Salsomaggiore 2025 — player statistics

Four double-dummy measures per player plus bidding activity, over every board they played, and an opponent-adjusted (strength-of-schedule) Butler. Each table lists all players and is sortable by any column. Double-dummy is idealised — the true best play needs all four hands — so read these as tendencies, not verdicts.

Butler vs double-dummy par↑ top

IMPs per board scored above (+) or below (−) the board’s minimax par — what real bidding and play (theirs and the opponents’) added or gave away against perfect double-dummy play. Players with few boards are greyed. Click a column header to sort; filter by name or team.

#	Player	Team	Boards	/board	Total
1	ACHARYA SHUBHAM	🇮🇳 INDIA	120	+1.45	+174.0
2	S.Roy	🇮🇳 INDIA	120	+1.45	+174.0
3	R.Emmers	🇳🇱 NETHERLANDS	104	+1.34	+139.0
4	W.Klarenbeek	🇳🇱 NETHERLANDS	104	+1.34	+139.0
5	M.Andonov	🇧🇬 BULGARIA	144	+1.14	+164.0
6	L.Bellicaud	🇫🇷 FRANCE	112	+0.95	+106.0
7	T.Guichet	🇫🇷 FRANCE	112	+0.95	+106.0
8	Y.Li	🇨🇳 CHINA	80	+0.93	+74.0
9	Q.Tan	🇨🇳 CHINA	80	+0.93	+74.0
10	T.Pavlov	🇧🇬 BULGARIA	128	+0.81	+104.0
11	A.Momov	🇧🇬 BULGARIA	64	+0.80	+51.0
12	H.Koh	🇸🇬 SINGAPORE	104	+0.78	+81.0
13	J.Ong	🇸🇬 SINGAPORE	104	+0.78	+81.0
14	P.Beer	🇺🇸 USA1	152	+0.63	+96.0
15	H.Xing	🇺🇸 USA1	152	+0.63	+96.0
16	J.Bereza	🇵🇱 POLAND	96	+0.62	+60.0
17	B.Kula	🇵🇱 POLAND	96	+0.62	+60.0
18	G.Donati	🇮🇹 ITALY	128	+0.62	+79.0
19	G.Percario	🇮🇹 ITALY	128	+0.62	+79.0
20	M.Balodis	🇱🇻 LATVIA	120	+0.59	+71.0
21	J.Ilzins	🇱🇻 LATVIA	120	+0.59	+71.0
22	F.Guerra	🇦🇷 ARGENTINA	104	+0.59	+61.0
23	S.Semberoiz	🇦🇷 ARGENTINA	104	+0.59	+61.0
24	P.Cazabon	🇨🇱 CHILE	152	+0.57	+86.0
25	F.Nacrur	🇨🇱 CHILE	152	+0.57	+86.0
26	J.Andruszkiewicz	🇵🇱 POLAND	104	+0.44	+46.0
27	E.Sucharda	🇵🇱 POLAND	104	+0.44	+46.0
28	M.Seizovic	🇷🇸 SERBIA	128	+0.43	+55.0
29	S.Vazic	🇷🇸 SERBIA	128	+0.43	+55.0
30	V.Zhu	🇺🇸 USA2	104	+0.42	+44.0
31	A.Dhir	🇺🇸 USA2	112	+0.41	+46.0
32	X.Liu	🇨🇳 CHINA	112	+0.29	+32.0
33	H.Gao	🇨🇳 CHINA	104	+0.24	+25.0
34	D.Hsiao	🇹🇼 CHINESE TAIPEI	112	+0.23	+26.0
35	B.Bejenka	🇵🇱 POLAND	104	+0.20	+21.0
36	T.Kielbasa	🇵🇱 POLAND	104	+0.20	+21.0
37	Y.Chen	🇹🇼 CHINESE TAIPEI	96	+0.16	+15.0
38	C.Li	🇨🇳 CHINA	120	+0.14	+17.0
39	G.Giubilo	🇮🇹 ITALY	72	+0.14	+10.0
40	R.Sau	🇮🇹 ITALY	72	+0.14	+10.0
41	Z.Ferov	🇧🇬 BULGARIA	144	+0.13	+19.0
42	Z.Chu	🇨🇳 CHINA	112	+0.09	+10.0
43	C.Chiang	🇹🇼 CHINESE TAIPEI	104	+0.05	+5.0
44	Y.Huang	🇺🇸 USA2	87	-0.06	-5.0
45	R.Bloch	🇫🇷 FRANCE	104	-0.07	-7.0
46	E.Vallet	🇫🇷 FRANCE	104	-0.07	-7.0
47	S.Bar	🇮🇳 INDIA	87	-0.07	-6.0
48	S.Kar	🇮🇳 INDIA	87	-0.07	-6.0
49	M.Iher	🇪🇪 ESTONIA	104	-0.10	-10.0
50	S.Laan	🇪🇪 ESTONIA	104	-0.10	-10.0
