Philadelphia 2010 — 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.
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 | T.Bessis | 🇫🇷 France | 110 | +0.08 | +1.11 | +1.20 | · |
| 2 | F.Volcker | 🇫🇷 France | 110 | +0.08 | +1.11 | +1.20 | · |
| 3 | L.Fisher | 🇮🇱 Israel | 150 | +0.05 | +1.08 | +1.14 | · |
| 4 | B.Tarnovski | 🇮🇱 Israel | 160 | +0.06 | +1.05 | +1.12 | · |
| 5 | J.Chiu | 🇺🇸 USA 1 | 100 | +0.11 | +0.81 | +0.92 | · |
| 6 | K.Fay | 🇺🇸 USA 1 | 100 | +0.11 | +0.81 | +0.92 | · |
| 7 | Y.Chen | 🇨🇳 China | 150 | +0.06 | +0.40 | +0.46 | ▲7 |
| 8 | I.Veselov | 🇷🇺 Russia | 160 | -0.03 | +0.43 | +0.40 | ▲1 |
| 9 | J.Katerbau | 🇩🇪 Germany | 160 | -0.00 | +0.40 | +0.39 | ▲6 |
| 10 | M.Rehder | 🇩🇪 Germany | 160 | -0.00 | +0.40 | +0.39 | ▲6 |
| 11 | C.Grosset | 🇫🇷 France | 100 | -0.02 | +0.38 | +0.36 | ▲6 |
| 12 | C.Lorenzini | 🇫🇷 France | 100 | -0.02 | +0.38 | +0.36 | ▲6 |
| 13 | B.Van Den Bos | 🇳🇱 Netherlands | 110 | -0.12 | +0.47 | +0.35 | ▼6 |
| 14 | J.Van Lankveld | 🇳🇱 Netherlands | 110 | -0.12 | +0.47 | +0.35 | ▼6 |
| 15 | N.Edgtton | 🇦🇺 Australia | 140 | -0.08 | +0.41 | +0.33 | ▼3 |
| 16 | J.Gosney | 🇦🇺 Australia | 140 | -0.08 | +0.41 | +0.33 | ▼3 |
| 17 | D.Dobrin | 🇷🇺 Russia | 160 | +0.03 | +0.29 | +0.32 | ▲5 |
| 18 | A.Mohota | 🇮🇳 India | 100 | +0.13 | +0.15 | +0.28 | ▲10 |
| 19 | R.Rajkumar | 🇮🇳 India | 100 | +0.13 | +0.15 | +0.28 | ▲10 |
| 20 | H.Miura | 🇯🇵 Japan | 140 | -0.06 | +0.30 | +0.24 | · |
| 21 | H.Yokoi | 🇯🇵 Japan | 140 | -0.06 | +0.30 | +0.24 | · |
| 22 | G.Delle Cave | 🇮🇹 Italy | 90 | -0.15 | +0.36 | +0.21 | ▼3 |
| 23 | K.Asplund | 🇸🇪 Sweden | 160 | -0.02 | +0.23 | +0.20 | ▲1 |
| 24 | E.Fryklund | 🇸🇪 Sweden | 160 | -0.02 | +0.23 | +0.20 | ▲1 |
| 25 | E.Argelazi | 🇮🇱 Israel | 160 | -0.22 | +0.41 | +0.20 | ▼15 |
| 26 | A.Birman | 🇮🇱 Israel | 160 | -0.22 | +0.41 | +0.20 | ▼15 |
| 27 | D.Molenaar | 🇳🇱 Netherlands | 110 | +0.28 | -0.09 | +0.19 | ▲20 |
| 28 | T.Verbeek | 🇳🇱 Netherlands | 110 | +0.28 | -0.09 | +0.19 | ▲20 |
