sail/symbolic-instruction-tuning huggingface dataset:
[Table] header: Pick # | CFL Team | Player | Position | College row 1 : 1 | Hamilton Tiger-Cats | Dylan Barker | DB | Saskatchewan
row 2 : 2 | Calgary Stampeders (via Edmonton Eski | Dimitri Tsoumpas | OL | Weber State
row 3 : 3 | Calgary Stampeders | Jesse Newman | OL | Louisiana-Lafayette
row 4 : 4 | Saskatchewan Roughriders (via Toronto Argo | Keith Shologan | DL | Central Florida
row 5 : 5 | British Columbia Lions | Justin Sorensen | OL/ RT | South Carolina
row 6 : 6 | Winnipeg Blue Bombers | Brendon LaBatte | OL | Regina
row 7 : 7 | Montreal Alouettes (via Saskatchewan ) | Shea Emry | LB | UBC
row 8 : 8 | Hamilton Tiger-Cats (via Montreal forfeiture | Samuel Giguère | WR | Sherbrooke [/Table] Answer this question based on the above table: What position does a Keith Shologan, who was picked higher than 6, play?

Answer: DL
[Table] header: Year | Gross Domestic Product | US Dollar Exchange | Inflation Index (2000=100) | Per Capita Income (as % of USA) row 1 : 1980 | 7,764 | 0.27 Kuwaiti Dinars | 55 | 171.08
row 2 : 1985 | 6,450 | 0.29 Kuwaiti Dinars | 68 | 71.58
row 3 : 1990 | 5,328 | 0.29 Kuwaiti Dinars | 80 | 37.00
row 4 : 1995 | 8,114 | 0.29 Kuwaiti Dinars | 92 | 62.14
row 5 : 2000 | 11,570 | 0.30 Kuwaiti Dinars | 100 | 48.92
row 6 : 2005 | 21,783 | 0.29 Kuwaiti Dinars | 108 | 64.35 [/Table] Answer this question based on the above table: What year before 1980 has is the highest Inflation Index (2000=100)?

Answer: none
[Table] header: Model number | sSpec number | Frequency | L2 cache | Mult. | Voltage | Socket | Part number(s) row 1 : Mobile Pentium 266PE | SL3HH(mdpA0 | 267 MHz | 256 KB | 4× | 1.6V | μPGA2 BGA2 MMC-2 | KP80524KX266256
row 2 : Mobile Pentium 300PE | SL3HJ(mdpA | 300 MHz | 256 KB | 4.5× | 1.6V | μPGA2BGA2MMC-2 | KP80524KX300256KC
row 3 : Mobile Pentium 333 | SL3HK(mdpA0 | 333 MHz | 256 KB | 5× | 1.6V | μPGA2BGA2MMC-2 | KP80524KX333256KC
row 4 : Mobile Pentium II 366 | SL3HL(mdpA0 | 367 MHz | 256 KB | 5.5× | 1.6V | μPGA2BGA2MMC-2 | PMG36602002AA
row 5 : Mobile Pentium II 400 | SL3BW(mqpA | 400 MHz | 256 KB | 6× | 1.55V | μPGA2BGA2MMC-2 | PMG40002002AA [/Table] Answer this question based on the above table: Which frequency has voltage of 1.6v and part number kp80524kx300256kc80524kx300256pmg30002002aa?

Answer: none
[Table] header: Model number | sSpec number | Frequency | L2 cache | Mult. | Voltage | Socket | Part number(s) row 1 : Mobile Pentium 266PE | SL3HH(mdpA0 | 267 MHz | 256 KB | 4× | 1.6V | μPGA2 BGA2 MMC-2 | KP80524KX266256
row 2 : Mobile Pentium 300PE | SL3HJ(mdpA | 300 MHz | 256 KB | 4.5× | 1.6V | μPGA2BGA2MMC-2 | KP80524KX300256KC
row 3 : Mobile Pentium 333 | SL3HK(mdpA0 | 333 MHz | 256 KB | 5× | 1.6V | μPGA2BGA2MMC-2 | KP80524KX333256KC
row 4 : Mobile Pentium II 366 | SL3HL(mdpA0 | 367 MHz | 256 KB | 5.5× | 1.6V | μPGA2BGA2MMC-2 | PMG36602002AA
row 5 : Mobile Pentium II 400 | SL3BW(mqpA | 400 MHz | 256 KB | 6× | 1.55V | μPGA2BGA2MMC-2 | PMG40002002AA [/Table] Answer this question based on the above table: Which model number has socket μpga2 bga2 mmc-2?

Answer: Mobile Pentium 266PE
[Table] header: Model number | sSpec number | Frequency | L2 cache | Mult. | Voltage | Socket | Part number(s) row 1 : Mobile Pentium 266PE | SL3HH(mdpA0 | 267 MHz | 256 KB | 4× | 1.6V | μPGA2 BGA2 MMC-2 | KP80524KX266256
row 2 : Mobile Pentium 300PE | SL3HJ(mdpA | 300 MHz | 256 KB | 4.5× | 1.6V | μPGA2BGA2MMC-2 | KP80524KX300256KC
row 3 : Mobile Pentium 333 | SL3HK(mdpA0 | 333 MHz | 256 KB | 5× | 1.6V | μPGA2BGA2MMC-2 | KP80524KX333256KC
row 4 : Mobile Pentium II 366 | SL3HL(mdpA0 | 367 MHz | 256 KB | 5.5× | 1.6V | μPGA2BGA2MMC-2 | PMG36602002AA
row 5 : Mobile Pentium II 400 | SL3BW(mqpA | 400 MHz | 256 KB | 6× | 1.55V | μPGA2BGA2MMC-2 | PMG40002002AA [/Table] Answer this question based on the above table: What is the L2 cache for the Mobile Pentium 333?