51	A.Huang	🏴󠁧󠁢󠁳󠁣󠁴󠁿 SCOTLAND	104	-0.12	-13.0
52	A.Boonstra	🇳🇱 NETHERLANDS	96	-0.16	-15.0
53	B.Van Noort	🇳🇱 NETHERLANDS	96	-0.16	-15.0
54	Y.Cheng	🇹🇼 CHINESE TAIPEI	88	-0.16	-14.0
55	A.Manganella	🇮🇹 ITALY	104	-0.17	-18.0
56	S.Scata	🇮🇹 ITALY	104	-0.17	-18.0
57	A.Hutton	🏴󠁧󠁢󠁥󠁮󠁧󠁿 ENGLAND	152	-0.18	-28.0
58	O.Powell	🏴󠁧󠁢󠁥󠁮󠁧󠁿 ENGLAND	152	-0.18	-28.0
59	I.Miquelez Caballero	🇦🇷 ARGENTINA	96	-0.20	-19.0
60	N.Tiscornia Biaus	🇦🇷 ARGENTINA	96	-0.20	-19.0
61	M.Satriawan	🇮🇩 INDONESIA	120	-0.20	-24.0
62	S.Wijayanto	🇮🇩 INDONESIA	120	-0.20	-24.0
63	A.Yeung	🇺🇸 USA2	79	-0.22	-17.0
64	R.Toom	🇪🇪 ESTONIA	96	-0.22	-21.0
65	R.Zvorovski	🇪🇪 ESTONIA	96	-0.22	-21.0
66	D.Jansons	🇱🇻 LATVIA	80	-0.25	-20.0
67	R.Kreitals	🇱🇻 LATVIA	80	-0.25	-20.0
68	P.Bedouet	🇫🇷 FRANCE	88	-0.28	-25.0
69	C.Deheeger	🇫🇷 FRANCE	88	-0.28	-25.0
70	D.Lazarov	🇧🇬 BULGARIA	128	-0.30	-38.0
71	S.Li	🇹🇼 CHINESE TAIPEI	104	-0.31	-32.0
72	Z.Zhu	🇩🇪 GERMANY	104	-0.34	-35.0
73	Y.Zuo	🇩🇪 GERMANY	104	-0.34	-35.0
74	C.Lin	🇹🇼 CHINESE TAIPEI	104	-0.38	-40.0
75	C.Welland	🇺🇸 USA2	112	-0.42	-47.0
76	E.Olla	🇱🇻 LATVIA	104	-0.43	-45.0
77	T.Straume	🇱🇻 LATVIA	104	-0.43	-45.0
78	N.Davila	🇨🇱 CHILE	152	-0.45	-68.0
79	B.Perez	🇨🇱 CHILE	152	-0.45	-68.0
80	A.Bauer	🇩🇪 GERMANY	96	-0.45	-43.0
81	P.Petrov	🇩🇪 GERMANY	96	-0.45	-43.0
82	E.Gardner	🏴󠁧󠁢󠁳󠁣󠁴󠁿 SCOTLAND	80	-0.45	-36.0
83	R.Luhaorg	🇪🇪 ESTONIA	104	-0.46	-48.0
84	R.Piirisild	🇪🇪 ESTONIA	104	-0.46	-48.0
85	J.Middleton	🏴󠁧󠁢󠁳󠁣󠁴󠁿 SCOTLAND	112	-0.46	-52.0
86	N.Tennant	🏴󠁧󠁢󠁳󠁣󠁴󠁿 SCOTLAND	112	-0.47	-53.0
87	M.Johnstone	🇺🇸 USA1	152	-0.49	-75.0
88	J.Udomsrirungruang	🇺🇸 USA1	152	-0.49	-75.0
89	J.Lieberman	🇺🇸 USA2	112	-0.51	-57.0
90	R.Shaumi	🇮🇩 INDONESIA	80	-0.51	-41.0
91	D.Tarabunga	🇮🇩 INDONESIA	80	-0.51	-41.0
92	H.Gao	🇸🇬 SINGAPORE	96	-0.53	-51.0
93	R.Lee	🇸🇬 SINGAPORE	96	-0.53	-51.0
94	J.Clark	🏴󠁧󠁢󠁥󠁮󠁧󠁿 ENGLAND	152	-0.54	-82.0
95	K.Panchagnula	🏴󠁧󠁢󠁥󠁮󠁧󠁿 ENGLAND	152	-0.54	-82.0
96	J.Shearer	🏴󠁧󠁢󠁳󠁣󠁴󠁿 SCOTLAND	104	-0.55	-57.0
97	A.Casparie	🇳🇱 NETHERLANDS	104	-0.57	-59.0
98	M.Sprinkhuizen	🇳🇱 NETHERLANDS	104	-0.57	-59.0
99	D.Lee	🇸🇬 SINGAPORE	104	-0.60	-62.0
100	S.Wu	🇸🇬 SINGAPORE	104	-0.60	-62.0
101	C.Nunez	🇦🇷 ARGENTINA	104	-0.62	-64.0
102	R.Nunez	🇦🇷 ARGENTINA	104	-0.62	-64.0
103	D.Nobira	🇮🇩 INDONESIA	104	-0.66	-69.0
104	D.Rahayu	🇮🇩 INDONESIA	104	-0.66	-69.0
105	S.Pepic	🇷🇸 SERBIA	136	-0.67	-91.0
106	M.Simic	🇷🇸 SERBIA	136	-0.67	-91.0
107	S.Jesse	🇩🇪 GERMANY	104	-0.73	-76.0
108	Y.Tian	🇩🇪 GERMANY	104	-0.73	-76.0
109	D.Murray	🏴󠁧󠁢󠁳󠁣󠁴󠁿 SCOTLAND	96	-0.74	-71.0
110	S.Chatterjee	🇮🇳 INDIA	96	-0.80	-77.0
111	P.Dey	🇮🇳 INDIA	96	-0.80	-77.0
112	S.Guzvica	🇷🇸 SERBIA	40	+0.17	+7.0
113	B.Velickovic	🇷🇸 SERBIA	40	+0.17	+7.0

