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.

November NAC

Y-14 Women's Saber

Friday, November 10, 2023 at 8:45 AM

Fort Worth Convention Center - Fort Worth, TX, 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 ZHANG XUANYI - - - 5% 32% 62%
2 FERNANDEZ Martina - - - 1% 10% 38% 50%
3 HSU Leah - 1% 10% 34% 44% 11%
3 LIU Yifei - - - 3% 17% 41% 38%
5 CHIARELLI Valentina - - - 2% 14% 41% 43%
5 VINOGOROVA Sofiia - - 1% 5% 20% 41% 34%
7 HUAI Delilah - - - - 5% 33% 62%
8 YOUNG Charlotte G. - - - 1% 6% 33% 60%
9 HAN Emma - 6% 23% 36% 26% 8% 1%
10 MALEK Zolie - - 1% 6% 24% 43% 27%
11 SENOGLU Irmak - - - 3% 17% 42% 38%
12 SCHMIDT Isabel - - 1% 5% 21% 42% 31%
13 GAUTAM Sahana - - 1% 8% 37% 54%
14 LIU Hannah - 5% 21% 39% 29% 7%
15 CHIANG Melissa - 1% 6% 23% 38% 27% 6%
16 SHEARER Alena 1% 8% 24% 35% 24% 7% 1%
17 KURAEVA Vasilisa - - 4% 20% 43% 33%
18 LIN Elaine - 2% 16% 40% 33% 9%
19 ARNOLD Hali - - 2% 11% 29% 38% 19%
20 PANTALEON-MAZOLA Amari - 1% 6% 21% 36% 28% 8%
21 HAMMERSTROM Aria - 1% 7% 22% 37% 27% 7%
22 FAVO Isabella - - 1% 7% 24% 40% 27%
23 DHAR Layla - 4% 17% 35% 33% 11%
24 MERMEGAS Olivia 2% 18% 40% 31% 8% 1%
25 LIU Kelly - 4% 17% 34% 31% 12% 1%
26 LOO Kaitlyn - 1% 7% 24% 38% 25% 5%
27 KWON Ava 1% 6% 19% 33% 28% 12% 2%
28 BUSH Bethany - 2% 10% 26% 35% 23% 5%
29 LEOU Korina - 1% 6% 24% 39% 26% 5%
30 VINOKUR Anita - - 4% 18% 39% 32% 6%
31 DAMBAL Sasha - 1% 9% 32% 42% 17%
32 FENG Alicia G. - 4% 15% 30% 32% 16% 3%
33 TENG EMMA - 2% 13% 32% 35% 16% 3%
34 CHAN Jolene - - 1% 10% 33% 44% 11%
35 TA-ZHOU Emma 1% 10% 27% 33% 21% 7% 1%
36 HUGHES-WILLIAMS Adelayde - 5% 20% 36% 29% 9%
37 KANG Ellie - - 1% 8% 27% 41% 23%
38 NADKARNI Marisa 2% 17% 36% 31% 12% 2% -
39 WANG Callie - - 2% 12% 32% 39% 15%
40 KIM Karen 2% 15% 34% 33% 13% 2% -
41 GAY Sasha 1% 9% 25% 34% 23% 7% 1%
42 HU Anna - 1% 5% 20% 37% 30% 7%
43 DHAR Rana 2% 11% 29% 34% 19% 5% -
44 LIU Hannah 3% 18% 36% 30% 12% 2% -
45 WEI JoyAnn - 1% 4% 16% 33% 34% 12%
45 BERMAN greta - - 1% 9% 27% 40% 23%
47 HUANG Doris - 3% 13% 30% 34% 17% 3%
48 KINKADE Ellie - 1% 5% 20% 36% 29% 8%
49 GUGALA Hanna - 2% 12% 32% 38% 16%
50 STONE Coral - 3% 14% 34% 36% 14%
51 LEI Zitong (Meya) 1% 6% 23% 37% 26% 7%
52 CHAVAN Arya - 1% 12% 35% 41% 11%
53 HALPERIN Elizabeth H. - 6% 25% 38% 25% 5%
54 LONG Jessie 7% 27% 37% 22% 6% 1%
55 SINGER Ellery 2% 15% 35% 33% 13% 2% -
56 CHOI Charlotte 1% 11% 32% 37% 17% 3% -
56 AWAD Royce - 2% 11% 29% 36% 18% 3%
58 STADNIK Emilia - 6% 23% 38% 26% 6% -
59 RANDALL-COLLINS Shea M. 6% 23% 35% 25% 9% 2% -
60 YUEN Nicole 4% 21% 36% 28% 10% 2% -
61 HO Sophia 14% 49% 30% 6% 1% -