Answer: 256 KB
[Table] header: Rank | Nation | Gold | Silver | Bronze | Total row 1 : 1 | Soviet Union | 7 | 5 | 9 | 21
row 2 : 2 | Germany | 4 | 3 | 1 | 8
row 3 : 3 | United States | 3 | 4 | 3 | 10
row 4 : 4 | Norway | 3 | 3 | 0 | 6
row 5 : 5 | Sweden | 3 | 2 | 2 | 7
row 6 : 6 | Finland | 2 | 3 | 3 | 8
row 7 : 7 | Canada | 2 | 1 | 1 | 4
row 8 : 8 | Switzerland | 2 | 0 | 0 | 2
row 9 : 9 | Austria | 1 | 2 | 3 | 6
row 10 : 10 | France | 1 | 0 | 2 | 3
row 11 : 11 | Netherlands | 0 | 1 | 1 | 2
row 12 : 11 | Poland | 0 | 1 | 1 | 2
row 13 : 13 | Czechoslovakia | 0 | 1 | 0 | 1
row 14 : 14 | Italy | 0 | 0 | 1 | 1
row 15 : Total (14 NOCs) | Total (14 NOCs) | 28‡ | 26‡ | 27 | 81 [/Table] Answer this question based on the above table: How many totals have golds of 3, silvers of 3, and bronzes under 3?

Answer: 6.0
[Table] header: Rank | Nation | Gold | Silver | Bronze | Total row 1 : 1 | Soviet Union | 7 | 5 | 9 | 21
row 2 : 2 | Germany | 4 | 3 | 1 | 8
row 3 : 3 | United States | 3 | 4 | 3 | 10
row 4 : 4 | Norway | 3 | 3 | 0 | 6
row 5 : 5 | Sweden | 3 | 2 | 2 | 7
row 6 : 6 | Finland | 2 | 3 | 3 | 8
row 7 : 7 | Canada | 2 | 1 | 1 | 4
row 8 : 8 | Switzerland | 2 | 0 | 0 | 2
row 9 : 9 | Austria | 1 | 2 | 3 | 6
row 10 : 10 | France | 1 | 0 | 2 | 3
row 11 : 11 | Netherlands | 0 | 1 | 1 | 2
row 12 : 11 | Poland | 0 | 1 | 1 | 2
row 13 : 13 | Czechoslovakia | 0 | 1 | 0 | 1
row 14 : 14 | Italy | 0 | 0 | 1 | 1
row 15 : Total (14 NOCs) | Total (14 NOCs) | 28‡ | 26‡ | 27 | 81 [/Table] Answer this question based on the above table: Which nation has a rank of 7?

Answer: Canada
[Table] header: Rank | Nation | Gold | Silver | Bronze | Total row 1 : 1 | Soviet Union | 7 | 5 | 9 | 21
row 2 : 2 | Germany | 4 | 3 | 1 | 8
row 3 : 3 | United States | 3 | 4 | 3 | 10
row 4 : 4 | Norway | 3 | 3 | 0 | 6
row 5 : 5 | Sweden | 3 | 2 | 2 | 7
row 6 : 6 | Finland | 2 | 3 | 3 | 8
row 7 : 7 | Canada | 2 | 1 | 1 | 4
row 8 : 8 | Switzerland | 2 | 0 | 0 | 2
row 9 : 9 | Austria | 1 | 2 | 3 | 6
row 10 : 10 | France | 1 | 0 | 2 | 3
row 11 : 11 | Netherlands | 0 | 1 | 1 | 2
row 12 : 11 | Poland | 0 | 1 | 1 | 2
row 13 : 13 | Czechoslovakia | 0 | 1 | 0 | 1
row 14 : 14 | Italy | 0 | 0 | 1 | 1
row 15 : Total (14 NOCs) | Total (14 NOCs) | 28‡ | 26‡ | 27 | 81 [/Table] Answer this question based on the above table: What is the average bronze with silvers of 1 and totals over 2?

Answer: 1.0
[Table] header: Rank | Nation | Gold | Silver | Bronze | Total row 1 : 1 | Soviet Union | 7 | 5 | 9 | 21
row 2 : 2 | Germany | 4 | 3 | 1 | 8
row 3 : 3 | United States | 3 | 4 | 3 | 10
row 4 : 4 | Norway | 3 | 3 | 0 | 6
row 5 : 5 | Sweden | 3 | 2 | 2 | 7
row 6 : 6 | Finland | 2 | 3 | 3 | 8
row 7 : 7 | Canada | 2 | 1 | 1 | 4
row 8 : 8 | Switzerland | 2 | 0 | 0 | 2
row 9 : 9 | Austria | 1 | 2 | 3 | 6
row 10 : 10 | France | 1 | 0 | 2 | 3
row 11 : 11 | Netherlands | 0 | 1 | 1 | 2
row 12 : 11 | Poland | 0 | 1 | 1 | 2
row 13 : 13 | Czechoslovakia | 0 | 1 | 0 | 1
row 14 : 14 | Italy | 0 | 0 | 1 | 1
row 15 : Total (14 NOCs) | Total (14 NOCs) | 28‡ | 26‡ | 27 | 81 [/Table] Answer this question based on the above table: How many golds does Germany have?

Answer: 4.0
[Table] header: Rank | Nation | Gold | Silver | Bronze | Total row 1 : 1 | Soviet Union | 7 | 5 | 9 | 21
row 2 : 2 | Germany | 4 | 3 | 1 | 8
row 3 : 3 | United States | 3 | 4 | 3 | 10
row 4 : 4 | Norway | 3 | 3 | 0 | 6
row 5 : 5 | Sweden | 3 | 2 | 2 | 7
row 6 : 6 | Finland | 2 | 3 | 3 | 8
row 7 : 7 | Canada | 2 | 1 | 1 | 4
row 8 : 8 | Switzerland | 2 | 0 | 0 | 2
row 9 : 9 | Austria | 1 | 2 | 3 | 6
row 10 : 10 | France | 1 | 0 | 2 | 3
row 11 : 11 | Netherlands | 0 | 1 | 1 | 2
row 12 : 11 | Poland | 0 | 1 | 1 | 2
row 13 : 13 | Czechoslovakia | 0 | 1 | 0 | 1
row 14 : 14 | Italy | 0 | 0 | 1 | 1
row 15 : Total (14 NOCs) | Total (14 NOCs) | 28‡ | 26‡ | 27 | 81 [/Table] Answer this question based on the above table: What is the total number of bronzes with totals under 4 and ranks of 10?

