Veldhoven 2011 — 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	S.De Wijs	🇳🇱 NETHERLANDS	192	+0.80	+154.0
2	B.Muller	🇳🇱 NETHERLANDS	192	+0.80	+154.0
3	N.Bocchi	🇮🇹 ITALY	192	+0.66	+126.0
4	A.Madala	🇮🇹 ITALY	192	+0.66	+126.0
5	J.Hurd	🇺🇸 USA 2	272	+0.54	+147.0
6	J.Wooldridge	🇺🇸 USA 2	272	+0.54	+147.0
7	B.Levin	🇺🇸 USA 1	192	+0.26	+50.0
8	S.Weinstein	🇺🇸 USA 1	192	+0.26	+50.0
9	S.Brink	🇳🇱 NETHERLANDS	240	+0.05	+13.0
10	B.Drijver	🇳🇱 NETHERLANDS	240	+0.05	+13.0
11	R.Van Prooijen	🇳🇱 NETHERLANDS	208	-0.03	-7.0
12	J.Verhees	🇳🇱 NETHERLANDS	208	-0.03	-7.0
13	J.Grue	🇺🇸 USA 2	256	-0.06	-16.0
14	J.Lall	🇺🇸 USA 2	256	-0.06	-16.0
15	G.Duboin	🇮🇹 ITALY	144	-0.14	-20.0
16	A.Sementa	🇮🇹 ITALY	144	-0.14	-20.0
17	L.Lauria	🇮🇹 ITALY	144	-0.16	-23.0
18	A.Versace	🇮🇹 ITALY	144	-0.16	-23.0
19	C.Martel	🇺🇸 USA 1	128	-0.26	-33.0
20	L.Stansby	🇺🇸 USA 1	128	-0.26	-33.0
21	M.Fleisher	🇺🇸 USA 1	128	-0.27	-35.0
22	M.Kamil	🇺🇸 USA 1	128	-0.27	-35.0
23	X.Hou	🇨🇳 CHINA	96	+0.12	+12.0
24	M.Shi	🇨🇳 CHINA	96	+0.12	+12.0
25	J.Baldursson	🇮🇸 ICELAND	80	+0.05	+4.0
26	T.Jonsson	🇮🇸 ICELAND	80	+0.05	+4.0
27	P.Bertheau	🇸🇪 SWEDEN	48	-0.19	-9.0
28	P.Cullin	🇸🇪 SWEDEN	32	-0.22	-7.0
29	S.Haraldsson	🇮🇸 ICELAND	80	-0.24	-19.0
30	M.Magnusson	🇮🇸 ICELAND	80	-0.24	-19.0
31	F.Nystrom	🇸🇪 SWEDEN	80	-0.24	-19.0
32	R.Lian	🇨🇳 CHINA	80	-0.26	-21.0
33	H.Shi	🇨🇳 CHINA	80	-0.26	-21.0
34	J.Upmark	🇸🇪 SWEDEN	64	-0.27	-17.0
35	B.Fallenius	🇸🇪 SWEDEN	80	-0.33	-26.0
36	P.Fredin	🇸🇪 SWEDEN	80	-0.33	-26.0
37	J.Li	🇨🇳 CHINA	16	-0.44	-7.0
38	J.Liu	🇨🇳 CHINA	16	-0.44	-7.0
39	E.Ginossar	🇮🇱 ISRAEL	48	-0.56	-27.0
40	R.Pachtman	🇮🇱 ISRAEL	48	-0.56	-27.0
41	I.Herbst	🇮🇱 ISRAEL	64	-0.72	-46.0
42	O.Herbst	🇮🇱 ISRAEL	64	-0.72	-46.0
43	M.Barel	🇮🇱 ISRAEL	48	-0.79	-38.0
44	Y.Zack	🇮🇱 ISRAEL	48	-0.79	-38.0
45	K.Bathurst	🇺🇸 USA 2	112	-0.93	-104.0
46	D.Zagorin	🇺🇸 USA 2	112	-0.93	-104.0
47	B.Einarsson	🇮🇸 ICELAND	32	-1.81	-58.0
48	A.Jorgensen	🇮🇸 ICELAND	32	-1.81	-58.0

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	N.Bocchi	🇮🇹 ITALY	33	93.9%	0.06
2	A.Madala	🇮🇹 ITALY	43	93.0%	0.07
3	J.Hurd	🇺🇸 USA 2	56	91.1%	0.09
4	M.Kamil	🇺🇸 USA 1	27	88.9%	0.11
5	B.Drijver	🇳🇱 NETHERLANDS	45	88.9%	0.11
