Bangkok 2006 — 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	E.Argelazi	🇮🇱 ISRAEL	200	+1.68	+336.0
2	A.Birman	🇮🇱 ISRAEL	200	+1.68	+336.0
3	K.Dwyer Rimstedt	🇺🇸 USA RED	260	+1.00	+259.0
4	O.Lien	🇺🇸 USA RED	260	+1.00	+259.0
5	C.Rimstedt	🇸🇪 SWEDEN	260	+0.84	+218.0
6	D.Padon	🇮🇱 ISRAEL	200	+0.78	+155.0
7	B.Tarnovski	🇮🇱 ISRAEL	200	+0.78	+155.0
8	J.Balasovs	🇱🇻 LATVIA	300	+0.76	+227.0
9	J.Bethers	🇱🇻 LATVIA	300	+0.76	+227.0
10	M.Lorencs	🇱🇻 LATVIA	220	+0.74	+163.0
11	P.Hollands	🇦🇺 AUSTRALIA	180	+0.73	+131.0
12	P.Butryn	🇵🇱 POLAND	180	+0.69	+125.0
13	M.Sikora	🇵🇱 POLAND	180	+0.69	+125.0
14	A.Hung	🇦🇺 AUSTRALIA	220	+0.66	+146.0
15	A.Edgtton	🇦🇺 AUSTRALIA	220	+0.59	+130.0
16	N.Edgtton	🇦🇺 AUSTRALIA	220	+0.59	+130.0
17	L.Johansen	🇳🇴 NORWAY	180	+0.59	+106.0
18	J.Krawczyk	🇵🇱 POLAND	220	+0.59	+129.0
19	A.Wasiak	🇵🇱 POLAND	220	+0.59	+129.0
20	C.Lai	🇭🇰 CHINA HONG KONG	200	+0.56	+113.0
21	R.Segev	🇮🇱 ISRAEL	200	+0.55	+110.0
22	D.Tal	🇮🇱 ISRAEL	200	+0.55	+110.0
23	H.Bogen	🇳🇴 NORWAY	280	+0.54	+150.0
24	D.Banh	🇺🇸 USA RED	240	+0.47	+112.0
25	J.Fournier	🇺🇸 USA RED	240	+0.47	+112.0
26	S.Bech	🇸🇪 SWEDEN	260	+0.42	+108.0
27	E.Skjetne	🇳🇴 NORWAY	240	+0.37	+89.0
28	Y.Cheng	🇹🇼 CHINESE TAIPEI	200	+0.33	+66.0
29	K.Wang	🇹🇼 CHINESE TAIPEI	200	+0.33	+66.0
30	H.Lee	🇭🇰 CHINA HONG KONG	220	+0.29	+63.0
31	A.Imsa	🇱🇻 LATVIA	200	+0.28	+57.0
32	S.Simonsen	🇳🇴 NORWAY	300	+0.26	+77.0
33	G.Delle Cave	🇮🇹 ITALY	300	+0.26	+77.0
34	R.Fellus	🇮🇹 ITALY	300	+0.26	+77.0
35	D.Goldfein	🇺🇸 USA BLUE	300	+0.25	+75.0
36	S.Katz	🇺🇸 USA BLUE	300	+0.25	+75.0
37	J.Mill	🇦🇺 AUSTRALIA	200	+0.25	+50.0
38	C.Lin	🇹🇼 CHINESE TAIPEI	220	+0.22	+49.0
39	Y.Ou-Yang	🇹🇼 CHINESE TAIPEI	220	+0.22	+49.0
40	M.De Livera	🇦🇺 AUSTRALIA	160	+0.22	+35.0
41	T.Koo	🇭🇰 CHINA HONG KONG	179	+0.20	+35.0
42	C.Poon	🇭🇰 CHINA HONG KONG	179	+0.20	+35.0
43	E.Fryklund	🇸🇪 SWEDEN	240	+0.19	+45.0
44	B.Igla	🇵🇱 POLAND	200	+0.18	+37.0
45	A.Machno	🇵🇱 POLAND	200	+0.18	+37.0
46	S.Butt	🇵🇰 PAKISTAN	180	+0.10	+18.0
47	Z.Khan	🇵🇰 PAKISTAN	300	+0.08	+25.0
48	P.Bethers	🇱🇻 LATVIA	180	+0.08	+14.0
49	R.Glickman	🇺🇸 USA BLUE	300	+0.04	+12.0
50	M.Meckstroth	🇺🇸 USA BLUE	300	+0.04	+12.0
51	H.Macaulay	🇨🇦 CANADA	199	-0.04	-7.0
52	H.Eide	🇳🇴 NORWAY	200	-0.09	-18.0
53	A.Blagov	🇨🇦 CANADA	300	-0.11	-33.0
54	O.Bashir	🇵🇰 PAKISTAN	240	-0.13	-31.0