Answer: 1.0
[Table] header: Year | Class | Team | Points | Wins row 1 : 1959 | 125cc | Honda | 1 | 0
row 2 : 1960 | 125cc | Honda | 1 | 0
row 3 : 1960 | 250cc | Honda | 1 | 0
row 4 : 1961 | 125cc | Honda | 2 | 0
row 5 : 1961 | 250cc | Honda | 2 | 0
row 6 : 1963 | 50cc | Honda | 0 | 0
row 7 : 1964 | 50cc | Honda | 1 | 0
row 8 : 1965 | 50cc | Honda | 0 | 0 [/Table] Answer this question based on the above table: What is the lowest Points, when Class is 50cc, when Year is 1965, and when Wins is less than 0?

Answer: none
[Table] header: Year | Class | Team | Points | Wins row 1 : 1959 | 125cc | Honda | 1 | 0
row 2 : 1960 | 125cc | Honda | 1 | 0
row 3 : 1960 | 250cc | Honda | 1 | 0
row 4 : 1961 | 125cc | Honda | 2 | 0
row 5 : 1961 | 250cc | Honda | 2 | 0
row 6 : 1963 | 50cc | Honda | 0 | 0
row 7 : 1964 | 50cc | Honda | 1 | 0
row 8 : 1965 | 50cc | Honda | 0 | 0 [/Table] Answer this question based on the above table: What is the total number of Year, when Wins is less than 0?

Answer: 0.0
[Table] header: Year | Class | Team | Points | Wins row 1 : 1959 | 125cc | Honda | 1 | 0
row 2 : 1960 | 125cc | Honda | 1 | 0
row 3 : 1960 | 250cc | Honda | 1 | 0
row 4 : 1961 | 125cc | Honda | 2 | 0
row 5 : 1961 | 250cc | Honda | 2 | 0
row 6 : 1963 | 50cc | Honda | 0 | 0
row 7 : 1964 | 50cc | Honda | 1 | 0
row 8 : 1965 | 50cc | Honda | 0 | 0 [/Table] Answer this question based on the above table: What is the sum of Points, when Year is after 1959, and when Class is 250cc?

Answer: 3.0
[Table] header: Year | Class | Team | Points | Wins row 1 : 1959 | 125cc | Honda | 1 | 0
row 2 : 1960 | 125cc | Honda | 1 | 0
row 3 : 1960 | 250cc | Honda | 1 | 0
row 4 : 1961 | 125cc | Honda | 2 | 0
row 5 : 1961 | 250cc | Honda | 2 | 0
row 6 : 1963 | 50cc | Honda | 0 | 0
row 7 : 1964 | 50cc | Honda | 1 | 0
row 8 : 1965 | 50cc | Honda | 0 | 0 [/Table] Answer this question based on the above table: What is the total number of Wins, when Points is less than 1?

Answer: 2.0
[Table] header: Year | Class | Team | Points | Wins row 1 : 1959 | 125cc | Honda | 1 | 0
row 2 : 1960 | 125cc | Honda | 1 | 0
row 3 : 1960 | 250cc | Honda | 1 | 0
row 4 : 1961 | 125cc | Honda | 2 | 0
row 5 : 1961 | 250cc | Honda | 2 | 0
row 6 : 1963 | 50cc | Honda | 0 | 0
row 7 : 1964 | 50cc | Honda | 1 | 0
row 8 : 1965 | 50cc | Honda | 0 | 0 [/Table] Answer this question based on the above table: What is the sum of Wins, when Year is 1959?

Answer: 0.0
[Table] header: Position | Team | Played | Drawn | Lost | Goals For | Goals Against | Goal Difference | Points 1 row 1 : 1 | Leek Town | 42 | 8 | 8 | 70 | 31 | +39 | 86
row 2 : 2 | Droylsden | 42 | 6 | 9 | 81 | 46 | +35 | 80 2
row 3 : 3 | Accrington Stanley | 42 | 10 | 10 | 80 | 53 | +27 | 76
row 4 : 4 | Whitley Bay | 42 | 11 | 10 | 93 | 59 | +38 | 74
row 5 : 5 | Emley | 42 | 9 | 13 | 70 | 42 | +28 | 69
row 6 : 6 | Congleton Town | 42 | 12 | 10 | 65 | 53 | +12 | 69 3
row 7 : 7 | Winsford United | 42 | 10 | 14 | 65 | 53 | +12 | 64
row 8 : 8 | Curzon Ashton | 42 | 11 | 14 | 66 | 60 | +6 | 62
row 9 : 9 | Harrogate Town | 42 | 9 | 16 | 68 | 62 | +6 | 60
row 10 : 10 | Lancaster City | 42 | 14 | 13 | 73 | 54 | +19 | 59
row 11 : 11 | Eastwood Town | 42 | 11 | 15 | 61 | 64 | −3 | 58
row 12 : 12 | Farsley Celtic | 42 | 6 | 19 | 71 | 76 | −5 | 57
row 13 : 13 | Rossendale United | 42 | 9 | 18 | 73 | 69 | +4 | 54
row 14 : 14 | Newtown | 42 | 12 | 16 | 49 | 62 | −13 | 54
row 15 : 15 | Irlam Town | 42 | 11 | 17 | 61 | 66 | −5 | 53
row 16 : 16 | Workington | 42 | 8 | 20 | 56 | 64 | −8 | 50
row 17 : 17 | Radcliffe Borough | 42 | 7 | 21 | 47 | 62 | −15 | 49
row 18 : 18 | Alfreton Town | 42 | 8 | 21 | 59 | 85 | −26 | 47
row 19 : 19 | Worksop Town | 42 | 5 | 24 | 56 | 95 | −39 | 44
row 20 : 20 | Netherfield | 42 | 6 | 25 | 56 | 89 | −33 | 39
row 21 : 21 | Eastwood Hanley | 42 | 6 | 26 | 45 | 76 | −31 | 36
row 22 : 22 | Penrith | 42 | 9 | 24 | 44 | 88 | −44 | 36 [/Table] Answer this question based on the above table: What is the fewest games played for teams with 73 goals for and more than 69 goals against?

