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.

Capitol Clash SYC/RCC

Y-14 Women's Saber

Sunday, January 15, 2023 at 8:00 AM

Gaylord National Resort and Convention Center - National Harbor, DC, 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 SO Catelyn - - - - 4% 30% 66%
2 CHIARELLI Valentina - - 2% 9% 29% 40% 20%
3 SCHAIBLE Sofia L. - 2% 10% 24% 33% 24% 7%
3 FERNANDEZ Martina - - 2% 10% 28% 39% 21%
5 HUCHWAJDA Pola - 1% 4% 17% 34% 33% 11%
6 CANSECO Carly - 1% 9% 27% 36% 22% 5%
7 SENOGLU Irmak - - 2% 10% 28% 39% 21%
8 GUGALA Hanna 1% 9% 26% 35% 22% 6% 1%
9 YOUNG Charlotte G. - - - 5% 23% 44% 29%
10 BUSH Bethany - 1% 8% 23% 35% 25% 7%
11 HUANG Rachael - 1% 7% 24% 37% 25% 6%
12 DENG Brooke - - 1% 8% 28% 43% 20%
13 DHAR Layla - 1% 7% 23% 35% 26% 7%
14 WEI JoyAnn - - 4% 17% 34% 33% 12%
15 CHIANG Melissa - - 1% 8% 33% 48% 11%
16 VINOKUR Anita - 1% 8% 23% 34% 25% 7%
17 WANG Callie - - 3% 13% 32% 36% 15%
17 DAVIDOVA Kira - 3% 14% 30% 32% 16% 3%
19 ZHOU Ruoxi ( Jasmine) - - 4% 18% 37% 31% 9%
19 KURAEVA Vasilisa - - 3% 15% 34% 35% 13%
21 HU Anna - 3% 12% 27% 33% 21% 5%
22 ZENG Sarah - - 1% 5% 20% 41% 32%
23 FAVO Isabella - - 1% 10% 33% 41% 16%
24 DEHON Inès - 1% 9% 27% 36% 22% 5%
25 LIU Hannah - 1% 7% 28% 45% 19% 2%
26 GUVEN Coco - - 4% 17% 34% 33% 12%
27 RANDALL-COLLINS Shea M. 1% 8% 24% 35% 24% 7% 1%
28 CHAN Madeleine V. 5% 21% 33% 27% 12% 3% -
29 PANTALEON-MAZOLA Amari - 4% 15% 29% 31% 17% 4%
30 PROBASCO Leila - 1% 8% 30% 39% 20% 3%
31 LEOU Korina - 1% 8% 26% 37% 23% 5%
32 MEYERSON Michelle - 5% 22% 37% 26% 8% 1%
33 TSUI Natalie - - - 4% 19% 44% 33%
34 LIU Yifei - - - 4% 19% 42% 34%
35 CHAVAN Arya - 4% 18% 35% 30% 12% 2%
36 LEE Alyson - 4% 19% 36% 29% 10% 1%
37 KHOST Maeve 2% 11% 28% 33% 20% 6% 1%
38 TA-ZHOU Emma 2% 13% 32% 33% 16% 4% -
39 DAMBAL Sasha - 2% 13% 32% 34% 16% 3%
40 DANTULURI Shalini - 1% 5% 20% 37% 29% 8%
41 MERCHANT Aishwarya - 4% 15% 29% 31% 16% 4%
42 MALEK Zolie - - 1% 8% 28% 41% 22%
43 BERMAN greta - - - 4% 18% 42% 36%
43 CAO Sophie - 1% 8% 24% 36% 24% 5%
43 PADANILAM Lily 8% 28% 36% 21% 6% 1% -
46 LI Sonia - 6% 24% 36% 25% 8% 1%
47 GONZALEZ Veronika - 2% 12% 30% 35% 18% 3%
48 YOUNG Audrey - 1% 7% 24% 37% 25% 6%
49 KOHLBERGER Noelle - - 3% 15% 34% 35% 13%
50 MCAFEE Jada 2% 14% 31% 32% 17% 4% -
51 HAMMERSTROM Aria - 1% 8% 22% 34% 26% 8%
51 KRASOWITZ Lucy 3% 23% 40% 26% 8% 1% -
53 HUANG Doris - 2% 11% 30% 35% 19% 4%