55	S.Rimstedt	🇸🇪 SWEDEN	220	-0.14	-30.0
56	P.Lerdmaharit	🇹🇭 THAILAND	180	-0.16	-28.0
57	S.Siriwatthannsest	🇹🇭 THAILAND	180	-0.16	-28.0
58	M.Mccoll	🇨🇦 CANADA	280	-0.23	-63.0
59	H.Saeed	🇵🇰 PAKISTAN	180	-0.24	-44.0
60	L.Kuo	🇹🇼 CHINESE TAIPEI	180	-0.27	-49.0
61	H.So	🇹🇼 CHINESE TAIPEI	180	-0.27	-49.0
62	H.Malik	🇵🇰 PAKISTAN	300	-0.27	-82.0
63	K.Cao	🇨🇳 CHINA	300	-0.36	-107.0
64	H.Wang	🇨🇳 CHINA	300	-0.36	-107.0
65	F.Masloman	🇮🇩 INDONESIA	260	-0.45	-116.0
66	C.Tirayoh	🇮🇩 INDONESIA	260	-0.45	-116.0
67	E.Sjoberg	🇸🇪 SWEDEN	220	-0.46	-101.0
68	A.Iaboni	🇨🇦 CANADA	199	-0.76	-151.0
69	E.Macaulay	🇨🇦 CANADA	220	-0.90	-198.0
70	T.Fok	🇭🇰 CHINA HONG KONG	200	-0.92	-183.0
71	P.Ng	🇭🇰 CHINA HONG KONG	220	-1.06	-233.0
72	A.Cattabiani	🇮🇹 ITALY	160	-1.08	-173.0
73	M.Presti	🇮🇹 ITALY	160	-1.08	-173.0
74	X.Wu	🇨🇳 CHINA	300	-1.16	-347.0
75	W.Yuan	🇨🇳 CHINA	300	-1.16	-347.0
76	N.Junthiang	🇹🇭 THAILAND	220	-1.30	-287.0
77	S.Sansuwan	🇹🇭 THAILAND	220	-1.30	-287.0
78	L.Fruscoloni	🇮🇹 ITALY	140	-1.37	-192.0
79	G.Trimarchi	🇮🇹 ITALY	140	-1.37	-192.0
80	T.Raweejarusroung	🇹🇭 THAILAND	200	-1.53	-306.0
81	B.Udomwatwong	🇹🇭 THAILAND	200	-1.53	-306.0
82	G.Lasut	🇮🇩 INDONESIA	280	-1.70	-477.0
83	A.Polly	🇮🇩 INDONESIA	280	-1.70	-477.0
84	M.Beck	🇺🇸 USA RED	100	-0.10	-10.0
85	J.Chiu	🇺🇸 USA RED	100	-0.10	-10.0
86	A.Gosal	🇮🇩 INDONESIA	60	-0.98	-59.0
87	M.Kandow	🇮🇩 INDONESIA	60	-0.98	-59.0

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	D.Goldfein	🇺🇸 USA BLUE	62	96.8%	0.07
2	J.Fournier	🇺🇸 USA RED	54	94.4%	0.06
3	C.Poon	🇭🇰 CHINA HONG KONG	41	92.7%	0.07
4	A.Birman	🇮🇱 ISRAEL	52	90.4%	0.10
5	A.Cattabiani	🇮🇹 ITALY	27	88.9%	0.15
6	A.Blagov	🇨🇦 CANADA	60	88.3%	0.18
7	C.Lai	🇭🇰 CHINA HONG KONG	55	87.3%	0.13
8	A.Edgtton	🇦🇺 AUSTRALIA	46	87.0%	0.13
9	N.Junthiang	🇹🇭 THAILAND	54	87.0%	0.13
10	Y.Ou-Yang	🇹🇼 CHINESE TAIPEI	52	86.5%	0.17
11	L.Johansen	🇳🇴 NORWAY	49	85.7%	0.14
12	W.Yuan	🇨🇳 CHINA	83	85.5%	0.16
13	P.Butryn	🇵🇱 POLAND	47	85.1%	0.19
14	J.Krawczyk	🇵🇱 POLAND	59	84.7%	0.19
15	A.Machno	🇵🇱 POLAND	52	84.6%	0.15
16	H.Lee	🇭🇰 CHINA HONG KONG	58	84.5%	0.15
17	D.Padon	🇮🇱 ISRAEL	45	84.4%	0.16
18	A.Wasiak	🇵🇱 POLAND	51	84.3%	0.18
19	M.Sikora	🇵🇱 POLAND	44	84.1%	0.27
20	R.Glickman	🇺🇸 USA BLUE	56	83.9%	0.18
21	D.Banh	🇺🇸 USA RED	65	83.1%	0.20
22	X.Wu	🇨🇳 CHINA	71	83.1%	0.24