6	B.Muller	🇳🇱 NETHERLANDS	43	88.4%	0.14
7	L.Stansby	🇺🇸 USA 1	31	87.1%	0.13
8	S.Weinstein	🇺🇸 USA 1	38	86.8%	0.16
9	A.Versace	🇮🇹 ITALY	25	84.0%	0.16
10	J.Lall	🇺🇸 USA 2	50	84.0%	0.16
11	J.Verhees	🇳🇱 NETHERLANDS	49	83.7%	0.16
12	J.Grue	🇺🇸 USA 2	45	82.2%	0.20
13	R.Van Prooijen	🇳🇱 NETHERLANDS	55	81.8%	0.20
14	S.Brink	🇳🇱 NETHERLANDS	65	81.5%	0.20
15	B.Levin	🇺🇸 USA 1	34	79.4%	0.23
16	G.Duboin	🇮🇹 ITALY	33	78.8%	0.24
17	S.De Wijs	🇳🇱 NETHERLANDS	46	78.3%	0.24
18	L.Lauria	🇮🇹 ITALY	32	78.1%	0.22
19	C.Martel	🇺🇸 USA 1	24	75.0%	0.29
20	J.Wooldridge	🇺🇸 USA 2	59	72.9%	0.34
21	M.Fleisher	🇺🇸 USA 1	25	72.0%	0.28
22	A.Sementa	🇮🇹 ITALY	23	69.6%	0.39
23	R.Lian	🇨🇳 CHINA	12	100.0%	0.00
24	P.Cullin	🇸🇪 SWEDEN	10	100.0%	0.00
25	X.Hou	🇨🇳 CHINA	22	100.0%	0.00
26	J.Baldursson	🇮🇸 ICELAND	15	100.0%	0.00
27	M.Barel	🇮🇱 ISRAEL	7	100.0%	0.00
28	J.Li	🇨🇳 CHINA	2	100.0%	0.00
29	A.Jorgensen	🇮🇸 ICELAND	6	100.0%	0.00
30	K.Bathurst	🇺🇸 USA 2	23	95.7%	0.04
31	Y.Zack	🇮🇱 ISRAEL	14	92.9%	0.07
32	O.Herbst	🇮🇱 ISRAEL	11	90.9%	0.09
33	E.Ginossar	🇮🇱 ISRAEL	10	90.0%	0.10
34	M.Magnusson	🇮🇸 ICELAND	14	85.7%	0.21
35	R.Pachtman	🇮🇱 ISRAEL	13	84.6%	0.15
36	M.Shi	🇨🇳 CHINA	19	84.2%	0.16
37	S.Haraldsson	🇮🇸 ICELAND	18	83.3%	0.17
38	T.Jonsson	🇮🇸 ICELAND	18	83.3%	0.22
39	F.Nystrom	🇸🇪 SWEDEN	17	82.4%	0.18
40	I.Herbst	🇮🇱 ISRAEL	15	80.0%	0.20
41	J.Liu	🇨🇳 CHINA	5	80.0%	0.20
42	J.Upmark	🇸🇪 SWEDEN	13	76.9%	0.23
43	B.Fallenius	🇸🇪 SWEDEN	17	76.5%	0.23
44	P.Bertheau	🇸🇪 SWEDEN	8	75.0%	0.25
45	P.Fredin	🇸🇪 SWEDEN	16	75.0%	0.25
46	D.Zagorin	🇺🇸 USA 2	19	73.7%	0.32
47	H.Shi	🇨🇳 CHINA	20	70.0%	0.35
48	B.Einarsson	🇮🇸 ICELAND	7	57.1%	0.43

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	S.De Wijs	🇳🇱 NETHERLANDS	45	93.3%	0.09
2	M.Kamil	🇺🇸 USA 1	21	85.7%	0.14
3	G.Duboin	🇮🇹 ITALY	24	83.3%	0.17
4	S.Brink	🇳🇱 NETHERLANDS	42	83.3%	0.24
5	L.Lauria	🇮🇹 ITALY	34	82.4%	0.18
6	N.Bocchi	🇮🇹 ITALY	35	80.0%	0.23
7	B.Levin	🇺🇸 USA 1	49	79.6%	0.31
8	B.Drijver	🇳🇱 NETHERLANDS	53	79.2%	0.23
9	M.Fleisher	🇺🇸 USA 1	28	78.6%	0.25
10	A.Sementa	🇮🇹 ITALY	27	77.8%	0.22
11	S.Weinstein	🇺🇸 USA 1	36	77.8%	0.25
12	J.Hurd	🇺🇸 USA 2	48	77.1%	0.23
13	J.Lall	🇺🇸 USA 2	60	75.0%	0.33