62 ZHAI AMY 1% 7% 22% 33% 25% 9% 1%
63 YU Stella 10% 32% 35% 18% 4% 1% -
64 GONG Joy - 5% 19% 35% 29% 10% 1%
65 MAK Kaitlin 4% 22% 41% 27% 6% -
66 BLAKE Anna - 3% 14% 31% 33% 16% 3%
67 CROOKS Riley 3% 14% 30% 32% 17% 4% -
68 CONG Anne - 1% 5% 20% 38% 30% 6%
69 SUNG Isabella 1% 9% 27% 36% 22% 6% 1%
70 GOLDIN Nina - - 5% 24% 44% 26%
71 GENTILE Vittoria 7% 30% 37% 20% 5% -
72 MERCHANT Aishwarya - 2% 10% 27% 36% 22% 4%
73 MUNGUIA Mila - 4% 18% 36% 30% 10% 1%
74 MEYERSON Michelle 3% 16% 33% 31% 14% 3% -
75 MOON Claire 6% 29% 39% 20% 5% 1% -
76 BERRIOS Catalina 5% 20% 34% 27% 11% 2% -
77 YE Madeleine 5% 28% 38% 22% 6% 1% -
78 KIM Satie 1% 13% 34% 35% 15% 2% -
79 CHERON Helene 11% 33% 35% 17% 4% - -
80 KIM Saeren 13% 33% 33% 16% 4% 1% -
81 TISSONE Veronica 17% 38% 31% 12% 2% - -
82 JIANG Evelyn 1% 9% 28% 36% 21% 5%
83 KU Alathea-Joy 1% 13% 37% 36% 12% 1%
84 MYAT Chloe - 6% 22% 37% 27% 7%
85 ZHU Avril 2% 13% 36% 37% 12% 1%
86 KIM Grace M. 14% 36% 33% 14% 3% -
87 HUANG Neila 1% 15% 41% 32% 10% 1%
88 LAI Karen 63% 31% 6% - - -
89 KIRBY Skye 64% 30% 5% - - -
90 WANG JiaQi - 1% 8% 28% 40% 21% 3%
91 BORGUETA Madison - 6% 22% 36% 27% 8% 1%
92 TONG Laurie 1% 10% 31% 36% 18% 4% -
93 STAPLEY Claire 13% 38% 34% 13% 2% - -
94 MACKAY Katherine 1% 10% 29% 36% 20% 5% -
95 SUNG Olivia 16% 36% 31% 14% 3% - -
96 BROWN Aria 4% 25% 40% 24% 6% 1% -
97 LIN Annika 4% 18% 33% 29% 13% 3% -
98 CAI Veronica 8% 27% 35% 22% 7% 1% -
99 PALMIERI Giuliana M. 15% 37% 32% 13% 2% -
100 TIAN Cynthia 1% 15% 37% 33% 12% 1%
101 ASPIRAS Avery 39% 43% 16% 2% - -
102 CHEN Elaine 2% 12% 28% 33% 19% 5% 1%
103 SHMULER Fiona 10% 31% 35% 19% 5% 1% -
104 LI Sonia 4% 19% 33% 28% 12% 3% -
105 LEE Alyson 1% 10% 26% 33% 22% 7% 1%
106 SEBASTIAN Ava 1% 19% 38% 30% 10% 1% -
107 KIM Audrey 3% 17% 34% 30% 13% 2% -
108 VATS Ishita 24% 41% 26% 8% 1% - -
109 SHEN Emily 17% 36% 31% 13% 3% - -
110 BAERENWALD Welles 1% 9% 25% 34% 23% 8% 1%
111 ZHANG Olivia 14% 36% 33% 14% 3% - -
112 PADHI Kaavya 1% 10% 28% 35% 21% 5% 1%
113 JUILLERAT Elina 12% 36% 34% 14% 3% - -
114 WANG Jiayi < 1% 5% 19% 34% 29% 11% 2%
115 LEE Kaitlin 12% 40% 35% 12% 1% -
115 REN Katherine 4% 30% 42% 21% 4% -
117 ZHANG Ashley 4% 27% 40% 23% 6% -
118 KESSLER Amelia 53% 37% 9% 1% - - -
119 CLAIANU Adriana 61% 34% 5% - - -
120 SYED Azra 29% 43% 23% 5% 1% - -
120 YU Skylar 17% 38% 31% 12% 2% - -
122 CHERUKURI Tanvi 75% 23% 3% - - - -
122 LEIGH Adalene 26% 42% 24% 7% 1% - -
122 KIM Alice 29% 43% 23% 5% 1% - -
122 JUNG Sienna 50% 38% 10% 1% - - -
126 KO Ariel 42% 41% 15% 3% - -
127 AKULOVA Eva 58% 34% 7% 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.