23	P.Ng	🇭🇰 CHINA HONG KONG	35	82.9%	0.17
24	M.De Livera	🇦🇺 AUSTRALIA	41	82.9%	0.20
25	O.Bashir	🇵🇰 PAKISTAN	63	82.5%	0.19
26	S.Butt	🇵🇰 PAKISTAN	45	82.2%	0.22
27	J.Balasovs	🇱🇻 LATVIA	77	81.8%	0.22
28	C.Lin	🇹🇼 CHINESE TAIPEI	60	81.7%	0.22
29	D.Tal	🇮🇱 ISRAEL	54	81.5%	0.26
30	L.Fruscoloni	🇮🇹 ITALY	32	81.2%	0.25
31	B.Tarnovski	🇮🇱 ISRAEL	52	80.8%	0.19
32	S.Sansuwan	🇹🇭 THAILAND	57	80.7%	0.23
33	C.Rimstedt	🇸🇪 SWEDEN	62	80.6%	0.19
34	P.Hollands	🇦🇺 AUSTRALIA	51	80.4%	0.22
35	A.Hung	🇦🇺 AUSTRALIA	45	80.0%	0.20
36	H.Saeed	🇵🇰 PAKISTAN	45	80.0%	0.20
37	H.Malik	🇵🇰 PAKISTAN	70	80.0%	0.21
38	H.Macaulay	🇨🇦 CANADA	50	80.0%	0.22
39	H.Wang	🇨🇳 CHINA	75	80.0%	0.23
40	H.Eide	🇳🇴 NORWAY	45	80.0%	0.24
41	B.Udomwatwong	🇹🇭 THAILAND	59	79.7%	0.22
42	A.Iaboni	🇨🇦 CANADA	49	79.6%	0.24
43	T.Koo	🇭🇰 CHINA HONG KONG	53	79.2%	0.23
44	H.Bogen	🇳🇴 NORWAY	72	79.2%	0.25
45	G.Delle Cave	🇮🇹 ITALY	67	79.1%	0.21
46	M.Lorencs	🇱🇻 LATVIA	57	78.9%	0.25
47	K.Dwyer Rimstedt	🇺🇸 USA RED	66	78.8%	0.23
48	M.Meckstroth	🇺🇸 USA BLUE	75	78.7%	0.24
49	P.Bethers	🇱🇻 LATVIA	47	78.7%	0.26
50	R.Fellus	🇮🇹 ITALY	74	78.4%	0.27
51	J.Mill	🇦🇺 AUSTRALIA	51	78.4%	0.29
52	B.Igla	🇵🇱 POLAND	60	78.3%	0.25
53	E.Sjoberg	🇸🇪 SWEDEN	60	78.3%	0.27
54	E.Skjetne	🇳🇴 NORWAY	68	77.9%	0.25
55	J.Bethers	🇱🇻 LATVIA	68	77.9%	0.25
56	K.Cao	🇨🇳 CHINA	67	77.6%	0.27
57	S.Katz	🇺🇸 USA BLUE	67	77.6%	0.30
58	T.Fok	🇭🇰 CHINA HONG KONG	62	77.4%	0.29
59	O.Lien	🇺🇸 USA RED	66	77.3%	0.27
60	H.So	🇹🇼 CHINESE TAIPEI	52	76.9%	0.25
61	M.Mccoll	🇨🇦 CANADA	69	76.8%	0.32
62	A.Polly	🇮🇩 INDONESIA	73	76.7%	0.26
63	S.Bech	🇸🇪 SWEDEN	77	76.6%	0.30
64	S.Siriwatthannsest	🇹🇭 THAILAND	51	76.5%	0.23
65	F.Masloman	🇮🇩 INDONESIA	62	75.8%	0.29
66	S.Simonsen	🇳🇴 NORWAY	70	75.7%	0.33
67	Z.Khan	🇵🇰 PAKISTAN	64	75.0%	0.28
68	E.Fryklund	🇸🇪 SWEDEN	68	75.0%	0.35
69	P.Lerdmaharit	🇹🇭 THAILAND	54	74.1%	0.26
70	K.Wang	🇹🇼 CHINESE TAIPEI	57	73.7%	0.28
71	S.Rimstedt	🇸🇪 SWEDEN	57	73.7%	0.32
72	A.Imsa	🇱🇻 LATVIA	53	73.6%	0.30
73	G.Trimarchi	🇮🇹 ITALY	30	73.3%	0.30
74	R.Segev	🇮🇱 ISRAEL	60	73.3%	0.38
75	G.Lasut	🇮🇩 INDONESIA	82	73.2%	0.30
76	L.Kuo	🇹🇼 CHINESE TAIPEI	43	72.1%	0.40
77	Y.Cheng	🇹🇼 CHINESE TAIPEI	60	71.7%	0.30
78	C.Tirayoh	🇮🇩 INDONESIA	53	71.7%	0.38
79	E.Macaulay	🇨🇦 CANADA	59	71.2%	0.29
80	M.Presti	🇮🇹 ITALY	38	71.1%	0.37