Answer: none
[Table] header: Position | Team | Played | Drawn | Lost | Goals For | Goals Against | Goal Difference | Points 1 row 1 : 1 | Leek Town | 42 | 8 | 8 | 70 | 31 | +39 | 86
row 2 : 2 | Droylsden | 42 | 6 | 9 | 81 | 46 | +35 | 80 2
row 3 : 3 | Accrington Stanley | 42 | 10 | 10 | 80 | 53 | +27 | 76
row 4 : 4 | Whitley Bay | 42 | 11 | 10 | 93 | 59 | +38 | 74
row 5 : 5 | Emley | 42 | 9 | 13 | 70 | 42 | +28 | 69
row 6 : 6 | Congleton Town | 42 | 12 | 10 | 65 | 53 | +12 | 69 3
row 7 : 7 | Winsford United | 42 | 10 | 14 | 65 | 53 | +12 | 64
row 8 : 8 | Curzon Ashton | 42 | 11 | 14 | 66 | 60 | +6 | 62
row 9 : 9 | Harrogate Town | 42 | 9 | 16 | 68 | 62 | +6 | 60
row 10 : 10 | Lancaster City | 42 | 14 | 13 | 73 | 54 | +19 | 59
row 11 : 11 | Eastwood Town | 42 | 11 | 15 | 61 | 64 | −3 | 58
row 12 : 12 | Farsley Celtic | 42 | 6 | 19 | 71 | 76 | −5 | 57
row 13 : 13 | Rossendale United | 42 | 9 | 18 | 73 | 69 | +4 | 54
row 14 : 14 | Newtown | 42 | 12 | 16 | 49 | 62 | −13 | 54
row 15 : 15 | Irlam Town | 42 | 11 | 17 | 61 | 66 | −5 | 53
row 16 : 16 | Workington | 42 | 8 | 20 | 56 | 64 | −8 | 50
row 17 : 17 | Radcliffe Borough | 42 | 7 | 21 | 47 | 62 | −15 | 49
row 18 : 18 | Alfreton Town | 42 | 8 | 21 | 59 | 85 | −26 | 47
row 19 : 19 | Worksop Town | 42 | 5 | 24 | 56 | 95 | −39 | 44
row 20 : 20 | Netherfield | 42 | 6 | 25 | 56 | 89 | −33 | 39
row 21 : 21 | Eastwood Hanley | 42 | 6 | 26 | 45 | 76 | −31 | 36
row 22 : 22 | Penrith | 42 | 9 | 24 | 44 | 88 | −44 | 36 [/Table] Answer this question based on the above table: What is the highest number of goals for for teams with 25 losses?

Answer: 56.0
[Table] header: Position | Team | Played | Drawn | Lost | Goals For | Goals Against | Goal Difference | Points 1 row 1 : 1 | Leek Town | 42 | 8 | 8 | 70 | 31 | +39 | 86
row 2 : 2 | Droylsden | 42 | 6 | 9 | 81 | 46 | +35 | 80 2
row 3 : 3 | Accrington Stanley | 42 | 10 | 10 | 80 | 53 | +27 | 76
row 4 : 4 | Whitley Bay | 42 | 11 | 10 | 93 | 59 | +38 | 74
row 5 : 5 | Emley | 42 | 9 | 13 | 70 | 42 | +28 | 69
row 6 : 6 | Congleton Town | 42 | 12 | 10 | 65 | 53 | +12 | 69 3
row 7 : 7 | Winsford United | 42 | 10 | 14 | 65 | 53 | +12 | 64
row 8 : 8 | Curzon Ashton | 42 | 11 | 14 | 66 | 60 | +6 | 62
row 9 : 9 | Harrogate Town | 42 | 9 | 16 | 68 | 62 | +6 | 60
row 10 : 10 | Lancaster City | 42 | 14 | 13 | 73 | 54 | +19 | 59
row 11 : 11 | Eastwood Town | 42 | 11 | 15 | 61 | 64 | −3 | 58
row 12 : 12 | Farsley Celtic | 42 | 6 | 19 | 71 | 76 | −5 | 57
row 13 : 13 | Rossendale United | 42 | 9 | 18 | 73 | 69 | +4 | 54
row 14 : 14 | Newtown | 42 | 12 | 16 | 49 | 62 | −13 | 54
row 15 : 15 | Irlam Town | 42 | 11 | 17 | 61 | 66 | −5 | 53
row 16 : 16 | Workington | 42 | 8 | 20 | 56 | 64 | −8 | 50
row 17 : 17 | Radcliffe Borough | 42 | 7 | 21 | 47 | 62 | −15 | 49
row 18 : 18 | Alfreton Town | 42 | 8 | 21 | 59 | 85 | −26 | 47
row 19 : 19 | Worksop Town | 42 | 5 | 24 | 56 | 95 | −39 | 44
row 20 : 20 | Netherfield | 42 | 6 | 25 | 56 | 89 | −33 | 39
row 21 : 21 | Eastwood Hanley | 42 | 6 | 26 | 45 | 76 | −31 | 36
row 22 : 22 | Penrith | 42 | 9 | 24 | 44 | 88 | −44 | 36 [/Table] Answer this question based on the above table: What is the most losses for positions under 15 and 66 goals against?