Opening-lead accuracy↑ top

How often a player’s opening lead held declarer to the same tricks as the best defensive lead double-dummy. Players with few boards are greyed. Click a column header to sort; filter by name or team.

#	Player	Team	Leads	On target	Conceded
1	T.Kielbasa	🇵🇱 POLAND	19	100.0%	0.00
2	P.Dey	🇮🇳 INDIA	22	100.0%	0.00
3	Z.Ferov	🇧🇬 BULGARIA	33	97.0%	0.03
4	X.Liu	🇨🇳 CHINA	27	96.3%	0.04
5	G.Giubilo	🇮🇹 ITALY	16	93.8%	0.06
6	S.Bar	🇮🇳 INDIA	28	92.9%	0.07
7	Y.Li	🇨🇳 CHINA	24	91.7%	0.08
8	S.Kar	🇮🇳 INDIA	21	90.5%	0.10
9	T.Pavlov	🇧🇬 BULGARIA	41	90.2%	0.15
10	J.Middleton	🏴󠁧󠁢󠁳󠁣󠁴󠁿 SCOTLAND	20	90.0%	0.10
11	T.Straume	🇱🇻 LATVIA	27	88.9%	0.11
12	S.Wijayanto	🇮🇩 INDONESIA	18	88.9%	0.11
13	J.Clark	🏴󠁧󠁢󠁥󠁮󠁧󠁿 ENGLAND	44	88.6%	0.11
14	M.Andonov	🇧🇬 BULGARIA	35	88.6%	0.14
15	S.Roy	🇮🇳 INDIA	26	88.5%	0.12
16	V.Zhu	🇺🇸 USA2	24	87.5%	0.12
17	R.Zvorovski	🇪🇪 ESTONIA	24	87.5%	0.17
18	T.Guichet	🇫🇷 FRANCE	22	86.4%	0.14
19	Y.Tian	🇩🇪 GERMANY	22	86.4%	0.14
20	A.Manganella	🇮🇹 ITALY	29	86.2%	0.14
21	C.Nunez	🇦🇷 ARGENTINA	14	85.7%	0.14
22	R.Emmers	🇳🇱 NETHERLANDS	21	85.7%	0.19
23	R.Piirisild	🇪🇪 ESTONIA	21	85.7%	0.19
24	B.Perez	🇨🇱 CHILE	34	85.3%	0.15
25	L.Bellicaud	🇫🇷 FRANCE	27	85.2%	0.15
26	N.Tennant	🏴󠁧󠁢󠁳󠁣󠁴󠁿 SCOTLAND	33	84.8%	0.15
27	H.Koh	🇸🇬 SINGAPORE	26	84.6%	0.19
28	R.Sau	🇮🇹 ITALY	26	84.6%	0.23
29	M.Satriawan	🇮🇩 INDONESIA	32	84.4%	0.16
30	D.Nobira	🇮🇩 INDONESIA	32	84.4%	0.22
31	R.Luhaorg	🇪🇪 ESTONIA	25	84.0%	0.16
32	S.Scata	🇮🇹 ITALY	25	84.0%	0.20
33	ACHARYA SHUBHAM	🇮🇳 INDIA	31	83.9%	0.23
34	C.Li	🇨🇳 CHINA	31	83.9%	0.23
35	B.Van Noort	🇳🇱 NETHERLANDS	18	83.3%	0.17
36	D.Tarabunga	🇮🇩 INDONESIA	24	83.3%	0.17
37	S.Pepic	🇷🇸 SERBIA	30	83.3%	0.17
38	G.Percario	🇮🇹 ITALY	30	83.3%	0.20
39	M.Balodis	🇱🇻 LATVIA	35	82.9%	0.17
40	H.Xing	🇺🇸 USA1	41	82.9%	0.20
41	P.Petrov	🇩🇪 GERMANY	23	82.6%	0.17
42	D.Hsiao	🇹🇼 CHINESE TAIPEI	23	82.6%	0.39
43	J.Bereza	🇵🇱 POLAND	34	82.4%	0.21
44	R.Bloch	🇫🇷 FRANCE	22	81.8%	0.18
45	R.Kreitals	🇱🇻 LATVIA	22	81.8%	0.18
46	J.Lieberman	🇺🇸 USA2	22	81.8%	0.23
47	Z.Zhu	🇩🇪 GERMANY	22	81.8%	0.23
48	M.Simic	🇷🇸 SERBIA	38	81.6%	0.24
49	M.Johnstone	🇺🇸 USA1	32	81.2%	0.19
50	A.Yeung	🇺🇸 USA2	16	81.2%	0.19
51	A.Dhir	🇺🇸 USA2	37	81.1%	0.19
52	Y.Zuo	🇩🇪 GERMANY	21	81.0%	0.19
53	S.Wu	🇸🇬 SINGAPORE	21	81.0%	0.19
54	F.Nacrur	🇨🇱 CHILE	42	81.0%	0.24
55	C.Welland	🇺🇸 USA2	26	80.8%	0.19
56	B.Bejenka	🇵🇱 POLAND	31	80.6%	0.19
57	S.Li	🇹🇼 CHINESE TAIPEI	31	80.6%	0.26
58	S.Vazic	🇷🇸 SERBIA	31	80.6%	0.29
59	W.Klarenbeek	🇳🇱 NETHERLANDS	25	80.0%	0.20
60	R.Nunez	🇦🇷 ARGENTINA	30	80.0%	0.20
61	S.Chatterjee	🇮🇳 INDIA	25	80.0%	0.24
62	J.Andruszkiewicz	🇵🇱 POLAND	25	80.0%	0.28
63	A.Casparie	🇳🇱 NETHERLANDS	20	80.0%	0.30
64	H.Gao	🇸🇬 SINGAPORE	25	80.0%	0.32
65	S.Jesse	🇩🇪 GERMANY	34	79.4%	0.23
66	C.Lin	🇹🇼 CHINESE TAIPEI	29	79.3%	0.21
67	A.Hutton	🏴󠁧󠁢󠁥󠁮󠁧󠁿 ENGLAND	47	78.7%	0.30
68	D.Lazarov	🇧🇬 BULGARIA	23	78.3%	0.22
69	Y.Cheng	🇹🇼 CHINESE TAIPEI	23	78.3%	0.22
70	J.Udomsrirungruang	🇺🇸 USA1	41	78.0%	0.29
71	H.Gao	🇨🇳 CHINA	27	77.8%	0.22
72	K.Panchagnula	🏴󠁧󠁢󠁥󠁮󠁧󠁿 ENGLAND	36	77.8%	0.22
73	F.Guerra	🇦🇷 ARGENTINA	27	77.8%	0.26
74	I.Miquelez Caballero	🇦🇷 ARGENTINA	27	77.8%	0.33
75	N.Davila	🇨🇱 CHILE	49	77.6%	0.24
76	P.Beer	🇺🇸 USA1	40	77.5%	0.35
77	M.Iher	🇪🇪 ESTONIA	31	77.4%	0.23
78	C.Chiang	🇹🇼 CHINESE TAIPEI	31	77.4%	0.29
79	D.Jansons	🇱🇻 LATVIA	22	77.3%	0.23
80	G.Donati	🇮🇹 ITALY	26	76.9%	0.46
81	P.Cazabon	🇨🇱 CHILE	30	76.7%	0.23
82	M.Seizovic	🇷🇸 SERBIA	30	76.7%	0.30
83	J.Ilzins	🇱🇻 LATVIA	17	76.5%	0.23
84	Y.Chen	🇹🇼 CHINESE TAIPEI	25	76.0%	0.24
85	R.Lee	🇸🇬 SINGAPORE	25	76.0%	0.24
86	Q.Tan	🇨🇳 CHINA	25	76.0%	0.28
87	Y.Huang	🇺🇸 USA2	25	76.0%	0.28
88	A.Boonstra	🇳🇱 NETHERLANDS	29	75.9%	0.28
89	N.Tiscornia Biaus	🇦🇷 ARGENTINA	29	75.9%	0.31
90	A.Momov	🇧🇬 BULGARIA	20	75.0%	0.25
91	R.Toom	🇪🇪 ESTONIA	20	75.0%	0.25
92	E.Vallet	🇫🇷 FRANCE	28	75.0%	0.29
93	S.Semberoiz	🇦🇷 ARGENTINA	28	75.0%	0.29
94	B.Kula	🇵🇱 POLAND	20	75.0%	0.30
95	D.Lee	🇸🇬 SINGAPORE	35	74.3%	0.31
96	A.Bauer	🇩🇪 GERMANY	23	73.9%	0.26
97	M.Sprinkhuizen	🇳🇱 NETHERLANDS	23	73.9%	0.30
98	Z.Chu	🇨🇳 CHINA	23	73.9%	0.39
99	D.Rahayu	🇮🇩 INDONESIA	19	73.7%	0.37
100	J.Ong	🇸🇬 SINGAPORE	32	71.9%	0.28
101	P.Bedouet	🇫🇷 FRANCE	21	71.4%	0.29
102	E.Olla	🇱🇻 LATVIA	31	71.0%	0.39
103	S.Laan	🇪🇪 ESTONIA	24	70.8%	0.33
104	R.Shaumi	🇮🇩 INDONESIA	20	70.0%	0.35
105	A.Huang	🏴󠁧󠁢󠁳󠁣󠁴󠁿 SCOTLAND	23	69.6%	0.39
106	C.Deheeger	🇫🇷 FRANCE	21	66.7%	0.38
107	J.Shearer	🏴󠁧󠁢󠁳󠁣󠁴󠁿 SCOTLAND	30	66.7%	0.40
108	D.Murray	🏴󠁧󠁢󠁳󠁣󠁴󠁿 SCOTLAND	24	66.7%	0.54
109	E.Sucharda	🇵🇱 POLAND	26	65.4%	0.42
110	O.Powell	🏴󠁧󠁢󠁥󠁮󠁧󠁿 ENGLAND	34	64.7%	0.38
111	E.Gardner	🏴󠁧󠁢󠁳󠁣󠁴󠁿 SCOTLAND	17	58.8%	0.53
112	S.Guzvica	🇷🇸 SERBIA	12	75.0%	0.25
113	B.Velickovic	🇷🇸 SERBIA	10	60.0%	0.40