81	T.Raweejarusroung	🇹🇭 THAILAND	44	70.5%	0.34
82	N.Edgtton	🇦🇺 AUSTRALIA	53	67.9%	0.32
83	E.Argelazi	🇮🇱 ISRAEL	53	64.2%	0.41
84	M.Kandow	🇮🇩 INDONESIA	21	85.7%	0.19
85	A.Gosal	🇮🇩 INDONESIA	10	80.0%	0.20
86	M.Beck	🇺🇸 USA RED	22	77.3%	0.27
87	J.Chiu	🇺🇸 USA RED	26	76.9%	0.27

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	L.Kuo	🇹🇼 CHINESE TAIPEI	38	89.5%	0.18
2	C.Rimstedt	🇸🇪 SWEDEN	57	87.7%	0.16
3	K.Dwyer Rimstedt	🇺🇸 USA RED	52	86.5%	0.14
4	A.Machno	🇵🇱 POLAND	37	86.5%	0.22
5	B.Tarnovski	🇮🇱 ISRAEL	50	86.0%	0.14
6	A.Hung	🇦🇺 AUSTRALIA	56	85.7%	0.16
7	D.Padon	🇮🇱 ISRAEL	53	84.9%	0.24
8	M.Lorencs	🇱🇻 LATVIA	48	83.3%	0.19
9	K.Wang	🇹🇼 CHINESE TAIPEI	42	83.3%	0.26
10	E.Sjoberg	🇸🇪 SWEDEN	60	83.3%	0.27
11	E.Argelazi	🇮🇱 ISRAEL	46	82.6%	0.20
12	J.Krawczyk	🇵🇱 POLAND	55	81.8%	0.20
13	A.Wasiak	🇵🇱 POLAND	55	81.8%	0.20
14	A.Birman	🇮🇱 ISRAEL	48	81.2%	0.31
15	A.Blagov	🇨🇦 CANADA	98	80.6%	0.22
16	R.Segev	🇮🇱 ISRAEL	46	80.4%	0.24
17	H.Bogen	🇳🇴 NORWAY	64	79.7%	0.23
18	M.De Livera	🇦🇺 AUSTRALIA	33	78.8%	0.21
19	J.Mill	🇦🇺 AUSTRALIA	56	78.6%	0.25
20	M.Sikora	🇵🇱 POLAND	42	78.6%	0.31
21	E.Fryklund	🇸🇪 SWEDEN	51	78.4%	0.23
22	C.Lai	🇭🇰 CHINA HONG KONG	46	78.3%	0.26
23	H.Eide	🇳🇴 NORWAY	50	78.0%	0.22
24	Y.Cheng	🇹🇼 CHINESE TAIPEI	41	78.0%	0.24
25	E.Skjetne	🇳🇴 NORWAY	53	77.4%	0.28
26	S.Simonsen	🇳🇴 NORWAY	84	77.4%	0.29
27	M.Meckstroth	🇺🇸 USA BLUE	93	77.4%	0.32
28	L.Johansen	🇳🇴 NORWAY	44	77.3%	0.25
29	J.Balasovs	🇱🇻 LATVIA	78	76.9%	0.31
30	B.Igla	🇵🇱 POLAND	51	76.5%	0.35
31	D.Goldfein	🇺🇸 USA BLUE	89	76.4%	0.38
32	H.So	🇹🇼 CHINESE TAIPEI	46	76.1%	0.30
33	P.Hollands	🇦🇺 AUSTRALIA	46	76.1%	0.33
34	A.Cattabiani	🇮🇹 ITALY	41	75.6%	0.37
35	A.Imsa	🇱🇻 LATVIA	53	75.5%	0.34
36	H.Macaulay	🇨🇦 CANADA	53	75.5%	0.34
37	R.Fellus	🇮🇹 ITALY	65	75.4%	0.35
38	Y.Ou-Yang	🇹🇼 CHINESE TAIPEI	48	75.0%	0.29
39	P.Bethers	🇱🇻 LATVIA	40	75.0%	0.38
40	P.Butryn	🇵🇱 POLAND	47	74.5%	0.32
41	J.Bethers	🇱🇻 LATVIA	77	74.0%	0.31
42	A.Iaboni	🇨🇦 CANADA	42	73.8%	0.29
43	H.Wang	🇨🇳 CHINA	87	73.6%	0.32
44	A.Polly	🇮🇩 INDONESIA	72	73.6%	0.33
45	N.Edgtton	🇦🇺 AUSTRALIA	67	73.1%	0.40
46	D.Tal	🇮🇱 ISRAEL	40	72.5%	0.28
47	G.Trimarchi	🇮🇹 ITALY	51	72.5%	0.41
48	F.Masloman	🇮🇩 INDONESIA	94	72.3%	0.37
49	R.Glickman	🇺🇸 USA BLUE	75	72.0%	0.32
50	G.Delle Cave	🇮🇹 ITALY	93	72.0%	0.33
51	S.Katz	🇺🇸 USA BLUE	82	72.0%	0.34