Answer: none
[Table] header: Position | Team | Played | Drawn | Lost | Goals For | Goals Against | Goal Difference | Points 1 row 1 : 1 | Leek Town | 42 | 8 | 8 | 70 | 31 | +39 | 86
row 2 : 2 | Droylsden | 42 | 6 | 9 | 81 | 46 | +35 | 80 2
row 3 : 3 | Accrington Stanley | 42 | 10 | 10 | 80 | 53 | +27 | 76
row 4 : 4 | Whitley Bay | 42 | 11 | 10 | 93 | 59 | +38 | 74
row 5 : 5 | Emley | 42 | 9 | 13 | 70 | 42 | +28 | 69
row 6 : 6 | Congleton Town | 42 | 12 | 10 | 65 | 53 | +12 | 69 3
row 7 : 7 | Winsford United | 42 | 10 | 14 | 65 | 53 | +12 | 64
row 8 : 8 | Curzon Ashton | 42 | 11 | 14 | 66 | 60 | +6 | 62
row 9 : 9 | Harrogate Town | 42 | 9 | 16 | 68 | 62 | +6 | 60
row 10 : 10 | Lancaster City | 42 | 14 | 13 | 73 | 54 | +19 | 59
row 11 : 11 | Eastwood Town | 42 | 11 | 15 | 61 | 64 | −3 | 58
row 12 : 12 | Farsley Celtic | 42 | 6 | 19 | 71 | 76 | −5 | 57
row 13 : 13 | Rossendale United | 42 | 9 | 18 | 73 | 69 | +4 | 54
row 14 : 14 | Newtown | 42 | 12 | 16 | 49 | 62 | −13 | 54
row 15 : 15 | Irlam Town | 42 | 11 | 17 | 61 | 66 | −5 | 53
row 16 : 16 | Workington | 42 | 8 | 20 | 56 | 64 | −8 | 50
row 17 : 17 | Radcliffe Borough | 42 | 7 | 21 | 47 | 62 | −15 | 49
row 18 : 18 | Alfreton Town | 42 | 8 | 21 | 59 | 85 | −26 | 47
row 19 : 19 | Worksop Town | 42 | 5 | 24 | 56 | 95 | −39 | 44
row 20 : 20 | Netherfield | 42 | 6 | 25 | 56 | 89 | −33 | 39
row 21 : 21 | Eastwood Hanley | 42 | 6 | 26 | 45 | 76 | −31 | 36
row 22 : 22 | Penrith | 42 | 9 | 24 | 44 | 88 | −44 | 36 [/Table] Answer this question based on the above table: What is the average goals against for teams with more than 56 goals for and exactly 50 points?

Answer: none
[Table] header: Party | Leader | Seats | % of seats | First Pref votes | % FPv row 1 : Fianna Fáil | Bertie Ahern | 77 | 46.6 | 858,565 | 41.56
row 2 : Fine Gael | Enda Kenny | 51 | 30.9 | 564,428 | 27.32
row 3 : Labour Party | Pat Rabbitte | 20 | 12.1 | 209,175 | 10.13
row 4 : Green Party | Trevor Sargent | 6 | 3.6 | 96,936 | 4.69
row 5 : Sinn Féin | Gerry Adams | 4 | 2.4 | 143,410 | 6.94
row 6 : Progressive Democrats | Michael McDowell | 2 | 1.2 | 56,396 | 2.73
row 7 : Socialist Party | Joe Higgins | 0 | 0 | 13,218 | 0.64
row 8 : People Before Profit | N/A | 0 | 0 | 9,333 | 0.45
row 9 : Workers' Party | Seán Garland | 0 | 0 | 3,026 | 0.15
row 10 : Christian Solidarity | Cathal Loftus | 0 | 0 | 1,705 | 0.08
row 11 : Fathers Rights | Liam Ó Gógáin | 0 | 0 | 1,355 | 0.07
row 12 : Immigration Control | Áine Ní Chonaill | 0 | 0 | 1,329 | 0.06
row 13 : Irish Socialist Network | N/A | 0 | 0 | 505 | 0.02
row 14 : Independent | N/A | 5 | 3.0 | 106,429 | 5.15
row 15 : Ceann Comhairle | N/A | 1† | 0.6 | N/A | N/A
row 16 : Spoilt votes | Spoilt votes | Spoilt votes | Spoilt votes | 19,435 | —
row 17 : Total | Total | 166 | 100 | 2,085,245 | 100
row 18 : Electorate/Turnout | Electorate/Turnout | Electorate/Turnout | Electorate/Turnout | 3,110,914 | 67.0% [/Table] Answer this question based on the above table: Which Leader has Spoilt Votes as % of Seats?

Answer: Spoilt votes
[Table] header: Party | Leader | Seats | % of seats | First Pref votes | % FPv row 1 : Fianna Fáil | Bertie Ahern | 77 | 46.6 | 858,565 | 41.56
row 2 : Fine Gael | Enda Kenny | 51 | 30.9 | 564,428 | 27.32
row 3 : Labour Party | Pat Rabbitte | 20 | 12.1 | 209,175 | 10.13
row 4 : Green Party | Trevor Sargent | 6 | 3.6 | 96,936 | 4.69
row 5 : Sinn Féin | Gerry Adams | 4 | 2.4 | 143,410 | 6.94
row 6 : Progressive Democrats | Michael McDowell | 2 | 1.2 | 56,396 | 2.73
row 7 : Socialist Party | Joe Higgins | 0 | 0 | 13,218 | 0.64
row 8 : People Before Profit | N/A | 0 | 0 | 9,333 | 0.45
row 9 : Workers' Party | Seán Garland | 0 | 0 | 3,026 | 0.15
row 10 : Christian Solidarity | Cathal Loftus | 0 | 0 | 1,705 | 0.08
row 11 : Fathers Rights | Liam Ó Gógáin | 0 | 0 | 1,355 | 0.07
row 12 : Immigration Control | Áine Ní Chonaill | 0 | 0 | 1,329 | 0.06
row 13 : Irish Socialist Network | N/A | 0 | 0 | 505 | 0.02
row 14 : Independent | N/A | 5 | 3.0 | 106,429 | 5.15
row 15 : Ceann Comhairle | N/A | 1† | 0.6 | N/A | N/A
row 16 : Spoilt votes | Spoilt votes | Spoilt votes | Spoilt votes | 19,435 | —
row 17 : Total | Total | 166 | 100 | 2,085,245 | 100
row 18 : Electorate/Turnout | Electorate/Turnout | Electorate/Turnout | Electorate/Turnout | 3,110,914 | 67.0% [/Table] Answer this question based on the above table: What is the %FPv for the Workers' Party?