Declarer-play accuracy↑ top

How often declarer took at least the double-dummy makeable tricks after the actual opening lead — i.e. didn’t leave tricks on the table. Players with few boards are greyed. Click a column header to sort; filter by name or team.

#	Player	Team	Contracts	On target	Conceded
1	R.Emmers	🇳🇱 NETHERLANDS	25	96.0%	0.04
2	J.Ong	🇸🇬 SINGAPORE	21	95.2%	0.05
3	Z.Zhu	🇩🇪 GERMANY	27	88.9%	0.11
4	S.Semberoiz	🇦🇷 ARGENTINA	27	88.9%	0.26
5	Z.Chu	🇨🇳 CHINA	28	85.7%	0.14
6	L.Bellicaud	🇫🇷 FRANCE	34	85.3%	0.21
7	S.Roy	🇮🇳 INDIA	33	84.8%	0.18
8	A.Dhir	🇺🇸 USA2	33	84.8%	0.21
9	Q.Tan	🇨🇳 CHINA	13	84.6%	0.15
10	S.Scata	🇮🇹 ITALY	26	84.6%	0.15
11	E.Sucharda	🇵🇱 POLAND	26	84.6%	0.19
12	M.Balodis	🇱🇻 LATVIA	39	84.6%	0.20
13	R.Kreitals	🇱🇻 LATVIA	19	84.2%	0.16
14	H.Xing	🇺🇸 USA1	31	83.9%	0.16
15	D.Hsiao	🇹🇼 CHINESE TAIPEI	37	83.8%	0.22
16	B.Bejenka	🇵🇱 POLAND	30	83.3%	0.17
17	J.Bereza	🇵🇱 POLAND	24	83.3%	0.21
18	S.Laan	🇪🇪 ESTONIA	18	83.3%	0.22
19	B.Kula	🇵🇱 POLAND	18	83.3%	0.44
20	S.Vazic	🇷🇸 SERBIA	29	82.8%	0.17
21	T.Guichet	🇫🇷 FRANCE	29	82.8%	0.21
22	J.Ilzins	🇱🇻 LATVIA	29	82.8%	0.21
23	G.Donati	🇮🇹 ITALY	23	82.6%	0.22
24	Y.Huang	🇺🇸 USA2	17	82.4%	0.29
25	R.Sau	🇮🇹 ITALY	11	81.8%	0.18
26	E.Vallet	🇫🇷 FRANCE	22	81.8%	0.23
27	M.Andonov	🇧🇬 BULGARIA	27	81.5%	0.37
28	C.Deheeger	🇫🇷 FRANCE	21	81.0%	0.19
29	S.Wijayanto	🇮🇩 INDONESIA	36	80.6%	0.19
30	P.Cazabon	🇨🇱 CHILE	35	80.0%	0.20
31	R.Nunez	🇦🇷 ARGENTINA	20	80.0%	0.20
32	D.Tarabunga	🇮🇩 INDONESIA	20	80.0%	0.20
33	A.Hutton	🏴󠁧󠁢󠁥󠁮󠁧󠁿 ENGLAND	30	80.0%	0.23
34	A.Momov	🇧🇬 BULGARIA	15	80.0%	0.27
35	E.Gardner	🏴󠁧󠁢󠁳󠁣󠁴󠁿 SCOTLAND	24	79.2%	0.25
36	W.Klarenbeek	🇳🇱 NETHERLANDS	33	78.8%	0.27
37	C.Lin	🇹🇼 CHINESE TAIPEI	23	78.3%	0.26
38	D.Nobira	🇮🇩 INDONESIA	32	78.1%	0.25
39	M.Sprinkhuizen	🇳🇱 NETHERLANDS	27	77.8%	0.37
40	P.Petrov	🇩🇪 GERMANY	27	77.8%	0.37
41	F.Guerra	🇦🇷 ARGENTINA	22	77.3%	0.27
42	B.Van Noort	🇳🇱 NETHERLANDS	26	76.9%	0.23
43	C.Li	🇨🇳 CHINA	26	76.9%	0.23
44	H.Gao	🇸🇬 SINGAPORE	30	76.7%	0.23
45	I.Miquelez Caballero	🇦🇷 ARGENTINA	21	76.2%	0.24
46	D.Rahayu	🇮🇩 INDONESIA	21	76.2%	0.33
47	D.Lazarov	🇧🇬 BULGARIA	37	75.7%	0.27
48	G.Percario	🇮🇹 ITALY	49	75.5%	0.27
49	T.Kielbasa	🇵🇱 POLAND	24	75.0%	0.25
50	A.Huang	🏴󠁧󠁢󠁳󠁣󠁴󠁿 SCOTLAND	39	74.4%	0.39
51	X.Liu	🇨🇳 CHINA	31	74.2%	0.26
52	M.Simic	🇷🇸 SERBIA	31	74.2%	0.29
53	S.Bar	🇮🇳 INDIA	23	73.9%	0.26
54	D.Murray	🏴󠁧󠁢󠁳󠁣󠁴󠁿 SCOTLAND	23	73.9%	0.26
55	T.Straume	🇱🇻 LATVIA	23	73.9%	0.35
56	N.Tiscornia Biaus	🇦🇷 ARGENTINA	19	73.7%	0.26
57	G.Giubilo	🇮🇹 ITALY	19	73.7%	0.32
58	ACHARYA SHUBHAM	🇮🇳 INDIA	30	73.3%	0.30
59	Y.Tian	🇩🇪 GERMANY	30	73.3%	0.30
60	F.Nacrur	🇨🇱 CHILE	45	73.3%	0.36
61	O.Powell	🏴󠁧󠁢󠁥󠁮󠁧󠁿 ENGLAND	41	73.2%	0.37
62	S.Pepic	🇷🇸 SERBIA	37	73.0%	0.30
63	R.Luhaorg	🇪🇪 ESTONIA	33	72.7%	0.36
64	P.Beer	🇺🇸 USA1	40	72.5%	0.38
65	Y.Li	🇨🇳 CHINA	18	72.2%	0.28
66	K.Panchagnula	🏴󠁧󠁢󠁥󠁮󠁧󠁿 ENGLAND	36	72.2%	0.33
67	Z.Ferov	🇧🇬 BULGARIA	43	72.1%	0.35
68	J.Middleton	🏴󠁧󠁢󠁳󠁣󠁴󠁿 SCOTLAND	25	72.0%	0.32
69	H.Koh	🇸🇬 SINGAPORE	25	72.0%	0.40
70	S.Kar	🇮🇳 INDIA	14	71.4%	0.29
71	M.Seizovic	🇷🇸 SERBIA	38	71.1%	0.29
72	R.Piirisild	🇪🇪 ESTONIA	24	70.8%	0.46
73	B.Perez	🇨🇱 CHILE	41	70.7%	0.32
74	S.Jesse	🇩🇪 GERMANY	17	70.6%	0.29
75	M.Satriawan	🇮🇩 INDONESIA	34	70.6%	0.41
76	J.Andruszkiewicz	🇵🇱 POLAND	27	70.4%	0.41
77	C.Welland	🇺🇸 USA2	33	69.7%	0.42
78	A.Bauer	🇩🇪 GERMANY	23	69.6%	0.43
79	T.Pavlov	🇧🇬 BULGARIA	29	69.0%	0.41
80	R.Shaumi	🇮🇩 INDONESIA	16	68.8%	0.31
81	A.Boonstra	🇳🇱 NETHERLANDS	22	68.2%	0.36
82	S.Li	🇹🇼 CHINESE TAIPEI	22	68.2%	0.41
83	D.Lee	🇸🇬 SINGAPORE	22	68.2%	0.50
84	S.Wu	🇸🇬 SINGAPORE	25	68.0%	0.36
85	P.Dey	🇮🇳 INDIA	25	68.0%	0.40
86	P.Bedouet	🇫🇷 FRANCE	25	68.0%	0.48
87	M.Iher	🇪🇪 ESTONIA	31	67.7%	0.32
88	S.Chatterjee	🇮🇳 INDIA	24	66.7%	0.38
89	M.Johnstone	🇺🇸 USA1	45	66.7%	0.38
90	J.Shearer	🏴󠁧󠁢󠁳󠁣󠁴󠁿 SCOTLAND	18	66.7%	0.39
91	A.Manganella	🇮🇹 ITALY	23	65.2%	0.43
92	A.Yeung	🇺🇸 USA2	23	65.2%	0.48
93	C.Nunez	🇦🇷 ARGENTINA	40	65.0%	0.38
94	Y.Chen	🇹🇼 CHINESE TAIPEI	20	65.0%	0.40
95	A.Casparie	🇳🇱 NETHERLANDS	34	64.7%	0.47
96	Y.Zuo	🇩🇪 GERMANY	34	64.7%	0.56
97	R.Zvorovski	🇪🇪 ESTONIA	25	64.0%	0.48
98	V.Zhu	🇺🇸 USA2	22	63.6%	0.36
99	R.Lee	🇸🇬 SINGAPORE	16	62.5%	0.50
100	N.Tennant	🏴󠁧󠁢󠁳󠁣󠁴󠁿 SCOTLAND	26	61.5%	0.42
101	E.Olla	🇱🇻 LATVIA	23	60.9%	0.43
102	J.Lieberman	🇺🇸 USA2	25	60.0%	0.52
103	R.Bloch	🇫🇷 FRANCE	32	59.4%	0.41
104	D.Jansons	🇱🇻 LATVIA	17	58.8%	0.47
105	J.Clark	🏴󠁧󠁢󠁥󠁮󠁧󠁿 ENGLAND	36	58.3%	0.50
106	H.Gao	🇨🇳 CHINA	31	58.1%	0.52
107	R.Toom	🇪🇪 ESTONIA	26	57.7%	0.54
108	N.Davila	🇨🇱 CHILE	28	57.1%	0.50
109	Y.Cheng	🇹🇼 CHINESE TAIPEI	14	57.1%	0.57
110	J.Udomsrirungruang	🇺🇸 USA1	34	52.9%	0.62
111	C.Chiang	🇹🇼 CHINESE TAIPEI	26	50.0%	0.73
112	S.Guzvica	🇷🇸 SERBIA	10	80.0%	0.20
113	B.Velickovic	🇷🇸 SERBIA	8	62.5%	0.50

Defensive accuracy↑ top

How often the defenders held declarer to the double-dummy makeable (or fewer) — charged to both defenders on the board. Players with few boards are greyed. Click a column header to sort; filter by name or team.