52	O.Lien	🇺🇸 USA RED	75	72.0%	0.37
53	H.Lee	🇭🇰 CHINA HONG KONG	53	71.7%	0.45
54	D.Banh	🇺🇸 USA RED	66	71.2%	0.39
55	T.Koo	🇭🇰 CHINA HONG KONG	45	71.1%	0.38
56	J.Fournier	🇺🇸 USA RED	55	70.9%	0.38
57	T.Fok	🇭🇰 CHINA HONG KONG	44	70.5%	0.46
58	S.Butt	🇵🇰 PAKISTAN	59	69.5%	0.42
59	H.Saeed	🇵🇰 PAKISTAN	45	68.9%	0.47
60	S.Siriwatthannsest	🇹🇭 THAILAND	38	68.4%	0.40
61	C.Poon	🇭🇰 CHINA HONG KONG	40	67.5%	0.38
62	E.Macaulay	🇨🇦 CANADA	58	67.2%	0.48
63	Z.Khan	🇵🇰 PAKISTAN	75	66.7%	0.41
64	S.Bech	🇸🇪 SWEDEN	62	66.1%	0.45
65	C.Lin	🇹🇼 CHINESE TAIPEI	59	66.1%	0.49
66	A.Edgtton	🇦🇺 AUSTRALIA	53	66.0%	0.41
67	P.Ng	🇭🇰 CHINA HONG KONG	67	65.7%	0.46
68	S.Rimstedt	🇸🇪 SWEDEN	46	65.2%	0.39
69	M.Presti	🇮🇹 ITALY	54	64.8%	0.44
70	K.Cao	🇨🇳 CHINA	71	64.8%	0.54
71	C.Tirayoh	🇮🇩 INDONESIA	51	64.7%	0.45
72	P.Lerdmaharit	🇹🇭 THAILAND	36	63.9%	0.47
73	H.Malik	🇵🇰 PAKISTAN	72	63.9%	0.47
74	O.Bashir	🇵🇰 PAKISTAN	61	63.9%	0.47
75	S.Sansuwan	🇹🇭 THAILAND	54	63.0%	0.48
76	L.Fruscoloni	🇮🇹 ITALY	27	63.0%	0.56
77	B.Udomwatwong	🇹🇭 THAILAND	59	62.7%	0.53
78	G.Lasut	🇮🇩 INDONESIA	52	61.5%	0.60
79	W.Yuan	🇨🇳 CHINA	70	61.4%	0.47
80	X.Wu	🇨🇳 CHINA	75	61.3%	0.56
81	T.Raweejarusroung	🇹🇭 THAILAND	38	60.5%	0.58
82	M.Mccoll	🇨🇦 CANADA	60	56.7%	0.62
83	N.Junthiang	🇹🇭 THAILAND	55	54.5%	0.58
84	M.Beck	🇺🇸 USA RED	25	84.0%	0.16
85	J.Chiu	🇺🇸 USA RED	27	74.1%	0.41
86	M.Kandow	🇮🇩 INDONESIA	14	71.4%	0.50
87	A.Gosal	🇮🇩 INDONESIA	15	60.0%	0.53

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	R.Segev	🇮🇱 ISRAEL	114	93.0%	0.08
2	D.Tal	🇮🇱 ISRAEL	114	93.0%	0.08
3	P.Butryn	🇵🇱 POLAND	91	91.2%	0.11
4	M.Sikora	🇵🇱 POLAND	91	91.2%	0.11
5	Y.Cheng	🇹🇼 CHINESE TAIPEI	117	90.6%	0.10
6	K.Wang	🇹🇼 CHINESE TAIPEI	117	90.6%	0.10
7	E.Argelazi	🇮🇱 ISRAEL	105	90.5%	0.12
8	A.Birman	🇮🇱 ISRAEL	105	90.5%	0.12
9	C.Lin	🇹🇼 CHINESE TAIPEI	112	90.2%	0.12
10	Y.Ou-Yang	🇹🇼 CHINESE TAIPEI	112	90.2%	0.12
11	J.Krawczyk	🇵🇱 POLAND	110	90.0%	0.12
12	A.Wasiak	🇵🇱 POLAND	110	90.0%	0.12
13	A.Edgtton	🇦🇺 AUSTRALIA	99	88.9%	0.17
14	N.Edgtton	🇦🇺 AUSTRALIA	99	88.9%	0.17
15	S.Butt	🇵🇰 PAKISTAN	86	88.4%	0.13
16	M.Lorencs	🇱🇻 LATVIA	119	88.2%	0.15
17	B.Igla	🇵🇱 POLAND	112	87.5%	0.15
18	A.Machno	🇵🇱 POLAND	112	87.5%	0.15
19	C.Rimstedt	🇸🇪 SWEDEN	147	87.1%	0.14
20	K.Dwyer Rimstedt	🇺🇸 USA RED	132	87.1%	0.17
21	O.Lien	🇺🇸 USA RED	132	87.1%	0.17