Answer: 0.15
[Table] header: Party | Leader | Seats | % of seats | First Pref votes | % FPv row 1 : Fianna Fáil | Bertie Ahern | 77 | 46.6 | 858,565 | 41.56
row 2 : Fine Gael | Enda Kenny | 51 | 30.9 | 564,428 | 27.32
row 3 : Labour Party | Pat Rabbitte | 20 | 12.1 | 209,175 | 10.13
row 4 : Green Party | Trevor Sargent | 6 | 3.6 | 96,936 | 4.69
row 5 : Sinn Féin | Gerry Adams | 4 | 2.4 | 143,410 | 6.94
row 6 : Progressive Democrats | Michael McDowell | 2 | 1.2 | 56,396 | 2.73
row 7 : Socialist Party | Joe Higgins | 0 | 0 | 13,218 | 0.64
row 8 : People Before Profit | N/A | 0 | 0 | 9,333 | 0.45
row 9 : Workers' Party | Seán Garland | 0 | 0 | 3,026 | 0.15
row 10 : Christian Solidarity | Cathal Loftus | 0 | 0 | 1,705 | 0.08
row 11 : Fathers Rights | Liam Ó Gógáin | 0 | 0 | 1,355 | 0.07
row 12 : Immigration Control | Áine Ní Chonaill | 0 | 0 | 1,329 | 0.06
row 13 : Irish Socialist Network | N/A | 0 | 0 | 505 | 0.02
row 14 : Independent | N/A | 5 | 3.0 | 106,429 | 5.15
row 15 : Ceann Comhairle | N/A | 1† | 0.6 | N/A | N/A
row 16 : Spoilt votes | Spoilt votes | Spoilt votes | Spoilt votes | 19,435 | —
row 17 : Total | Total | 166 | 100 | 2,085,245 | 100
row 18 : Electorate/Turnout | Electorate/Turnout | Electorate/Turnout | Electorate/Turnout | 3,110,914 | 67.0% [/Table] Answer this question based on the above table: What is the First Pref Votes for the % FPv of 0.06?

Answer: 1329.0
[Table] header: Party | Leader | Seats | % of seats | First Pref votes | % FPv row 1 : Fianna Fáil | Bertie Ahern | 77 | 46.6 | 858,565 | 41.56
row 2 : Fine Gael | Enda Kenny | 51 | 30.9 | 564,428 | 27.32
row 3 : Labour Party | Pat Rabbitte | 20 | 12.1 | 209,175 | 10.13
row 4 : Green Party | Trevor Sargent | 6 | 3.6 | 96,936 | 4.69
row 5 : Sinn Féin | Gerry Adams | 4 | 2.4 | 143,410 | 6.94
row 6 : Progressive Democrats | Michael McDowell | 2 | 1.2 | 56,396 | 2.73
row 7 : Socialist Party | Joe Higgins | 0 | 0 | 13,218 | 0.64
row 8 : People Before Profit | N/A | 0 | 0 | 9,333 | 0.45
row 9 : Workers' Party | Seán Garland | 0 | 0 | 3,026 | 0.15
row 10 : Christian Solidarity | Cathal Loftus | 0 | 0 | 1,705 | 0.08
row 11 : Fathers Rights | Liam Ó Gógáin | 0 | 0 | 1,355 | 0.07
row 12 : Immigration Control | Áine Ní Chonaill | 0 | 0 | 1,329 | 0.06
row 13 : Irish Socialist Network | N/A | 0 | 0 | 505 | 0.02
row 14 : Independent | N/A | 5 | 3.0 | 106,429 | 5.15
row 15 : Ceann Comhairle | N/A | 1† | 0.6 | N/A | N/A
row 16 : Spoilt votes | Spoilt votes | Spoilt votes | Spoilt votes | 19,435 | —
row 17 : Total | Total | 166 | 100 | 2,085,245 | 100
row 18 : Electorate/Turnout | Electorate/Turnout | Electorate/Turnout | Electorate/Turnout | 3,110,914 | 67.0% [/Table] Answer this question based on the above table: What is the First Pref Votes where the Leader is n/a and the Party is Independent?

Answer: 106429.0
[Table] header: Party | Leader | Seats | % of seats | First Pref votes | % FPv row 1 : Fianna Fáil | Bertie Ahern | 77 | 46.6 | 858,565 | 41.56
row 2 : Fine Gael | Enda Kenny | 51 | 30.9 | 564,428 | 27.32
row 3 : Labour Party | Pat Rabbitte | 20 | 12.1 | 209,175 | 10.13
row 4 : Green Party | Trevor Sargent | 6 | 3.6 | 96,936 | 4.69
row 5 : Sinn Féin | Gerry Adams | 4 | 2.4 | 143,410 | 6.94
row 6 : Progressive Democrats | Michael McDowell | 2 | 1.2 | 56,396 | 2.73
row 7 : Socialist Party | Joe Higgins | 0 | 0 | 13,218 | 0.64
row 8 : People Before Profit | N/A | 0 | 0 | 9,333 | 0.45
row 9 : Workers' Party | Seán Garland | 0 | 0 | 3,026 | 0.15
row 10 : Christian Solidarity | Cathal Loftus | 0 | 0 | 1,705 | 0.08
row 11 : Fathers Rights | Liam Ó Gógáin | 0 | 0 | 1,355 | 0.07
row 12 : Immigration Control | Áine Ní Chonaill | 0 | 0 | 1,329 | 0.06
row 13 : Irish Socialist Network | N/A | 0 | 0 | 505 | 0.02
row 14 : Independent | N/A | 5 | 3.0 | 106,429 | 5.15
row 15 : Ceann Comhairle | N/A | 1† | 0.6 | N/A | N/A
row 16 : Spoilt votes | Spoilt votes | Spoilt votes | Spoilt votes | 19,435 | —
row 17 : Total | Total | 166 | 100 | 2,085,245 | 100
row 18 : Electorate/Turnout | Electorate/Turnout | Electorate/Turnout | Electorate/Turnout | 3,110,914 | 67.0% [/Table] Answer this question based on the above table: What is the number of Seats for Leader Enda kenny?