#	Player	Team	Boards	On target	Conceded
1	A.Momov	🇧🇬 BULGARIA	28	96.4%	0.04
2	P.Bedouet	🇫🇷 FRANCE	42	95.2%	0.05
3	C.Deheeger	🇫🇷 FRANCE	42	95.2%	0.05
4	J.Bereza	🇵🇱 POLAND	54	94.4%	0.06
5	B.Kula	🇵🇱 POLAND	54	94.4%	0.06
6	Y.Chen	🇹🇼 CHINESE TAIPEI	44	93.2%	0.09
7	X.Liu	🇨🇳 CHINA	56	92.9%	0.09
8	M.Andonov	🇧🇬 BULGARIA	85	92.9%	0.09
9	F.Guerra	🇦🇷 ARGENTINA	55	92.7%	0.11
10	S.Semberoiz	🇦🇷 ARGENTINA	55	92.7%	0.11
11	D.Hsiao	🇹🇼 CHINESE TAIPEI	52	92.3%	0.10
12	B.Bejenka	🇵🇱 POLAND	50	92.0%	0.12
13	T.Kielbasa	🇵🇱 POLAND	50	92.0%	0.12
14	T.Pavlov	🇧🇬 BULGARIA	74	91.9%	0.11
15	L.Bellicaud	🇫🇷 FRANCE	49	91.8%	0.08
16	T.Guichet	🇫🇷 FRANCE	49	91.8%	0.08
17	C.Li	🇨🇳 CHINA	60	91.7%	0.10
18	ACHARYA SHUBHAM	🇮🇳 INDIA	57	91.2%	0.09
19	S.Roy	🇮🇳 INDIA	57	91.2%	0.09
20	G.Giubilo	🇮🇹 ITALY	42	90.5%	0.12
21	R.Sau	🇮🇹 ITALY	42	90.5%	0.12
22	M.Seizovic	🇷🇸 SERBIA	61	90.2%	0.13
23	S.Vazic	🇷🇸 SERBIA	61	90.2%	0.13
24	A.Yeung	🇺🇸 USA2	39	89.7%	0.13
25	A.Manganella	🇮🇹 ITALY	54	88.9%	0.13
26	S.Scata	🇮🇹 ITALY	54	88.9%	0.13
27	P.Beer	🇺🇸 USA1	81	88.9%	0.14
28	H.Xing	🇺🇸 USA1	81	88.9%	0.14
29	Y.Huang	🇺🇸 USA2	44	88.6%	0.14
30	Y.Cheng	🇹🇼 CHINESE TAIPEI	51	88.2%	0.18
31	M.Iher	🇪🇪 ESTONIA	55	87.3%	0.14
32	S.Laan	🇪🇪 ESTONIA	55	87.3%	0.14
33	A.Bauer	🇩🇪 GERMANY	46	87.0%	0.17
34	P.Petrov	🇩🇪 GERMANY	46	87.0%	0.17
35	M.Balodis	🇱🇻 LATVIA	52	86.5%	0.14
36	J.Ilzins	🇱🇻 LATVIA	52	86.5%	0.14
37	C.Welland	🇺🇸 USA2	52	86.5%	0.14
38	C.Nunez	🇦🇷 ARGENTINA	44	86.4%	0.18
39	R.Nunez	🇦🇷 ARGENTINA	44	86.4%	0.18
40	C.Chiang	🇹🇼 CHINESE TAIPEI	59	86.4%	0.20
41	J.Andruszkiewicz	🇵🇱 POLAND	51	86.3%	0.23
42	E.Sucharda	🇵🇱 POLAND	51	86.3%	0.23
43	J.Lieberman	🇺🇸 USA2	50	86.0%	0.14
44	R.Bloch	🇫🇷 FRANCE	50	86.0%	0.16
45	E.Vallet	🇫🇷 FRANCE	50	86.0%	0.16
46	S.Jesse	🇩🇪 GERMANY	56	85.7%	0.18
47	Y.Tian	🇩🇪 GERMANY	56	85.7%	0.18
48	H.Gao	🇨🇳 CHINA	48	85.4%	0.17
49	A.Hutton	🏴󠁧󠁢󠁥󠁮󠁧󠁿 ENGLAND	81	85.2%	0.17
50	O.Powell	🏴󠁧󠁢󠁥󠁮󠁧󠁿 ENGLAND	81	85.2%	0.17
51	Z.Ferov	🇧🇬 BULGARIA	61	85.2%	0.18
52	Z.Chu	🇨🇳 CHINA	52	84.6%	0.17
53	N.Tennant	🏴󠁧󠁢󠁳󠁣󠁴󠁿 SCOTLAND	65	84.6%	0.18
54	G.Donati	🇮🇹 ITALY	56	83.9%	0.18
55	G.Percario	🇮🇹 ITALY	56	83.9%	0.18
56	J.Shearer	🏴󠁧󠁢󠁳󠁣󠁴󠁿 SCOTLAND	62	83.9%	0.19
57	J.Clark	🏴󠁧󠁢󠁥󠁮󠁧󠁿 ENGLAND	80	83.8%	0.17
58	K.Panchagnula	🏴󠁧󠁢󠁥󠁮󠁧󠁿 ENGLAND	80	83.8%	0.17
59	S.Pepic	🇷🇸 SERBIA	68	83.8%	0.22
60	M.Simic	🇷🇸 SERBIA	68	83.8%	0.22
61	A.Casparie	🇳🇱 NETHERLANDS	43	83.7%	0.21
62	M.Sprinkhuizen	🇳🇱 NETHERLANDS	43	83.7%	0.21
63	M.Johnstone	🇺🇸 USA1	73	83.6%	0.16
64	J.Udomsrirungruang	🇺🇸 USA1	73	83.6%	0.16
65	S.Chatterjee	🇮🇳 INDIA	47	83.0%	0.17
66	P.Dey	🇮🇳 INDIA	47	83.0%	0.17
67	A.Huang	🏴󠁧󠁢󠁳󠁣󠁴󠁿 SCOTLAND	41	82.9%	0.22
68	H.Koh	🇸🇬 SINGAPORE	58	82.8%	0.24
69	J.Ong	🇸🇬 SINGAPORE	58	82.8%	0.24
70	J.Middleton	🏴󠁧󠁢󠁳󠁣󠁴󠁿 SCOTLAND	46	82.6%	0.24
71	D.Nobira	🇮🇩 INDONESIA	51	82.4%	0.22
72	D.Rahayu	🇮🇩 INDONESIA	51	82.4%	0.22
73	D.Lee	🇸🇬 SINGAPORE	56	82.1%	0.20
74	S.Wu	🇸🇬 SINGAPORE	56	82.1%	0.20
75	D.Lazarov	🇧🇬 BULGARIA	56	82.1%	0.21
76	M.Satriawan	🇮🇩 INDONESIA	50	82.0%	0.18
77	S.Wijayanto	🇮🇩 INDONESIA	50	82.0%	0.18
78	R.Toom	🇪🇪 ESTONIA	44	81.8%	0.20
79	R.Zvorovski	🇪🇪 ESTONIA	44	81.8%	0.20
80	S.Bar	🇮🇳 INDIA	49	81.6%	0.20
81	S.Kar	🇮🇳 INDIA	49	81.6%	0.20
82	Z.Zhu	🇩🇪 GERMANY	43	81.4%	0.26
83	Y.Zuo	🇩🇪 GERMANY	43	81.4%	0.26
84	A.Boonstra	🇳🇱 NETHERLANDS	47	80.9%	0.28
85	B.Van Noort	🇳🇱 NETHERLANDS	47	80.9%	0.28
86	I.Miquelez Caballero	🇦🇷 ARGENTINA	56	80.4%	0.25
87	N.Tiscornia Biaus	🇦🇷 ARGENTINA	56	80.4%	0.25
88	R.Emmers	🇳🇱 NETHERLANDS	46	80.4%	0.26
89	W.Klarenbeek	🇳🇱 NETHERLANDS	46	80.4%	0.26
90	V.Zhu	🇺🇸 USA2	56	80.4%	0.27
91	H.Gao	🇸🇬 SINGAPORE	50	80.0%	0.26
92	R.Lee	🇸🇬 SINGAPORE	50	80.0%	0.26
93	C.Lin	🇹🇼 CHINESE TAIPEI	59	79.7%	0.24
94	A.Dhir	🇺🇸 USA2	59	79.7%	0.27
95	Y.Li	🇨🇳 CHINA	49	79.6%	0.24
96	Q.Tan	🇨🇳 CHINA	49	79.6%	0.24
97	R.Shaumi	🇮🇩 INDONESIA	44	79.5%	0.27
98	D.Tarabunga	🇮🇩 INDONESIA	44	79.5%	0.27
99	P.Cazabon	🇨🇱 CHILE	72	79.2%	0.26
100	F.Nacrur	🇨🇱 CHILE	72	79.2%	0.26
101	R.Luhaorg	🇪🇪 ESTONIA	46	78.3%	0.24
102	R.Piirisild	🇪🇪 ESTONIA	46	78.3%	0.24
103	S.Li	🇹🇼 CHINESE TAIPEI	59	78.0%	0.27
104	D.Jansons	🇱🇻 LATVIA	44	77.3%	0.29
105	R.Kreitals	🇱🇻 LATVIA	44	77.3%	0.29
106	E.Olla	🇱🇻 LATVIA	58	75.9%	0.28
107	T.Straume	🇱🇻 LATVIA	58	75.9%	0.28
108	D.Murray	🏴󠁧󠁢󠁳󠁣󠁴󠁿 SCOTLAND	44	75.0%	0.34
109	E.Gardner	🏴󠁧󠁢󠁳󠁣󠁴󠁿 SCOTLAND	36	72.2%	0.36
110	N.Davila	🇨🇱 CHILE	83	69.9%	0.37
111	B.Perez	🇨🇱 CHILE	83	69.9%	0.37
112	S.Guzvica	🇷🇸 SERBIA	22	90.9%	0.14
113	B.Velickovic	🇷🇸 SERBIA	22	90.9%	0.14