22	E.Skjetne	🇳🇴 NORWAY	131	87.0%	0.21
23	J.Balasovs	🇱🇻 LATVIA	145	86.9%	0.15
24	J.Bethers	🇱🇻 LATVIA	145	86.9%	0.15
25	S.Rimstedt	🇸🇪 SWEDEN	122	86.9%	0.20
26	H.Eide	🇳🇴 NORWAY	97	86.6%	0.20
27	G.Delle Cave	🇮🇹 ITALY	141	86.5%	0.16
28	R.Fellus	🇮🇹 ITALY	141	86.5%	0.16
29	L.Kuo	🇹🇼 CHINESE TAIPEI	95	86.3%	0.17
30	H.So	🇹🇼 CHINESE TAIPEI	95	86.3%	0.17
31	L.Johansen	🇳🇴 NORWAY	91	85.7%	0.17
32	S.Simonsen	🇳🇴 NORWAY	147	85.7%	0.20
33	R.Glickman	🇺🇸 USA BLUE	131	85.5%	0.17
34	M.Meckstroth	🇺🇸 USA BLUE	131	85.5%	0.17
35	M.De Livera	🇦🇺 AUSTRALIA	82	85.4%	0.26
36	A.Blagov	🇨🇦 CANADA	135	85.2%	0.17
37	P.Hollands	🇦🇺 AUSTRALIA	87	85.1%	0.26
38	P.Lerdmaharit	🇹🇭 THAILAND	105	84.8%	0.17
39	S.Siriwatthannsest	🇹🇭 THAILAND	105	84.8%	0.17
40	A.Imsa	🇱🇻 LATVIA	104	84.6%	0.18
41	P.Bethers	🇱🇻 LATVIA	91	84.6%	0.19
42	P.Ng	🇭🇰 CHINA HONG KONG	103	84.5%	0.17
43	D.Goldfein	🇺🇸 USA BLUE	129	84.5%	0.18
44	S.Katz	🇺🇸 USA BLUE	129	84.5%	0.18
45	H.Bogen	🇳🇴 NORWAY	142	84.5%	0.18
46	D.Padon	🇮🇱 ISRAEL	97	84.5%	0.19
47	B.Tarnovski	🇮🇱 ISRAEL	97	84.5%	0.19
48	M.Mccoll	🇨🇦 CANADA	128	84.4%	0.18
49	E.Sjoberg	🇸🇪 SWEDEN	114	84.2%	0.25
50	J.Mill	🇦🇺 AUSTRALIA	101	84.2%	0.28
51	T.Fok	🇭🇰 CHINA HONG KONG	94	84.0%	0.17
52	A.Hung	🇦🇺 AUSTRALIA	106	84.0%	0.28
53	H.Malik	🇵🇰 PAKISTAN	144	82.6%	0.21
54	H.Saeed	🇵🇰 PAKISTAN	84	81.0%	0.25
55	D.Banh	🇺🇸 USA RED	119	80.7%	0.25
56	J.Fournier	🇺🇸 USA RED	119	80.7%	0.25
57	Z.Khan	🇵🇰 PAKISTAN	143	80.4%	0.27
58	H.Macaulay	🇨🇦 CANADA	102	80.4%	0.28
59	S.Bech	🇸🇪 SWEDEN	142	80.3%	0.23
60	A.Cattabiani	🇮🇹 ITALY	65	80.0%	0.25
61	M.Presti	🇮🇹 ITALY	65	80.0%	0.25
62	T.Koo	🇭🇰 CHINA HONG KONG	94	79.8%	0.22
63	C.Poon	🇭🇰 CHINA HONG KONG	94	79.8%	0.22
64	E.Fryklund	🇸🇪 SWEDEN	123	79.7%	0.27
65	F.Masloman	🇮🇩 INDONESIA	115	79.1%	0.30
66	C.Tirayoh	🇮🇩 INDONESIA	115	79.1%	0.30
67	K.Cao	🇨🇳 CHINA	142	78.9%	0.27
68	H.Wang	🇨🇳 CHINA	142	78.9%	0.27
69	H.Lee	🇭🇰 CHINA HONG KONG	116	78.4%	0.25
70	C.Lai	🇭🇰 CHINA HONG KONG	107	77.6%	0.26
71	A.Iaboni	🇨🇦 CANADA	98	77.6%	0.28
72	O.Bashir	🇵🇰 PAKISTAN	117	76.9%	0.32
73	G.Lasut	🇮🇩 INDONESIA	155	76.8%	0.30
74	A.Polly	🇮🇩 INDONESIA	155	76.8%	0.30
75	T.Raweejarusroung	🇹🇭 THAILAND	103	75.7%	0.28
76	B.Udomwatwong	🇹🇭 THAILAND	103	75.7%	0.28
77	X.Wu	🇨🇳 CHINA	154	75.3%	0.29
78	W.Yuan	🇨🇳 CHINA	154	75.3%	0.29