Answer: 51.0
[Table] header: Place | Player | Country | Score | To par row 1 : 1 | Mike Souchak | United States | 68 | –3
row 2 : T2 | Jerry Barber | United States | 69 | –2
row 3 : T2 | Henry Ransom | United States | 69 | –2
row 4 : T3 | Don Cherry (a) | United States | 70 | –1
row 5 : T3 | Bruce Crampton | Australia | 70 | –1
row 6 : T3 | Jack Fleck | United States | 70 | –1
row 7 : T3 | Huston LaClair | United States | 70 | –1
row 8 : T3 | Gary Player | South Africa | 70 | –1
row 9 : T3 | Doug Sanders | United States | 70 | –1
row 10 : T3 | Richard Stranahan | United States | 70 | –1
row 11 : T3 | Joe Taylor | United States | 70 | –1 [/Table] Answer this question based on the above table: WHAT IS AVERAGE SCORE WITH T3 PLACE, FOR DOUG SANDERS?

Answer: 70.0
[Table] header: Place | Player | Country | Score | To par | Money ( $ ) row 1 : 1 | Raymond Floyd | United States | 65-66-70-70=271 | –17 | 40,000
row 2 : 2 | Ben Crenshaw | United States | 70-70-72-67=279 | –9 | 25,000
row 3 : T3 | Jack Nicklaus | United States | 67-69-73-73=28 | –6 | 16,250
row 4 : T3 | Larry Ziegler | United States | 67-71-72-72=28 | –6 | 16,250
row 5 : T5 | Charles Coody | United States | 72-69-70-74=285 | –3 | 11,167
row 6 : T5 | Hale Irwin | United States | 71-77-67-70=2 | –3 | 11,167
row 7 : T5 | Tom Kite | United States | 73-67-72-73=2 | –3 | 11,167
row 8 : 8 | Billy Casper | United States | 71-76-71-69=287 | -1 | 8,000
row 9 : T9 | Roger Maltbie | United States | 72-75-70-71=288 | E | 6,000
row 10 : T9 | Graham Marsh | Australia | 73-68-75-72=2 | E | 6,000
row 11 : T9 | Tom Weiskopf | United States | 73-71-70-74=2 | E | 6,000 [/Table] Answer this question based on the above table: How much is the money ($) when the country is united states, to par is e and the score is 72-75-70-71=288?

Answer: 6000.0
[Table] header: Place | Player | Country | Score | To par | Money ( $ ) row 1 : 1 | Raymond Floyd | United States | 65-66-70-70=271 | –17 | 40,000
row 2 : 2 | Ben Crenshaw | United States | 70-70-72-67=279 | –9 | 25,000
row 3 : T3 | Jack Nicklaus | United States | 67-69-73-73=28 | –6 | 16,250
row 4 : T3 | Larry Ziegler | United States | 67-71-72-72=28 | –6 | 16,250
row 5 : T5 | Charles Coody | United States | 72-69-70-74=285 | –3 | 11,167
row 6 : T5 | Hale Irwin | United States | 71-77-67-70=2 | –3 | 11,167
row 7 : T5 | Tom Kite | United States | 73-67-72-73=2 | –3 | 11,167
row 8 : 8 | Billy Casper | United States | 71-76-71-69=287 | -1 | 8,000
row 9 : T9 | Roger Maltbie | United States | 72-75-70-71=288 | E | 6,000
row 10 : T9 | Graham Marsh | Australia | 73-68-75-72=2 | E | 6,000
row 11 : T9 | Tom Weiskopf | United States | 73-71-70-74=2 | E | 6,000 [/Table] Answer this question based on the above table: what is the to par when the player is roger maltbie?

Answer: E
[Table] header: Place | Player | Country | Score | To par | Money ( $ ) row 1 : 1 | Raymond Floyd | United States | 65-66-70-70=271 | –17 | 40,000
row 2 : 2 | Ben Crenshaw | United States | 70-70-72-67=279 | –9 | 25,000
row 3 : T3 | Jack Nicklaus | United States | 67-69-73-73=28 | –6 | 16,250
row 4 : T3 | Larry Ziegler | United States | 67-71-72-72=28 | –6 | 16,250
row 5 : T5 | Charles Coody | United States | 72-69-70-74=285 | –3 | 11,167
row 6 : T5 | Hale Irwin | United States | 71-77-67-70=2 | –3 | 11,167
row 7 : T5 | Tom Kite | United States | 73-67-72-73=2 | –3 | 11,167
row 8 : 8 | Billy Casper | United States | 71-76-71-69=287 | -1 | 8,000
row 9 : T9 | Roger Maltbie | United States | 72-75-70-71=288 | E | 6,000
row 10 : T9 | Graham Marsh | Australia | 73-68-75-72=2 | E | 6,000
row 11 : T9 | Tom Weiskopf | United States | 73-71-70-74=2 | E | 6,000 [/Table] Answer this question based on the above table: How much is the money ($) when the score is 67-71-72-72=282?

