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Sumi-gaeshi

Based on fight data from 2016 onward.

All scores
1225
High-impact
79.3%
Fight win
89.2%
Avg ELO
1141
Ippon
284
Waza-ari
687
Yuko
254

Common setup techniques

Earlier tagged techniques by the same athlete in fights where this technique scored.

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Men vs women

Where this technique is credited — high-impact % and win % by sex.

Sex Fights High-impact Fight win
Men 868 81.8% 89.1%
Women 357 73.1% 89.6%

Weight divisions

Which divisions use this technique most; compare effectiveness by weight.

Division Fights High-impact Fight win
Men -73 kg
215 86.0% 91.7%
Men -66 kg
160 75.0% 94.1%
Men -81 kg
132 82.6% 86.9%
Men -60 kg
126 82.5% 87.8%
Men -90 kg
118 78.8% 82.9%
Men -100 kg
78 84.6% 88.2%
Women -48 kg
77 75.3% 96.0%
Women -63 kg
67 65.7% 89.1%
Women -70 kg
61 73.8% 91.8%
Women -57 kg
59 76.3% 84.5%
Women -52 kg
44 90.9% 88.4%
Women -78 kg
42 64.3% 86.8%

Average pre-fight ELO when credited with this technique (min 3 fights).

Judoka Avg ELO Fights
BEKAURI Lasha GEO
1541 3
GVINIASHVILI Beka GEO
1379 3
BOUKLI Shirine FRA
1353 9
TAMAOKI Momo JPN
1327 5
TOMA Sergiu UAE
1312 3
UNGVARI Miklos HUN
1311 3
MKHEIDZE Luka FRA
1297 3
DE WIT Frank NED
1293 8
ABULADZE Iago RUS
1291 7
KOTSOIEV Zelym AZE
1289 5
CARGNIN Daniel BRA
1289 3
CVJETKO Lara CRO
1277 5
KRPALEK Lukas CZE
1275 7
RINER Teddy FRA
1273 3
MEHDIYEV Mammadali AZE
1272 3

Judoka with the most credited fights using this technique.

Judoka Fights Fight win
STEVENSON Karen NED
14 85.7%
GOMBOC Adrian SLO
13 92.3%
IVANOV Ivaylo BUL
12 100.0%
SHEROV Abubakr TJK
12 100.0%
PELIVAN Petru MDA
11 100.0%
GILIAZOVA Sabina RUS
10 90.0%
MACIAS Tommy SWE
10 90.0%
ISSOUFI Kaila FRA
10 100.0%
BOUKLI Shirine FRA
9 100.0%
NYMAN Marcus SWE
9 100.0%
DE WIT Frank NED
8 87.5%
NIANG Assmaa MAR
8 87.5%
KHYAR Walide FRA
8 100.0%
MUKETE Daniel RUS
8 87.5%
ABULADZE Iago RUS
7 100.0%

Countries

Where credited scorers are from (one count per fight).

Country Fights Share
FRA 107
9.1%
RUS 100
8.5%
AZE 55
4.7%
KAZ 54
4.6%
ESP 45
3.8%
MGL 44
3.7%
NED 35
3.0%
GEO 33
2.8%
HUN 32
2.7%
GER 31
2.6%
SLO 30
2.5%
UKR 29
2.5%

Statistics count IJF-tagged scoring only. Archive grows as more competitions are scraped from 2016 onward.