79	E.Macaulay	🇨🇦 CANADA	111	73.0%	0.37
80	L.Fruscoloni	🇮🇹 ITALY	62	72.6%	0.34
81	G.Trimarchi	🇮🇹 ITALY	62	72.6%	0.34
82	N.Junthiang	🇹🇭 THAILAND	111	71.2%	0.35
83	S.Sansuwan	🇹🇭 THAILAND	111	71.2%	0.35
84	M.Beck	🇺🇸 USA RED	48	89.6%	0.10
85	J.Chiu	🇺🇸 USA RED	48	89.6%	0.10
86	A.Gosal	🇮🇩 INDONESIA	31	77.4%	0.29
87	M.Kandow	🇮🇩 INDONESIA	31	77.4%	0.29

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	E.Argelazi	🇮🇱 ISRAEL	200	+0.11	+1.44	+1.55	·
2	A.Birman	🇮🇱 ISRAEL	200	+0.11	+1.44	+1.55	·
3	A.Edgtton	🇦🇺 AUSTRALIA	220	+0.23	+0.71	+0.94	▲9
4	N.Edgtton	🇦🇺 AUSTRALIA	220	+0.23	+0.71	+0.94	▲9
5	M.Lorencs	🇱🇻 LATVIA	220	-0.09	+0.99	+0.90	▼2
6	J.Krawczyk	🇵🇱 POLAND	220	+0.16	+0.57	+0.72	▲12
7	A.Wasiak	🇵🇱 POLAND	220	+0.16	+0.57	+0.72	▲12
8	D.Padon	🇮🇱 ISRAEL	200	+0.06	+0.66	+0.72	▲6
9	B.Tarnovski	🇮🇱 ISRAEL	200	+0.06	+0.66	+0.72	▲6
10	A.Imsa	🇱🇻 LATVIA	200	-0.13	+0.82	+0.69	▼4
11	C.Rimstedt	🇸🇪 SWEDEN	260	-0.10	+0.80	+0.69	▼4
12	P.Butryn	🇵🇱 POLAND	180	-0.08	+0.73	+0.65	▼2
13	M.Sikora	🇵🇱 POLAND	180	-0.08	+0.73	+0.65	▼2
14	E.Skjetne	🇳🇴 NORWAY	240	-0.02	+0.64	+0.62	▲2
15	K.Dwyer Rimstedt	🇺🇸 USA RED	260	-0.20	+0.78	+0.58	▼7
16	O.Lien	🇺🇸 USA RED	260	-0.20	+0.78	+0.58	▼7
17	R.Segev	🇮🇱 ISRAEL	200	-0.39	+0.96	+0.57	▼13
18	D.Tal	🇮🇱 ISRAEL	200	-0.39	+0.96	+0.57	▼13
19	D.Banh	🇺🇸 USA RED	240	-0.01	+0.55	+0.54	▲1
20	J.Fournier	🇺🇸 USA RED	240	-0.01	+0.55	+0.54	▲1
21	P.Bethers	🇱🇻 LATVIA	180	+0.29	+0.23	+0.52	▲13
22	S.Bech	🇸🇪 SWEDEN	260	+0.20	+0.32	+0.52	▲8
23	D.Goldfein	🇺🇸 USA BLUE	300	-0.02	+0.48	+0.46	·
24	S.Katz	🇺🇸 USA BLUE	300	-0.02	+0.48	+0.46	·
25	L.Johansen	🇳🇴 NORWAY	180	-0.04	+0.49	+0.45	▼3
26	M.De Livera	🇦🇺 AUSTRALIA	160	-0.19	+0.63	+0.44	▼9
27	H.Bogen	🇳🇴 NORWAY	280	+0.03	+0.38	+0.41	▲2
28	J.Mill	🇦🇺 AUSTRALIA	200	-0.05	+0.42	+0.36	·
29	J.Balasovs	🇱🇻 LATVIA	300	-0.12	+0.45	+0.33	▼4
30	J.Bethers	🇱🇻 LATVIA	300	-0.12	+0.45	+0.33	▼4
31	S.Simonsen	🇳🇴 NORWAY	300	+0.11	+0.22	+0.33	▲4
32	Y.Cheng	🇹🇼 CHINESE TAIPEI	200	-0.05	+0.25	+0.20	·
33	K.Wang	🇹🇼 CHINESE TAIPEI	200	-0.05	+0.25	+0.20	·
34	C.Lin	🇹🇼 CHINESE TAIPEI	220	-0.00	+0.16	+0.16	▲6
35	Y.Ou-Yang	🇹🇼 CHINESE TAIPEI	220	-0.00	+0.16	+0.16	▲6
36	C.Lai	🇭🇰 CHINA HONG KONG	200	-0.04	+0.19	+0.15	▲2
37	B.Igla	🇵🇱 POLAND	200	-0.06	+0.21	+0.15	▼1
38	A.Machno	🇵🇱 POLAND	200	-0.06	+0.21	+0.15	▼1
