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.

October NAC

Div II Women's Saber

Sunday, October 29, 2023 at 8:00 AM

Orange County Convention Center - Orlando, FL, 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 BOYNTON Ainsley - 1% 9% 26% 36% 23% 5%
2 LIM Jaslene - 1% 8% 25% 41% 25%
3 YUCEL Emine I. - - - - 5% 32% 63%
3 CHIARELLI Valentina - - 1% 9% 30% 42% 17%
5 PABIAN Emilia - 1% 5% 19% 35% 31% 11%
6 FAVO Isabella - - 3% 14% 34% 37% 12%
7 LUKER Sophia - - 1% 7% 24% 41% 27%
8 CHUNG Hailey - 2% 10% 30% 39% 19%
9 SHI Julia - - 4% 18% 35% 31% 11%
10 SENOGLU Irmak - - 4% 17% 35% 33% 12%
11 HSU Leah - 2% 13% 30% 33% 18% 4%
11 MANKOVA Varvara - 1% 8% 25% 36% 24% 6%
13 DAVIDOVA Kira 1% 6% 22% 35% 26% 9% 1%
14 DANTULURI Shalini - 2% 13% 30% 34% 17% 3%
15 CAO Sophie 2% 15% 34% 32% 14% 3% -
16 ZHANG Sophie - 1% 5% 20% 36% 30% 8%
17 HUANG MADELINE - - 1% 7% 25% 41% 25%
18 ZHANG Chenfei - - 3% 13% 33% 37% 15%
19 FAN Grace - - 4% 16% 34% 33% 12%
20 LI Alexis - 1% 10% 29% 36% 20% 4%
20 LIN Nicole - - 2% 13% 31% 37% 17%
22 GOMERMAN Sophia - 1% 10% 29% 35% 20% 4%
23 HENRY Soraya S. - 2% 12% 31% 38% 17%
24 WANG Zidan - 1% 7% 23% 36% 26% 7%
25 LIU Sumin - - - 3% 18% 44% 35%
26 CHIANG Melissa - 3% 13% 30% 34% 17% 3%
27 DIECK Miranda P. - 4% 19% 34% 29% 12% 2%
28 FANG Victoria W. - - - 4% 20% 43% 33%
28 PANTALEON-MAZOLA Amari - 1% 9% 27% 36% 22% 5%
30 GOLOVITSER Maya - 2% 11% 29% 35% 19% 4%
31 VINOGOROVA Sofiia - - 6% 22% 37% 28% 8%
32 BERNARD Kathryn - 2% 10% 27% 35% 22% 5%
33 DENG Brooke - - 1% 5% 21% 42% 31%
34 LUKER Hannah 6% 23% 35% 26% 9% 1%
35 TURNOF Kayla M. - - 2% 12% 37% 41% 8%
36 MALEK Zolie - 4% 18% 35% 32% 10%
37 HU Michelle - 3% 14% 33% 36% 14%
38 ELLIS-FURLONG Ava 22% 39% 28% 10% 2% -
39 GRAJALES Hannah E. - - 2% 11% 30% 38% 19%
40 TA-ZHOU Emma 2% 17% 37% 31% 11% 2% -
41 DUDNICK Morgan - 4% 18% 34% 30% 12% 2%
42 CHAVAN Arya - 4% 17% 33% 31% 13% 2%
43 KHAN Alissa - 1% 6% 22% 37% 27% 8%
44 GOLDIN Nina - 1% 7% 23% 36% 26% 7%
45 DAMBAL Sasha - 2% 12% 32% 37% 16% 2%
46 SCHAIBLE Sofia L. 1% 6% 21% 35% 28% 9%
47 HUANG Doris 7% 26% 36% 23% 7% 1%
48 WANG Callie - 4% 17% 34% 33% 12%
49 DONDERIS Katherine 14% 34% 33% 15% 3% -
50 MONTORIO Lily M. 2% 13% 31% 34% 17% 3%
51 LIU Hannah - 7% 28% 38% 21% 5% -
52 ZOLLER Noelle - 2% 13% 30% 33% 18% 4%
53 LI Sonia 2% 24% 39% 26% 8% 1% -
54 SAYSON Andrea - 1% 6% 20% 36% 29% 9%
55 WANG Gloria Ruoyan - 1% 7% 26% 42% 21% 2%
56 GARRETT Madrid 1% 8% 27% 36% 22% 6% -
57 HALPERIN Elizabeth H. 1% 10% 28% 34% 20% 5% 1%
