1% 6% 23% 36% 27% 7%
8 ANDRES Charmaine G. - 2% 11% 30% 39% 19%
9 FREEDMAN Janna N. - - - 3% 16% 41% 39%
10 LI Amanda C. - - - 2% 13% 39% 46%
11 HWANG Gabriela M. - 1% 10% 33% 38% 15% 2%
11 ANDRES Katherine A. - - 1% 6% 25% 43% 25%
13 LIU Sophie - 4% 17% 31% 30% 14% 3%
14 ALCEBAR Kayla - 1% 8% 23% 36% 26% 7%
15 CHIN Sophia J. 2% 12% 31% 35% 17% 3%
16 CHEN Xiaohan - 2% 12% 32% 37% 16%
17 XU Ellen - - 1% 8% 29% 44% 18%
18 KIM Marley I. - 1% 10% 29% 37% 19% 2%
19 YANG Angelina LeLe - 1% 8% 25% 37% 23% 5%
20 BEVACQUA Aria F. - 1% 5% 20% 36% 29% 8%
21 SOURIMTO Valeria - 3% 16% 33% 33% 13% 2%
22 GHAYALOD reya 1% 9% 28% 37% 21% 4%
23 HILD Nisha - - 2% 11% 31% 39% 16%
24 LU Amy - 3% 13% 30% 34% 17% 3%
25 BLUM Leah I. - - - 4% 18% 42% 36%
26 DANK Dina - 1% 8% 22% 34% 26% 8%
27 CHIOLDI Mina - - 1% 8% 26% 40% 24%
28 LU Elaine 2% 13% 32% 34% 17% 3%
29 SINHA Anika - 4% 18% 34% 30% 11% 1%
30 BUHAY Rachel T. - 1% 8% 25% 37% 23% 5%
31 KANTIPUDI Shrika 9% 30% 36% 20% 5% 1% -
32 NATH Trisha 1% 8% 25% 36% 24% 7% -
33 GORMAN Victoria M. - 3% 17% 36% 33% 11%
34 ENGELMAN-SANZ Madeline A. - - - 3% 18% 44% 35%
35 JUNG Irene - 1% 8% 25% 36% 24% 5%
36 JULIEN Michelle - - 1% 6% 24% 42% 27%
37 PAUL Lila - - 4% 17% 36% 34% 10%
38 WIGGERS Susan Q. - - 3% 14% 32% 35% 15%
39 CODY Alexandra C. - - 1% 9% 28% 41% 21%
40 KER Grace - 3% 16% 35% 34% 11%
41 DELSOIN Chelsea C. - - - 2% 14% 43% 41%
42 YUAN Greta - 1% 9% 26% 37% 22% 4%
43 MCKEE Brynnley 10% 30% 35% 19% 5% 1% -
44 BOIS Adele - - 1% 8% 28% 42% 20%
45 SHTREVENSKY Maria - 1% 4% 17% 33% 33% 12%
46 XIAO julie - 6% 24% 38% 25% 6% -
47 VADASZ Ibla P. - 4% 17% 34% 33% 12%
48 PRIEUR Lauren - 1% 6% 21% 36% 29% 8%
49 MAKLIN Sofia 1% 8% 25% 35% 24% 7% -
50 LIGH Erenei J. - 2% 15% 36% 34% 12% 1%
51 LEE Sophia 1% 9% 27% 35% 21% 6% 1%
52 LEMUS-IAKOVIDOU ALEXANDRA 13% 33% 34% 16% 4% - -
53 WEI Vivian W. - 2% 14% 33% 34% 14% 1%
54 HENRY Soraya S. 13% 36% 34% 15% 3% - -
55 TSUI Natalie - 5% 19% 35% 29% 10% 1%
56 NGUYEN Ella - 7% 27% 38% 22% 5% -
57 SUBRAMANIAN Nitika 2% 13% 31% 34% 17% 3%
58 WU Helen 9% 32% 36% 18% 4% -
59 TABANGAY Heartlyn 3% 17% 34% 31% 13% 2%
60 CHEN Ashley 2% 13% 29% 32% 18% 5% 1%
61 BALAKUMARAN Maya - 2% 12% 30% 36% 17% 3%
62 DONG Angel 9% 30% 36% 20% 5% 1% -