14	C.Martel	🇺🇸 USA 1	31	74.2%	0.26
15	A.Madala	🇮🇹 ITALY	46	73.9%	0.30
16	B.Muller	🇳🇱 NETHERLANDS	39	71.8%	0.44
17	J.Wooldridge	🇺🇸 USA 2	60	71.7%	0.35
18	L.Stansby	🇺🇸 USA 1	27	70.4%	0.37
19	A.Versace	🇮🇹 ITALY	23	69.6%	0.43
20	J.Grue	🇺🇸 USA 2	55	69.1%	0.42
21	J.Verhees	🇳🇱 NETHERLANDS	34	67.6%	0.32
22	R.Van Prooijen	🇳🇱 NETHERLANDS	42	66.7%	0.38
23	P.Bertheau	🇸🇪 SWEDEN	8	100.0%	0.00
24	J.Liu	🇨🇳 CHINA	4	100.0%	0.00
25	B.Fallenius	🇸🇪 SWEDEN	14	92.9%	0.07
26	K.Bathurst	🇺🇸 USA 2	29	89.7%	0.10
27	I.Herbst	🇮🇱 ISRAEL	18	88.9%	0.11
28	B.Einarsson	🇮🇸 ICELAND	9	88.9%	0.11
29	O.Herbst	🇮🇱 ISRAEL	14	85.7%	0.14
30	J.Upmark	🇸🇪 SWEDEN	6	83.3%	0.33
31	E.Ginossar	🇮🇱 ISRAEL	6	83.3%	0.33
32	F.Nystrom	🇸🇪 SWEDEN	15	80.0%	0.20
33	D.Zagorin	🇺🇸 USA 2	25	80.0%	0.28
34	S.Haraldsson	🇮🇸 ICELAND	32	78.1%	0.25
35	R.Pachtman	🇮🇱 ISRAEL	9	77.8%	0.22
36	M.Magnusson	🇮🇸 ICELAND	16	75.0%	0.38
37	P.Fredin	🇸🇪 SWEDEN	15	73.3%	0.40
38	X.Hou	🇨🇳 CHINA	15	73.3%	0.47
39	H.Shi	🇨🇳 CHINA	22	72.7%	0.27
40	R.Lian	🇨🇳 CHINA	13	69.2%	0.39
41	J.Baldursson	🇮🇸 ICELAND	29	69.0%	0.34
42	J.Li	🇨🇳 CHINA	3	66.7%	0.33
43	M.Barel	🇮🇱 ISRAEL	9	66.7%	0.44
44	P.Cullin	🇸🇪 SWEDEN	6	66.7%	0.67
45	Y.Zack	🇮🇱 ISRAEL	11	63.6%	0.36
46	M.Shi	🇨🇳 CHINA	21	57.1%	0.48
47	A.Jorgensen	🇮🇸 ICELAND	6	50.0%	0.67
48	T.Jonsson	🇮🇸 ICELAND	18	50.0%	0.72

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	N.Bocchi	🇮🇹 ITALY	76	93.4%	0.08
2	A.Madala	🇮🇹 ITALY	76	93.4%	0.08
3	B.Levin	🇺🇸 USA 1	72	93.1%	0.07
4	S.Weinstein	🇺🇸 USA 1	72	93.1%	0.07
5	C.Martel	🇺🇸 USA 1	55	92.7%	0.07
6	L.Stansby	🇺🇸 USA 1	55	92.7%	0.07
7	G.Duboin	🇮🇹 ITALY	56	91.1%	0.09
8	A.Sementa	🇮🇹 ITALY	56	91.1%	0.09
9	S.De Wijs	🇳🇱 NETHERLANDS	89	89.9%	0.11
10	B.Muller	🇳🇱 NETHERLANDS	89	89.9%	0.11
11	J.Hurd	🇺🇸 USA 2	115	89.6%	0.12
12	J.Wooldridge	🇺🇸 USA 2	115	89.6%	0.12
13	S.Brink	🇳🇱 NETHERLANDS	110	89.1%	0.14
14	B.Drijver	🇳🇱 NETHERLANDS	110	89.1%	0.14
15	R.Van Prooijen	🇳🇱 NETHERLANDS	104	87.5%	0.15
16	J.Verhees	🇳🇱 NETHERLANDS	104	87.5%	0.15
17	J.Grue	🇺🇸 USA 2	95	87.4%	0.17
18	J.Lall	🇺🇸 USA 2	95	87.4%	0.17
19	L.Lauria	🇮🇹 ITALY	57	86.0%	0.16
20	A.Versace	🇮🇹 ITALY	57	86.0%	0.16
21	M.Fleisher	🇺🇸 USA 1	52	80.8%	0.19