Bidding activity↑ top

Share of a player’s bids that were not a pass — contract bids, doubles and redoubles, over every auction they sat in. High = active, low = quiet. Players with few boards are greyed. Click a column header to sort; filter by name or team.

#	Player	Team	Bids	Not pass	Active %
1	T.Guichet	🇫🇷 FRANCE	299	164	54.8%
2	C.Deheeger	🇫🇷 FRANCE	260	132	50.8%
3	M.Sprinkhuizen	🇳🇱 NETHERLANDS	295	148	50.2%
4	R.Emmers	🇳🇱 NETHERLANDS	287	144	50.2%
5	J.Middleton	🏴󠁧󠁢󠁳󠁣󠁴󠁿 SCOTLAND	314	157	50.0%
6	A.Momov	🇧🇬 BULGARIA	186	93	50.0%
7	R.Luhaorg	🇪🇪 ESTONIA	293	146	49.8%
8	S.Vazic	🇷🇸 SERBIA	341	169	49.6%
9	G.Percario	🇮🇹 ITALY	360	177	49.2%
10	L.Bellicaud	🇫🇷 FRANCE	305	150	49.2%
11	Z.Ferov	🇧🇬 BULGARIA	399	196	49.1%
12	Z.Zhu	🇩🇪 GERMANY	287	141	49.1%
13	Y.Zuo	🇩🇪 GERMANY	291	142	48.8%
14	R.Nunez	🇦🇷 ARGENTINA	315	152	48.3%
15	R.Piirisild	🇪🇪 ESTONIA	292	141	48.3%
16	C.Nunez	🇦🇷 ARGENTINA	308	147	47.7%
17	J.Lieberman	🇺🇸 USA2	308	146	47.4%
18	B.Bejenka	🇵🇱 POLAND	302	143	47.4%
19	S.Pepic	🇷🇸 SERBIA	404	191	47.3%
20	T.Kielbasa	🇵🇱 POLAND	299	141	47.2%
21	A.Huang	🏴󠁧󠁢󠁳󠁣󠁴󠁿 SCOTLAND	297	140	47.1%
22	R.Toom	🇪🇪 ESTONIA	263	124	47.1%
23	S.Wijayanto	🇮🇩 INDONESIA	330	155	47.0%
24	D.Hsiao	🇹🇼 CHINESE TAIPEI	311	146	46.9%
25	M.Satriawan	🇮🇩 INDONESIA	329	154	46.8%
26	J.Ilzins	🇱🇻 LATVIA	327	153	46.8%
27	S.Wu	🇸🇬 SINGAPORE	295	138	46.8%
28	G.Donati	🇮🇹 ITALY	369	172	46.6%
29	A.Casparie	🇳🇱 NETHERLANDS	297	138	46.5%
30	R.Zvorovski	🇪🇪 ESTONIA	260	120	46.2%
31	E.Gardner	🏴󠁧󠁢󠁳󠁣󠁴󠁿 SCOTLAND	238	110	46.2%
32	H.Gao	🇨🇳 CHINA	292	134	45.9%
33	Y.Cheng	🇹🇼 CHINESE TAIPEI	244	112	45.9%
34	J.Udomsrirungruang	🇺🇸 USA1	427	195	45.7%
35	D.Lee	🇸🇬 SINGAPORE	296	134	45.3%
36	H.Gao	🇸🇬 SINGAPORE	247	112	45.3%
37	Y.Chen	🇹🇼 CHINESE TAIPEI	270	122	45.2%
38	P.Dey	🇮🇳 INDIA	273	123	45.1%
39	G.Giubilo	🇮🇹 ITALY	234	105	44.9%
40	S.Roy	🇮🇳 INDIA	338	151	44.7%
41	A.Yeung	🇺🇸 USA2	219	98	44.7%
42	C.Li	🇨🇳 CHINA	337	150	44.5%
43	S.Semberoiz	🇦🇷 ARGENTINA	288	128	44.4%
44	R.Sau	🇮🇹 ITALY	228	101	44.3%
45	ACHARYA SHUBHAM	🇮🇳 INDIA	344	152	44.2%
46	E.Sucharda	🇵🇱 POLAND	304	134	44.1%
47	S.Scata	🇮🇹 ITALY	296	130	43.9%
48	D.Jansons	🇱🇻 LATVIA	226	99	43.8%
49	F.Nacrur	🇨🇱 CHILE	426	186	43.7%
50	D.Tarabunga	🇮🇩 INDONESIA	229	100	43.7%
51	M.Johnstone	🇺🇸 USA1	427	186	43.6%
52	D.Lazarov	🇧🇬 BULGARIA	351	153	43.6%
53	Z.Chu	🇨🇳 CHINA	317	138	43.5%
54	J.Bereza	🇵🇱 POLAND	273	118	43.2%
55	B.Van Noort	🇳🇱 NETHERLANDS	266	115	43.2%
56	S.Li	🇹🇼 CHINESE TAIPEI	309	133	43.0%
57	A.Boonstra	🇳🇱 NETHERLANDS	268	115	42.9%
58	H.Xing	🇺🇸 USA1	411	176	42.8%
59	J.Clark	🏴󠁧󠁢󠁥󠁮󠁧󠁿 ENGLAND	426	182	42.7%
60	A.Bauer	🇩🇪 GERMANY	291	124	42.6%
61	D.Murray	🏴󠁧󠁢󠁳󠁣󠁴󠁿 SCOTLAND	275	117	42.5%
62	Y.Huang	🇺🇸 USA2	240	102	42.5%
63	F.Guerra	🇦🇷 ARGENTINA	283	120	42.4%
64	P.Petrov	🇩🇪 GERMANY	286	121	42.3%
65	P.Bedouet	🇫🇷 FRANCE	274	116	42.3%
66	R.Shaumi	🇮🇩 INDONESIA	234	99	42.3%
67	P.Cazabon	🇨🇱 CHILE	429	181	42.2%
68	W.Klarenbeek	🇳🇱 NETHERLANDS	289	122	42.2%
69	R.Kreitals	🇱🇻 LATVIA	225	95	42.2%
70	M.Iher	🇪🇪 ESTONIA	274	115	42.0%
71	M.Seizovic	🇷🇸 SERBIA	351	147	41.9%
72	C.Chiang	🇹🇼 CHINESE TAIPEI	301	125	41.5%
73	N.Tiscornia Biaus	🇦🇷 ARGENTINA	282	117	41.5%
74	P.Beer	🇺🇸 USA1	419	173	41.3%
75	M.Simic	🇷🇸 SERBIA	408	168	41.2%
76	I.Miquelez Caballero	🇦🇷 ARGENTINA	284	117	41.2%
77	B.Kula	🇵🇱 POLAND	279	114	40.9%
78	D.Rahayu	🇮🇩 INDONESIA	294	120	40.8%
79	E.Vallet	🇫🇷 FRANCE	292	119	40.8%
80	J.Andruszkiewicz	🇵🇱 POLAND	313	127	40.6%
81	S.Kar	🇮🇳 INDIA	240	97	40.4%
82	O.Powell	🏴󠁧󠁢󠁥󠁮󠁧󠁿 ENGLAND	444	179	40.3%
83	N.Davila	🇨🇱 CHILE	437	176	40.3%
84	X.Liu	🇨🇳 CHINA	320	129	40.3%
85	C.Welland	🇺🇸 USA2	318	128	40.3%
86	S.Jesse	🇩🇪 GERMANY	288	116	40.3%
87	M.Andonov	🇧🇬 BULGARIA	403	162	40.2%
88	M.Balodis	🇱🇻 LATVIA	338	136	40.2%
89	V.Zhu	🇺🇸 USA2	276	111	40.2%
90	E.Olla	🇱🇻 LATVIA	303	121	39.9%
91	D.Nobira	🇮🇩 INDONESIA	298	118	39.6%
92	A.Dhir	🇺🇸 USA2	294	116	39.5%
93	Q.Tan	🇨🇳 CHINA	222	87	39.2%
94	B.Perez	🇨🇱 CHILE	441	172	39.0%
95	A.Hutton	🏴󠁧󠁢󠁥󠁮󠁧󠁿 ENGLAND	441	172	39.0%
96	T.Straume	🇱🇻 LATVIA	295	115	39.0%
97	A.Manganella	🇮🇹 ITALY	307	119	38.8%
98	R.Bloch	🇫🇷 FRANCE	292	112	38.4%
99	S.Chatterjee	🇮🇳 INDIA	286	109	38.1%
100	J.Ong	🇸🇬 SINGAPORE	308	117	38.0%
101	J.Shearer	🏴󠁧󠁢󠁳󠁣󠁴󠁿 SCOTLAND	284	108	38.0%
102	Y.Li	🇨🇳 CHINA	225	85	37.8%
103	H.Koh	🇸🇬 SINGAPORE	309	116	37.5%
104	K.Panchagnula	🏴󠁧󠁢󠁥󠁮󠁧󠁿 ENGLAND	434	161	37.1%
105	N.Tennant	🏴󠁧󠁢󠁳󠁣󠁴󠁿 SCOTLAND	299	111	37.1%
106	C.Lin	🇹🇼 CHINESE TAIPEI	308	114	37.0%
107	T.Pavlov	🇧🇬 BULGARIA	350	129	36.9%
108	Y.Tian	🇩🇪 GERMANY	288	103	35.8%
109	R.Lee	🇸🇬 SINGAPORE	252	90	35.7%
110	S.Laan	🇪🇪 ESTONIA	275	97	35.3%
111	S.Bar	🇮🇳 INDIA	244	86	35.2%
112	S.Guzvica	🇷🇸 SERBIA	105	50	47.6%
113	B.Velickovic	🇷🇸 SERBIA	111	41	36.9%