39	H.Saeed	🇵🇰 PAKISTAN	180	+0.36	-0.24	+0.12	▲21
40	S.Rimstedt	🇸🇪 SWEDEN	220	-0.03	+0.14	+0.11	▲2
41	H.Eide	🇳🇴 NORWAY	200	-0.09	+0.17	+0.09	▼2
42	H.Lee	🇭🇰 CHINA HONG KONG	220	+0.05	+0.03	+0.08	▲1
43	G.Delle Cave	🇮🇹 ITALY	300	+0.07	-0.04	+0.03	▲2
44	R.Fellus	🇮🇹 ITALY	300	+0.07	-0.04	+0.03	▲2
45	S.Butt	🇵🇰 PAKISTAN	180	+0.13	-0.11	+0.02	▲6
46	A.Hung	🇦🇺 AUSTRALIA	220	-0.25	+0.26	+0.01	▼15
47	T.Koo	🇭🇰 CHINA HONG KONG	180	+0.11	-0.10	+0.01	▲2
48	C.Poon	🇭🇰 CHINA HONG KONG	180	+0.11	-0.10	+0.01	▲2
49	P.Hollands	🇦🇺 AUSTRALIA	180	-0.41	+0.42	+0.01	▼22
50	E.Fryklund	🇸🇪 SWEDEN	240	+0.00	-0.04	-0.04	▼3
51	H.Malik	🇵🇰 PAKISTAN	300	+0.19	-0.26	-0.07	▲11
52	Z.Khan	🇵🇰 PAKISTAN	300	-0.02	-0.06	-0.09	▼4
53	R.Glickman	🇺🇸 USA BLUE	300	+0.02	-0.12	-0.10	▼1
54	M.Meckstroth	🇺🇸 USA BLUE	300	+0.02	-0.12	-0.10	▼1
55	P.Lerdmaharit	🇹🇭 THAILAND	180	+0.11	-0.22	-0.11	▲1
56	S.Siriwatthannsest	🇹🇭 THAILAND	180	+0.11	-0.22	-0.11	▲1
57	H.Macaulay	🇨🇦 CANADA	200	-0.11	-0.01	-0.12	▼13
58	L.Kuo	🇹🇼 CHINESE TAIPEI	180	+0.07	-0.24	-0.16	·
59	H.So	🇹🇼 CHINESE TAIPEI	180	+0.07	-0.24	-0.16	·
60	E.Macaulay	🇨🇦 CANADA	220	+0.16	-0.44	-0.27	▲4
61	O.Bashir	🇵🇰 PAKISTAN	240	-0.16	-0.14	-0.30	▼7
62	A.Blagov	🇨🇦 CANADA	300	-0.13	-0.19	-0.32	▼7
63	F.Masloman	🇮🇩 INDONESIA	260	+0.13	-0.50	-0.37	▲3
64	C.Tirayoh	🇮🇩 INDONESIA	260	+0.13	-0.50	-0.37	▲3
65	M.Mccoll	🇨🇦 CANADA	280	-0.15	-0.24	-0.40	▼4
66	E.Sjoberg	🇸🇪 SWEDEN	220	-0.14	-0.28	-0.42	▼3
67	K.Cao	🇨🇳 CHINA	300	+0.08	-0.52	-0.45	▲3
68	H.Wang	🇨🇳 CHINA	300	+0.08	-0.52	-0.45	▲3
69	L.Fruscoloni	🇮🇹 ITALY	140	+0.21	-0.83	-0.63	▲5
70	G.Trimarchi	🇮🇹 ITALY	140	+0.21	-0.83	-0.63	▲5
71	A.Cattabiani	🇮🇹 ITALY	160	-0.13	-0.51	-0.64	▼3
72	M.Presti	🇮🇹 ITALY	160	-0.13	-0.51	-0.64	▼3
73	P.Ng	🇭🇰 CHINA HONG KONG	220	-0.16	-0.56	-0.72	▼1
74	A.Iaboni	🇨🇦 CANADA	200	+0.10	-0.82	-0.72	▼1
75	T.Fok	🇭🇰 CHINA HONG KONG	200	-0.27	-0.45	-0.72	▼10
76	X.Wu	🇨🇳 CHINA	300	+0.05	-1.18	-1.13	·
77	W.Yuan	🇨🇳 CHINA	300	+0.05	-1.18	-1.13	·
78	T.Raweejarusroung	🇹🇭 THAILAND	200	+0.01	-1.35	-1.33	·
79	B.Udomwatwong	🇹🇭 THAILAND	200	+0.01	-1.35	-1.33	·
80	N.Junthiang	🇹🇭 THAILAND	220	+0.01	-1.38	-1.36	·
81	S.Sansuwan	🇹🇭 THAILAND	220	+0.01	-1.38	-1.36	·
82	G.Lasut	🇮🇩 INDONESIA	280	+0.11	-1.57	-1.46	·
83	A.Polly	🇮🇩 INDONESIA	280	+0.11	-1.57	-1.46	·

Stages

Statistics