22	M.Kamil	🇺🇸 USA 1	52	80.8%	0.19
23	P.Bertheau	🇸🇪 SWEDEN	18	100.0%	0.00
24	F.Nystrom	🇸🇪 SWEDEN	33	100.0%	0.00
25	R.Lian	🇨🇳 CHINA	32	96.9%	0.03
26	H.Shi	🇨🇳 CHINA	32	96.9%	0.03
27	J.Upmark	🇸🇪 SWEDEN	30	96.7%	0.03
28	I.Herbst	🇮🇱 ISRAEL	26	96.2%	0.04
29	O.Herbst	🇮🇱 ISRAEL	26	96.2%	0.04
30	M.Barel	🇮🇱 ISRAEL	21	95.2%	0.05
31	Y.Zack	🇮🇱 ISRAEL	21	95.2%	0.05
32	P.Cullin	🇸🇪 SWEDEN	15	93.3%	0.07
33	X.Hou	🇨🇳 CHINA	41	92.7%	0.12
34	M.Shi	🇨🇳 CHINA	41	92.7%	0.12
35	E.Ginossar	🇮🇱 ISRAEL	23	91.3%	0.09
36	R.Pachtman	🇮🇱 ISRAEL	23	91.3%	0.09
37	B.Fallenius	🇸🇪 SWEDEN	33	90.9%	0.12
38	P.Fredin	🇸🇪 SWEDEN	33	90.9%	0.12
39	J.Baldursson	🇮🇸 ICELAND	33	87.9%	0.18
40	T.Jonsson	🇮🇸 ICELAND	33	87.9%	0.18
41	S.Haraldsson	🇮🇸 ICELAND	32	87.5%	0.12
42	M.Magnusson	🇮🇸 ICELAND	32	87.5%	0.12
43	J.Li	🇨🇳 CHINA	7	85.7%	0.14
44	J.Liu	🇨🇳 CHINA	7	85.7%	0.14
45	B.Einarsson	🇮🇸 ICELAND	13	84.6%	0.15
46	A.Jorgensen	🇮🇸 ICELAND	13	84.6%	0.15
47	K.Bathurst	🇺🇸 USA 2	42	83.3%	0.19
48	D.Zagorin	🇺🇸 USA 2	42	83.3%	0.19

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	N.Bocchi	🇮🇹 ITALY	272	+0.03	+0.72	+0.75	▲2
2	A.Madala	🇮🇹 ITALY	272	+0.03	+0.72	+0.75	▲2
3	J.Hurd	🇺🇸 USA 2	272	-0.12	+0.74	+0.62	▼2
4	J.Wooldridge	🇺🇸 USA 2	272	-0.12	+0.74	+0.62	▼2
5	S.De Wijs	🇳🇱 NETHERLANDS	192	-0.10	+0.49	+0.39	·
6	B.Muller	🇳🇱 NETHERLANDS	192	-0.10	+0.49	+0.39	·
7	R.Van Prooijen	🇳🇱 NETHERLANDS	208	+0.03	+0.18	+0.21	▲6
8	J.Verhees	🇳🇱 NETHERLANDS	208	+0.03	+0.18	+0.21	▲6
9	G.Duboin	🇮🇹 ITALY	144	-0.09	+0.26	+0.18	·
10	A.Sementa	🇮🇹 ITALY	144	-0.09	+0.26	+0.18	·
11	S.Brink	🇳🇱 NETHERLANDS	240	-0.06	+0.21	+0.16	·
12	B.Drijver	🇳🇱 NETHERLANDS	240	-0.06	+0.21	+0.16	·
13	M.Fleisher	🇺🇸 USA 1	208	-0.44	+0.39	-0.05	▼6
14	M.Kamil	🇺🇸 USA 1	208	-0.44	+0.39	-0.05	▼6
15	B.Levin	🇺🇸 USA 1	272	+0.09	-0.18	-0.09	·
16	S.Weinstein	🇺🇸 USA 1	272	+0.09	-0.18	-0.09	·
17	L.Lauria	🇮🇹 ITALY	224	+0.14	-0.40	-0.25	·
18	A.Versace	🇮🇹 ITALY	224	+0.14	-0.40	-0.25	·
19	J.Grue	🇺🇸 USA 2	256	+0.02	-0.42	-0.40	·
20	J.Lall	🇺🇸 USA 2	256	+0.02	-0.42	-0.40	·
21	C.Martel	🇺🇸 USA 1	128	+0.08	-0.68	-0.59	·
22	L.Stansby	🇺🇸 USA 1	128	+0.08	-0.68	-0.59	·

Stages

Statistics