Strength of schedule — opponent-adjusted Butler↑ top

On every board a player meets a specific opposing pair, and strong opponents defend and bid well — which quietly depresses your cross-IMP. Opp /bd is the mean cumulative Butler of the pairs faced, i.e. the strength of the draw (+ tough, − easy). Adj /bd adds it back — a tough draw is credited, an easy one discounted — and Δ is the resulting move against the raw Butler order. Regulars only (≥ 40% of the boards). Click a column header to sort; filter by name or team.

#	Player	Team	Boards	Opp /bd	Raw /bd	Adj /bd	Δ
1	ACHARYA SHUBHAM	🇮🇳 INDIA	120	-0.02	+1.13	+1.11	·
2	S.Roy	🇮🇳 INDIA	120	-0.02	+1.13	+1.11	·
3	M.Andonov	🇧🇬 BULGARIA	144	+0.03	+0.74	+0.77	▲4
4	T.Pavlov	🇧🇬 BULGARIA	128	+0.09	+0.67	+0.76	▲4
5	Z.Chu	🇨🇳 CHINA	112	+0.10	+0.66	+0.76	▲6
6	H.Gao	🇨🇳 CHINA	104	+0.15	+0.60	+0.75	▲7
7	G.Donati	🇮🇹 ITALY	128	-0.09	+0.79	+0.70	▼2
8	G.Percario	🇮🇹 ITALY	128	-0.09	+0.79	+0.70	▼2
9	R.Emmers	🇳🇱 NETHERLANDS	104	-0.22	+0.91	+0.69	▼6
10	W.Klarenbeek	🇳🇱 NETHERLANDS	104	-0.22	+0.91	+0.69	▼6
11	Y.Chen	🇹🇼 CHINESE TAIPEI	96	-0.04	+0.64	+0.60	▲1
12	M.Seizovic	🇷🇸 SERBIA	128	+0.09	+0.46	+0.55	▲7
13	S.Vazic	🇷🇸 SERBIA	128	+0.09	+0.46	+0.55	▲7
14	J.Andruszkiewicz	🇵🇱 POLAND	104	+0.27	+0.26	+0.52	▲26
15	E.Sucharda	🇵🇱 POLAND	104	+0.27	+0.26	+0.52	▲26
16	Z.Ferov	🇧🇬 BULGARIA	144	-0.02	+0.53	+0.51	▼2
17	H.Koh	🇸🇬 SINGAPORE	104	-0.18	+0.67	+0.49	▼8
18	J.Ong	🇸🇬 SINGAPORE	104	-0.18	+0.67	+0.49	▼8
19	R.Bloch	🇫🇷 FRANCE	104	+0.02	+0.44	+0.46	▲4
20	E.Vallet	🇫🇷 FRANCE	104	+0.02	+0.44	+0.46	▲4
21	A.Momov	🇧🇬 BULGARIA	64	+0.06	+0.35	+0.41	▲10
22	L.Bellicaud	🇫🇷 FRANCE	112	-0.08	+0.47	+0.39	▼5
23	T.Guichet	🇫🇷 FRANCE	112	-0.08	+0.47	+0.39	▼5
24	B.Bejenka	🇵🇱 POLAND	104	-0.13	+0.48	+0.35	▼9
25	T.Kielbasa	🇵🇱 POLAND	104	-0.13	+0.48	+0.35	▼9
26	D.Hsiao	🇹🇼 CHINESE TAIPEI	112	-0.07	+0.41	+0.34	▼1
27	P.Beer	🇺🇸 USA1	152	+0.06	+0.28	+0.34	▲9
28	H.Xing	🇺🇸 USA1	152	+0.06	+0.28	+0.34	▲9
29	D.Lazarov	🇧🇬 BULGARIA	128	+0.02	+0.32	+0.34	▲3
30	Y.Li	🇨🇳 CHINA	80	-0.05	+0.38	+0.33	▼2
31	Q.Tan	🇨🇳 CHINA	80	-0.05	+0.38	+0.33	▼2
32	M.Balodis	🇱🇻 LATVIA	120	+0.05	+0.26	+0.31	▲6
33	J.Ilzins	🇱🇻 LATVIA	120	+0.05	+0.26	+0.31	▲6
34	A.Boonstra	🇳🇱 NETHERLANDS	96	-0.15	+0.45	+0.30	▼13
35	B.Van Noort	🇳🇱 NETHERLANDS	96	-0.15	+0.45	+0.30	▼13
36	J.Bereza	🇵🇱 POLAND	96	-0.15	+0.41	+0.26	▼10
37	B.Kula	🇵🇱 POLAND	96	-0.15	+0.41	+0.26	▼10
38	P.Cazabon	🇨🇱 CHILE	152	-0.06	+0.31	+0.24	▼5
39	F.Nacrur	🇨🇱 CHILE	152	-0.06	+0.31	+0.24	▼5
40	C.Li	🇨🇳 CHINA	120	-0.17	+0.36	+0.19	▼10
41	D.Jansons	🇱🇻 LATVIA	80	+0.04	+0.12	+0.15	▲2
42	R.Kreitals	🇱🇻 LATVIA	80	+0.04	+0.12	+0.15	▲2
43	X.Liu	🇨🇳 CHINA	112	-0.14	+0.29	+0.15	▼8
44	R.Luhaorg	🇪🇪 ESTONIA	104	-0.03	+0.08	+0.06	▲1
45	R.Piirisild	🇪🇪 ESTONIA	104	-0.03	+0.08	+0.06	▲1
46	A.Manganella	🇮🇹 ITALY	104	+0.04	+0.01	+0.06	▲2
47	S.Scata	🇮🇹 ITALY	104	+0.04	+0.01	+0.06	▲2
48	S.Li	🇹🇼 CHINESE TAIPEI	104	-0.18	+0.21	+0.03	▼6
49	E.Olla	🇱🇻 LATVIA	104	+0.04	-0.05	-0.01	▲1
50	T.Straume	🇱🇻 LATVIA	104	+0.04	-0.05	-0.01	▲1
51	M.Johnstone	🇺🇸 USA1	152	+0.11	-0.15	-0.04	▲14