54 BERNARD Kathryn 1% 7% 23% 36% 26% 7% 1%
55 WU Yuwei - 1% 5% 21% 38% 29% 7%
56 CHEN Kevy - 1% 7% 21% 33% 28% 9%
57 KWON Ava 1% 10% 27% 34% 21% 6% 1%
58 LOO Kaitlyn - 3% 13% 28% 32% 19% 4%
59 CHI Claire 8% 28% 35% 21% 7% 1% -
59 MACKAY Katherine 24% 42% 26% 7% 1% - -
61 FABRICANT Kioka R. - 4% 16% 31% 31% 15% 3%
62 PALMIERI Giuliana M. 12% 32% 33% 17% 5% 1% -
63 HILD Anya 6% 23% 34% 25% 10% 2% -
64 MANI Francesca B. - < 1% 2% 13% 34% 37% 14%
65 HSU leah - 1% 7% 23% 37% 26% 6%
66 LAURI Keira - 3% 21% 39% 28% 9% 1%
67 FAN Alexandria 2% 11% 26% 32% 21% 7% 1%
68 YERENKOVA Ameliia 2% 13% 34% 36% 13% 2% -
69 NADKARNI Marisa 6% 23% 36% 25% 8% 1% -
70 LATYSHAVA Stephanie - 5% 22% 37% 26% 8% 1%
70 WALLER London 3% 14% 29% 31% 18% 5% 1%
72 WANG JiaQi 3% 16% 30% 30% 16% 4% 1%
73 BORGUETA Madison 2% 13% 28% 32% 19% 6% 1%
74 CHEN Elaine 3% 17% 34% 31% 13% 2% -
75 STADNIK Emilia 4% 28% 40% 22% 5% 1% -
76 FUNG Iris - 2% 14% 32% 33% 16% 3%
77 HO Sophia 16% 37% 31% 13% 3% - -
78 MERMEGAS Olivia 1% 11% 28% 34% 20% 5% 1%
79 BAIREDDY Maya 19% 38% 30% 11% 2% - -
80 CASTELO Soleil 1% 28% 40% 23% 7% 1% -
81 KWON Hannah 21% 39% 28% 10% 2% - -
82 KU Alathea-Joy - 3% 14% 31% 33% 16% 3%
83 HALPERIN Elizabeth H. - 4% 18% 33% 30% 13% 2%
84 SHEN Emily 2% 13% 28% 31% 19% 6% 1%
85 MUELLER Sarah 6% 28% 40% 21% 4% - -
86 KALINICHENKO Yekaterina 4% 20% 36% 28% 11% 2% -
86 XU Demi 17% 41% 30% 10% 2% - -
88 ALAMI Amira 18% 45% 29% 8% 1% - -
89 BERRIOS Catalina - 5% 21% 36% 27% 10% 1%
90 FLEEGER Sophia 40% 45% 14% 1% - - -
91 KAUL Tara 2% 14% 32% 32% 15% 3% -
92 GENTILE Vittoria 29% 41% 22% 6% 1% - -
93 MUTHAPPAN Sahana 6% 27% 38% 22% 6% 1% -
94 DHAR Rana 6% 23% 33% 25% 10% 2% -
94 KIM Allison 13% 37% 35% 13% 2% - -
96 BROWN Aria 8% 38% 36% 15% 3% - -
97 ENG Madeleine 15% 36% 32% 14% 3% - -
98 WONG Charlene 42% 41% 14% 2% - - -
99 LIANG Claire 1% 11% 33% 35% 16% 3% -
100 SEBASTIAN Ava 13% 36% 34% 14% 3% - -
101 LEE Kaitlin 15% 49% 29% 6% 1% - -
102 ROHATGI Saanvi 29% 44% 22% 4% - - -
103 HUANG Neila 9% 30% 36% 19% 5% 1% -
104 WENG Amber 18% 39% 30% 11% 2% - -
105 ROSADO Leah 8% 31% 37% 19% 5% 1% -
106 LEE Kaelyn 2% 15% 38% 36% 9% 1% -
107 COOVADIA Malina 39% 43% 16% 3% - - -
108 ROOPRAI Amarjot 4% 20% 35% 28% 11% 2% -
108 POWERS Langley 65% 30% 5% - - - -
108 GALLAGHER Isabella 93% 7% - - - - -
111 YAO Annabelle 4% 24% 38% 25% 8% 1% -
112 SONG Emily 67% 29% 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.