| 29 | D.Lavee | 🇨🇦 Canada | 160 | -0.05 | +0.22 | +0.17 | ▼3 |
| 30 | S.Nystrom | 🇨🇦 Canada | 160 | -0.05 | +0.22 | +0.17 | ▼3 |
| 31 | A.Edgtton | 🇦🇺 Australia | 110 | +0.08 | +0.06 | +0.13 | · |
| 32 | A.Hung | 🇦🇺 Australia | 110 | +0.08 | +0.06 | +0.13 | · |
| 33 | J.Hu | 🇨🇳 China | 120 | -0.17 | +0.28 | +0.11 | ▼10 |
| 34 | A.Manno | 🇮🇹 Italy | 160 | +0.04 | +0.04 | +0.08 | ▲1 |
| 35 | G.Zind | 🇨🇦 Canada | 90 | -0.05 | +0.11 | +0.06 | ▼5 |
| 36 | Z.Deng | 🇨🇳 China | 140 | +0.05 | -0.01 | +0.04 | ▲4 |
| 37 | Y.Liu | 🇨🇳 China | 140 | +0.05 | -0.01 | +0.04 | ▲4 |
| 38 | F.Montes De Oca | 🇦🇷 Argentina | 160 | +0.11 | -0.08 | +0.03 | ▲8 |
| 39 | S.Simonsen | 🇳🇴 Norway | 120 | -0.06 | +0.06 | -0.00 | ▼6 |
| 40 | E.Skjetne | 🇳🇴 Norway | 120 | -0.06 | +0.06 | -0.00 | ▼6 |
| 41 | H.Bogen | 🇳🇴 Norway | 110 | +0.00 | -0.00 | -0.00 | ▼3 |
| 42 | L.Johansen | 🇳🇴 Norway | 110 | +0.00 | -0.00 | -0.00 | ▼3 |
| 43 | V.De Pagter | 🇳🇱 Netherlands | 100 | -0.02 | -0.01 | -0.03 | ▼1 |
| 44 | J.Hop | 🇳🇱 Netherlands | 100 | -0.02 | -0.01 | -0.03 | ▼1 |
| 45 | A.Franchi | 🇮🇹 Italy | 160 | -0.03 | +0.00 | -0.03 | ▼9 |
| 46 | M.Montanari | 🇮🇹 Italy | 160 | -0.03 | +0.00 | -0.03 | ▼9 |
| 47 | D.Goldfein | 🇺🇸 USA 2 | 110 | +0.10 | -0.15 | -0.05 | ▲6 |
| 48 | S.Katz | 🇺🇸 USA 2 | 110 | +0.10 | -0.15 | -0.05 | ▲6 |
| 49 | M.Di Franco | 🇮🇹 Italy | 70 | +0.30 | -0.38 | -0.08 | ▲24 |
| 50 | K.Dwyer Rimstedt | 🇺🇸 USA 2 | 120 | +0.14 | -0.23 | -0.10 | ▲11 |
| 51 | M.Meckstroth | 🇺🇸 USA 2 | 110 | +0.11 | -0.22 | -0.11 | ▲9 |
| 52 | O.Lien | 🇺🇸 USA 2 | 100 | -0.08 | -0.04 | -0.12 | ▼7 |
| 53 | Z.Brescoll | 🇺🇸 USA 2 | 90 | -0.14 | -0.01 | -0.15 | ▼9 |
| 54 | J.Fournier | 🇺🇸 USA 1 | 120 | +0.01 | -0.24 | -0.23 | ▲8 |
| 55 | R.Lee | 🇺🇸 USA 1 | 120 | +0.01 | -0.24 | -0.23 | ▲8 |
| 56 | N.Lhuissier | 🇫🇷 France | 110 | -0.13 | -0.11 | -0.24 | ▼7 |
| 57 | Q.Robert | 🇫🇷 France | 110 | -0.13 | -0.11 | -0.24 | ▼7 |
| 58 | E.Arvidsson | 🇸🇪 Sweden | 160 | +0.01 | -0.25 | -0.24 | ▲6 |
| 59 | S.Bech | 🇸🇪 Sweden | 160 | +0.01 | -0.25 | -0.24 | ▲6 |