52	J.Udomsrirungruang	🇺🇸 USA1	152	+0.11	-0.15	-0.04	▲14
53	V.Zhu	🇺🇸 USA2	104	+0.07	-0.13	-0.06	▲11
54	C.Welland	🇺🇸 USA2	112	+0.03	-0.11	-0.08	▲7
55	M.Iher	🇪🇪 ESTONIA	104	-0.03	-0.06	-0.09	▼3
56	S.Laan	🇪🇪 ESTONIA	104	-0.03	-0.06	-0.09	▼3
57	I.Miquelez Caballero	🇦🇷 ARGENTINA	96	-0.03	-0.07	-0.10	▼3
58	N.Tiscornia Biaus	🇦🇷 ARGENTINA	96	-0.03	-0.07	-0.10	▼3
59	F.Guerra	🇦🇷 ARGENTINA	104	+0.02	-0.12	-0.10	▲3
60	S.Semberoiz	🇦🇷 ARGENTINA	104	+0.02	-0.12	-0.10	▲3
61	J.Lieberman	🇺🇸 USA2	112	-0.02	-0.09	-0.11	▼3
62	C.Nunez	🇦🇷 ARGENTINA	104	-0.05	-0.08	-0.12	▼6
63	R.Nunez	🇦🇷 ARGENTINA	104	-0.05	-0.08	-0.12	▼6
64	A.Huang	🏴󠁧󠁢󠁳󠁣󠁴󠁿 SCOTLAND	104	-0.16	+0.01	-0.15	▼17
65	A.Dhir	🇺🇸 USA2	112	+0.01	-0.16	-0.15	▲2
66	G.Giubilo	🇮🇹 ITALY	72	-0.11	-0.10	-0.21	▼7
67	R.Sau	🇮🇹 ITALY	72	-0.11	-0.10	-0.21	▼7
68	S.Jesse	🇩🇪 GERMANY	104	+0.18	-0.40	-0.22	▲18
69	Y.Tian	🇩🇪 GERMANY	104	+0.18	-0.40	-0.22	▲18
70	M.Satriawan	🇮🇩 INDONESIA	120	+0.01	-0.25	-0.24	▲2
71	S.Wijayanto	🇮🇩 INDONESIA	120	+0.01	-0.25	-0.24	▲2
72	N.Davila	🇨🇱 CHILE	152	+0.07	-0.32	-0.25	▲8
73	B.Perez	🇨🇱 CHILE	152	+0.07	-0.32	-0.25	▲8
74	E.Gardner	🏴󠁧󠁢󠁳󠁣󠁴󠁿 SCOTLAND	80	+0.18	-0.43	-0.25	▲17
75	D.Lee	🇸🇬 SINGAPORE	104	+0.20	-0.46	-0.26	▲19
76	S.Wu	🇸🇬 SINGAPORE	104	+0.20	-0.46	-0.26	▲19
77	R.Shaumi	🇮🇩 INDONESIA	80	+0.01	-0.32	-0.31	▲1
78	D.Tarabunga	🇮🇩 INDONESIA	80	+0.01	-0.32	-0.31	▲1
79	S.Bar	🇮🇳 INDIA	88	-0.13	-0.18	-0.31	▼11
80	S.Kar	🇮🇳 INDIA	88	-0.13	-0.18	-0.31	▼11
81	Z.Zhu	🇩🇪 GERMANY	104	-0.08	-0.24	-0.32	▼11
82	Y.Zuo	🇩🇪 GERMANY	104	-0.08	-0.24	-0.32	▼11
83	A.Hutton	🏴󠁧󠁢󠁥󠁮󠁧󠁿 ENGLAND	152	+0.11	-0.48	-0.37	▲13
84	O.Powell	🏴󠁧󠁢󠁥󠁮󠁧󠁿 ENGLAND	152	+0.11	-0.48	-0.37	▲13
85	J.Clark	🏴󠁧󠁢󠁥󠁮󠁧󠁿 ENGLAND	152	-0.09	-0.29	-0.38	▼10
86	K.Panchagnula	🏴󠁧󠁢󠁥󠁮󠁧󠁿 ENGLAND	152	-0.09	-0.29	-0.38	▼10
87	A.Casparie	🇳🇱 NETHERLANDS	104	+0.20	-0.59	-0.38	▲12
88	M.Sprinkhuizen	🇳🇱 NETHERLANDS	104	+0.20	-0.59	-0.38	▲12
89	S.Chatterjee	🇮🇳 INDIA	96	+0.04	-0.44	-0.40	▲3
90	P.Dey	🇮🇳 INDIA	96	+0.04	-0.44	-0.40	▲3
91	C.Lin	🇹🇼 CHINESE TAIPEI	104	-0.13	-0.28	-0.41	▼17
92	S.Pepic	🇷🇸 SERBIA	136	-0.10	-0.32	-0.42	▼10
93	M.Simic	🇷🇸 SERBIA	136	-0.10	-0.32	-0.42	▼10
94	N.Tennant	🏴󠁧󠁢󠁳󠁣󠁴󠁿 SCOTLAND	112	+0.15	-0.58	-0.43	▲4
95	C.Chiang	🇹🇼 CHINESE TAIPEI	104	-0.06	-0.41	-0.46	▼7
96	J.Middleton	🏴󠁧󠁢󠁳󠁣󠁴󠁿 SCOTLAND	112	-0.08	-0.38	-0.47	▼11
97	H.Gao	🇸🇬 SINGAPORE	96	-0.06	-0.41	-0.47	▼8
98	R.Lee	🇸🇬 SINGAPORE	96	-0.06	-0.41	-0.47	▼8
99	P.Bedouet	🇫🇷 FRANCE	88	+0.14	-0.64	-0.51	▲2
100	C.Deheeger	🇫🇷 FRANCE	88	+0.14	-0.64	-0.51	▲2
101	A.Yeung	🇺🇸 USA2	80	-0.20	-0.31	-0.52	▼24
102	D.Murray	🏴󠁧󠁢󠁳󠁣󠁴󠁿 SCOTLAND	96	+0.22	-0.73	-0.52	▲2
103	J.Shearer	🏴󠁧󠁢󠁳󠁣󠁴󠁿 SCOTLAND	104	+0.17	-0.70	-0.53	·
104	Y.Huang	🇺🇸 USA2	88	-0.19	-0.37	-0.56	▼20
105	R.Toom	🇪🇪 ESTONIA	96	+0.06	-0.80	-0.74	·
106	R.Zvorovski	🇪🇪 ESTONIA	96	+0.06	-0.80	-0.74	·
107	Y.Cheng	🇹🇼 CHINESE TAIPEI	88	+0.04	-0.89	-0.85	·
108	D.Nobira	🇮🇩 INDONESIA	104	+0.03	-0.90	-0.88	·
109	D.Rahayu	🇮🇩 INDONESIA	104	+0.03	-0.90	-0.88	·
110	A.Bauer	🇩🇪 GERMANY	96	+0.12	-1.00	-0.89	·
111	P.Petrov	🇩🇪 GERMANY	96	+0.12	-1.00	-0.89	·

Stages

Statistics

Tables