58 BAIREDDY Maya 8% 29% 36% 21% 5% 1%
59 XIE Nora 2% 12% 31% 35% 17% 3%
60 TENG EMMA 1% 8% 25% 35% 24% 6%
61 MERCHANT Aishwarya 4% 19% 35% 29% 11% 2%
62 TESTROET Aubrey - 1% 10% 28% 36% 21% 4%
63 LABRECQUE Savannah 44% 40% 14% 2% - - -
64 NAYAK Antara 21% 49% 24% 5% 1% - -
65 STONE Coral 1% 7% 24% 36% 25% 6%
66 ONG Lauren 35% 42% 19% 4% < 1% -
67 MUNGUIA Mila 2% 11% 29% 34% 19% 5% -
68 LOPEZ-ONA Mia 3% 14% 31% 33% 16% 3%
69 HU Anna 1% 10% 29% 36% 20% 4%
70 XU Kaylyn 18% 38% 31% 12% 2% -
71 GLUCK Myriam 1% 5% 20% 35% 30% 9%
72 GUGALA Hanna - 1% 10% 27% 36% 21% 4%
73 JEFFORDS Sophia 1% 12% 33% 35% 16% 3% -
74 BAINS Nandini 4% 25% 39% 25% 7% 1% -
75 DHAR Layla - 2% 14% 33% 34% 14% 2%
76 OU Yixuan 2% 13% 33% 33% 15% 3% -
77 REN Xinling - 1% 7% 24% 36% 25% 7%
77 BORGUETA Madison 6% 28% 37% 21% 6% 1% -
77 BROWN Aria 23% 44% 26% 6% 1% - -
80 LOO Kaitlyn - 6% 26% 37% 23% 7% 1%
81 NAYAK Esha - 2% 14% 32% 33% 16% 3%
82 ALAMI Amira 25% 44% 25% 6% 1% - -
83 LITTLE Avery - 3% 14% 33% 36% 15%
84 KRIVOSHEEV Alexandra 1% 10% 27% 35% 22% 5%
85 NEUMAN Ella 5% 22% 36% 27% 9% 1%
86 LEE Lauren 2% 14% 31% 33% 16% 3%
87 LEOU Korina - 6% 22% 37% 28% 8%
88 FREEMAN Armine 4% 20% 34% 29% 11% 2%
89 BROWN Olivia - 2% 12% 30% 34% 19% 4%
90 LATYSHAVA Stephanie 3% 18% 35% 29% 12% 2% -
90 NGUYEN Madeleine 13% 35% 33% 15% 3% - -
92 CHI Claire 4% 20% 35% 28% 10% 2% -
93 SHEN Emily 15% 40% 32% 11% 2% - -
94 YOUNG Audrey - 7% 25% 35% 24% 8% 1%
95 MANN Sophia J. 1% 7% 23% 36% 26% 6%
96 BUSH Bethany 4% 19% 34% 29% 11% 2%
96 BLAKE Anna 6% 24% 36% 25% 8% 1%
98 CROOKS Riley 7% 25% 35% 24% 8% 1%
99 DE SILVA Augusta 7% 29% 37% 21% 6% 1%
100 SADANI Jyotika 5% 30% 40% 21% 5% - -
101 PADANILAM Lily 3% 18% 35% 30% 12% 2% -
102 MUELLER Amelia D. 1% 12% 35% 36% 13% 2% -
103 VILD Grace 20% 51% 24% 5% 1% - -
103 BANGALORE Shriya 28% 44% 22% 5% 1% - -
105 JEAN Emmanuelle C. 1% 6% 23% 36% 26% 8% 1%
106 HO Sophia 36% 43% 18% 3% - - -
106 SVENSSON Siri Lin 59% 33% 7% 1% - - -
108 WUNNAVA Elina 11% 31% 35% 19% 5% -
108 TURIANO Nadelle 18% 38% 30% 11% 2% -
110 PROBASCO Leila 3% 17% 38% 31% 10% 1% -
110 ALDERFER Katherine 41% 41% 15% 3% - - -
112 AKULOVA Kat 5% 31% 38% 20% 5% 1% -
113 MAUL Judy L. 9% 29% 36% 20% 5% 1%
114 LEE Kaelyn 47% 42% 10% 1% - - -
115 WUNNAVA Ellora 16% 37% 32% 13% 2% - -
116 SHEMONAEVA Irina 80% 19% 2% - - - -
117 CUTLER Juliet 23% 44% 26% 7% 1% - -
118 MILLER Tiffany E. 52% 39% 8% 1% - - -
119 PELLETIER Skylar 63% 31% 5% - - - -
120 SWEETLAND Lucy 60% 33% 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.