63 GRAFF Sophie 1% 6% 20% 34% 28% 10% 1%
64 SCALAMONI-GOLDSTEIN Charlotte S. 1% 8% 26% 37% 23% 5%
65 ERIKSON Kira R. 1% 6% 21% 34% 27% 10% 1%
66 LIAO Siwen - 4% 17% 33% 31% 12% 2%
67 SHINCHUK Ellisha 1% 19% 39% 30% 10% 2% -
68 FAN Grace 9% 30% 36% 19% 5% 1% -
69 HAMBAZAZA Liisa 11% 32% 35% 17% 4% - -
70 JEONG Katie 3% 18% 34% 29% 13% 3% -
71 JOHNSON Dagny L. 1% 7% 23% 36% 26% 8% 1%
72 NYSTROM Sofia C. - 4% 18% 34% 31% 12% 1%
73 ZHANG Chenfei 5% 24% 36% 25% 8% 1% -
74 BARNOVITZ Maya 5% 21% 36% 28% 10% 1% -
75 PENG Florella 1% 8% 25% 35% 23% 7% 1%
76 NATHANSON Sammy E. 1% 5% 18% 31% 29% 14% 2%
77 OBRADOVIC Ana 4% 20% 36% 28% 10% 2% -
78 BUHAY Kirsten M. 16% 35% 31% 14% 3% - -
79 SCHIMINOVICH Sophia I. 1% 8% 26% 35% 23% 7% 1%
80 CHEN Xinyan - 3% 16% 34% 32% 13% 2%
81 ZENG Megan 9% 31% 36% 19% 5% 1% -
82 CHANG Audrey 25% 42% 25% 7% 1% -
83 HUNG Anna - 7% 26% 37% 23% 6% -
84 JOHNSON Lydia 3% 18% 34% 30% 12% 2% -
85 SADOVA Olga 1% 18% 38% 31% 11% 2% -
86 JOHNSTON Lily 7% 29% 40% 20% 4% - -
87 YANG Lea 1% 13% 34% 34% 15% 2% -
88 SHI Julia 4% 18% 35% 30% 12% 2% -
89 KHAN Alissa 3% 18% 35% 30% 12% 2% -
90 CHIANG Emily 1% 9% 24% 33% 23% 8% 1%
91 LI Angela 16% 37% 32% 13% 2% - -
92 ALFARACHE Gabriella C. 5% 22% 36% 27% 9% 1% -
93 MANSPERGER Leena 1% 5% 21% 36% 28% 9% 1%
94 SO Catelyn 18% 41% 30% 10% 1% -
95 BAWA Anahat 38% 41% 17% 4% - -
96 SPRINGER Ella 3% 17% 36% 30% 12% 2% -
97 EVANS Madelynn 17% 37% 31% 12% 2% - -
98 CHRISTOTHOULOU Olympia C. 13% 34% 34% 16% 3% - -
99 WANG Jianning 4% 18% 34% 29% 12% 2% -
100 ELNATAN Mica A. 19% 40% 30% 10% 1% - -
101 RAMIREZ Mirka A. 5% 22% 36% 27% 9% 1% -
102 JENKINS Scotland 18% 39% 31% 11% 2% - -
103 COLBY Mercer 42% 41% 15% 3% - - -
104 HE Lizbeth - 8% 28% 37% 22% 5% -
105 MORAN Rhea 29% 42% 23% 6% 1% - -
106 WEI JoyAnn 16% 38% 32% 12% 2% - -
106 LO JOCELYN 21% 42% 28% 8% 1% - -
108 MCKEE Ainsley 8% 27% 35% 22% 7% 1% -
109 SHUM Cindy 18% 39% 30% 11% 2% - -
109 NEELEY Leilani 79% 19% 2% - - - -
109 FANG sophie 24% 41% 26% 7% 1% - -
109 KUANG TongFei 23% 40% 27% 9% 1% - -
113 HUANG MADELINE 33% 42% 20% 4% - -
114 YU Zhiang 2% 13% 31% 33% 17% 4% -
115 KOKAL Genevieve 90% 9% - - - - -
115 SCHICK Veronica 20% 42% 29% 8% 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.