| 60 | A.Blagov | 🇨🇦 Canada | 160 | +0.04 | -0.29 | -0.26 | ▲8 |
| 61 | K.Nekrasova | 🇷🇺 Russia | 160 | -0.07 | -0.19 | -0.26 | ▼6 |
| 62 | F.Scanavino | 🇦🇷 Argentina | 110 | +0.11 | -0.37 | -0.26 | ▲10 |
| 63 | M.Agica | 🇺🇸 USA 1 | 100 | -0.07 | -0.20 | -0.28 | ▼7 |
| 64 | D.Wolkowitz | 🇺🇸 USA 1 | 100 | -0.07 | -0.20 | -0.28 | ▼7 |
| 65 | S.Gotoda | 🇯🇵 Japan | 80 | -0.06 | -0.22 | -0.28 | ▼7 |
| 66 | N.Nakayama | 🇯🇵 Japan | 80 | -0.06 | -0.22 | -0.28 | ▼7 |
| 67 | W.Chiu | 🇭🇰 China Hong Kong | 110 | -0.05 | -0.26 | -0.31 | ▼1 |
| 68 | A.Tsang | 🇭🇰 China Hong Kong | 110 | -0.05 | -0.26 | -0.31 | ▼1 |
| 69 | Y.Ii | 🇯🇵 Japan | 100 | -0.02 | -0.31 | -0.34 | · |
| 70 | Y.Kido | 🇯🇵 Japan | 100 | -0.02 | -0.31 | -0.34 | · |
| 71 | I.Volozhenin | 🇷🇺 Russia | 160 | -0.01 | -0.33 | -0.34 | · |
| 72 | M.Wuermseer | 🇩🇪 Germany | 130 | +0.06 | -0.46 | -0.40 | ▲2 |
| 73 | F.Zimmermann | 🇩🇪 Germany | 130 | +0.06 | -0.46 | -0.40 | ▲2 |
| 74 | R.Guthi | 🇮🇳 India | 110 | -0.29 | -0.13 | -0.42 | ▼23 |
| 75 | V.Raghavan | 🇮🇳 India | 110 | -0.29 | -0.13 | -0.42 | ▼23 |
| 76 | F.Ferro | 🇦🇷 Argentina | 130 | +0.16 | -0.59 | -0.43 | · |
| 77 | Y.Leung | 🇭🇰 China Hong Kong | 110 | +0.18 | -0.66 | -0.48 | ▲6 |
| 78 | P.Tsang | 🇭🇰 China Hong Kong | 110 | +0.18 | -0.66 | -0.48 | ▲6 |
| 79 | M.Agarwal | 🇮🇳 India | 110 | +0.12 | -0.63 | -0.51 | · |
| 80 | P.Bachiaju | 🇮🇳 India | 110 | +0.12 | -0.63 | -0.51 | · |
| 81 | J.Mill | 🇦🇺 Australia | 70 | +0.10 | -0.65 | -0.55 | · |
| 82 | M.Whibley | 🇦🇺 Australia | 70 | +0.10 | -0.65 | -0.55 | · |
| 83 | C.Zhou | 🇨🇦 Canada | 70 | +0.15 | -0.81 | -0.66 | ▲4 |
| 84 | M.Bartnes | 🇳🇴 Norway | 90 | +0.10 | -0.80 | -0.70 | ▲1 |
| 85 | E.Berg | 🇳🇴 Norway | 90 | +0.10 | -0.80 | -0.70 | ▲1 |
| 86 | K.Kong | 🇭🇰 China Hong Kong | 100 | -0.21 | -0.62 | -0.84 | ▼9 |
| 87 | C.Lau | 🇭🇰 China Hong Kong | 100 | -0.21 | -0.62 | -0.84 | ▼9 |
| 88 | A.Scanavino | 🇦🇷 Argentina | 130 | +0.07 | -0.97 | -0.90 | ▲1 |
| 89 | J.Etchepareborda | 🇦🇷 Argentina | 110 | -0.08 | -0.91 | -0.98 | ▼1 |