Answer: 0.0
[Table] header: Place | Player | Country | Score | To par | Money ( $ ) row 1 : 1 | Raymond Floyd | United States | 65-66-70-70=271 | –17 | 40,000
row 2 : 2 | Ben Crenshaw | United States | 70-70-72-67=279 | –9 | 25,000
row 3 : T3 | Jack Nicklaus | United States | 67-69-73-73=28 | –6 | 16,250
row 4 : T3 | Larry Ziegler | United States | 67-71-72-72=28 | –6 | 16,250
row 5 : T5 | Charles Coody | United States | 72-69-70-74=285 | –3 | 11,167
row 6 : T5 | Hale Irwin | United States | 71-77-67-70=2 | –3 | 11,167
row 7 : T5 | Tom Kite | United States | 73-67-72-73=2 | –3 | 11,167
row 8 : 8 | Billy Casper | United States | 71-76-71-69=287 | -1 | 8,000
row 9 : T9 | Roger Maltbie | United States | 72-75-70-71=288 | E | 6,000
row 10 : T9 | Graham Marsh | Australia | 73-68-75-72=2 | E | 6,000
row 11 : T9 | Tom Weiskopf | United States | 73-71-70-74=2 | E | 6,000 [/Table] Answer this question based on the above table: what is the to par when the place is 8?

Answer: -1.0
[Table] header: Game | Date | Team | Score | High points | High rebounds | High assists | Location Attendance | Record row 1 : 47 | February 2 | @ New Orleans | W 97–89 (OT) | LaMarcus Aldridge (22) | LaMarcus Aldridge (11) | Jerryd Bayless (6) | New Orleans Arena 14,781 | 30–17
row 2 : 48 | February 4 | @ Dallas | L 99–104 (OT) | Brandon Roy (26) | Brandon Roy (7) | Jerryd Bayless , Travis Outlaw  | American Airlines Center 19,767 | 30–18
row 3 : 49 | February 6 | @ Oklahoma City | L 93–102 (OT) | Brandon Roy (32) | Brandon Roy (9) | Brandon Roy (6) | Ford Center 18,694 | 30–19
row 4 : 50 | February 8 | New York | W 109–108 (OT) | Travis Outlaw (23) | Greg Oden (12) | Brandon Roy (8) | Rose Garden 20,609 | 31–19
row 5 : 51 | February 11 | Oklahoma City | W 106–92 (OT) | Brandon Roy (22) | Joel Przybilla (14) | Jerryd Bayless (8) | Rose Garden 20,050 | 32–19
row 6 : 52 | February 12 | @ Golden State | L 98–105 (OT) | Brandon Roy (37) | Travis Outlaw (12) | Sergio Rodríguez (7) | Oracle Arena 19,322 | 32–20
row 7 : 53 | February 18 | Memphis | W 94–90 (OT) | Brandon Roy (24) | Joel Przybilla (15) | Brandon Roy (9) | Rose Garden 20,385 | 33–20
row 8 : 54 | February 20 | Atlanta | W 108–98 (OT) | Brandon Roy (27) | LaMarcus Aldridge (11) | Steve Blake , Brandon Roy (5) | Rose Garden 20,250 | 34–20
row 9 : 55 | February 22 | L.A. Clippers | W 116–87 (OT) | LaMarcus Aldridge (28) | LaMarcus Aldridge (10) | Steve Blake (17) | Rose Garden 20,447 | 35–20
row 10 : 56 | February 24 | @ Houston | L 94–98 (OT) | Brandon Roy (24) | LaMarcus Aldridge , Joel | Brandon Roy , Steve Blake (5) | Toyota Center 17,515 | 35–21
row 11 : 57 | February 25 | @ San Antonio | L 84–99 (OT) | Channing Frye (15) | Joel Przybilla (10) | Sergio Rodríguez (7) | AT&T Center 18,672 | 35–22
row 12 : 58 | February 27 | @ Minnesota | W 102–82 (OT) | Brandon Roy (19) | LaMarcus Aldridge (10) | Steve Blake (6) | Target Center 17,017 | 36–22 [/Table] Answer this question based on the above table: WHAT IS THE SCORE OF THE GAME LARGER THAN 47, AT THE ROSE GARDEN 20,250 IN ATTENDANCE?

Answer: W 108–98 (OT)
[Table] header: Date | Tournament | Winning score | Margin of victory | Runner(s)-up row 1 : Feb 21, 1987 | Tsumura Hawaiian Ladies Open | –9 (69-71-67= | 2 strokes | Jane Geddes
row 2 : May 31, 1987 | LPGA Corning Classic | –13 (70-69-69- | 1 stroke | Jane Geddes , Betsy King
row 3 : May 14, 1989 | Chrysler-Plymouth Classic | –5 (70-72-72= | 2 strokes | Laura Davies
row 4 : May 20, 1990 | Planters Pat Bradley International | 25 points (3-4-12-6) | 1 point | Beth Daniel
row 5 : Aug 18, 1991 | Northgate Computer Classic | –13 (75-68-68= | Playoff | Jody Anschutz , Beth Daniel [/Table] Answer this question based on the above table: What tournament was on May 31, 1987?

Answer: LPGA Corning Classic
[Table] header: Date | Tournament | Winning score | Margin of victory | Runner(s)-up row 1 : Feb 21, 1987 | Tsumura Hawaiian Ladies Open | –9 (69-71-67= | 2 strokes | Jane Geddes
row 2 : May 31, 1987 | LPGA Corning Classic | –13 (70-69-69- | 1 stroke | Jane Geddes , Betsy King
row 3 : May 14, 1989 | Chrysler-Plymouth Classic | –5 (70-72-72= | 2 strokes | Laura Davies
row 4 : May 20, 1990 | Planters Pat Bradley International | 25 points (3-4-12-6) | 1 point | Beth Daniel
row 5 : Aug 18, 1991 | Northgate Computer Classic | –13 (75-68-68= | Playoff | Jody Anschutz , Beth Daniel [/Table] Answer this question based on the above table: What tournament had a winning score of –9 (69-71-67=207)?

Answer: none
[Table] header: Date | Tournament | Winning score | Margin of victory | Runner(s)-up row 1 : Feb 21, 1987 | Tsumura Hawaiian Ladies Open | –9 (69-71-67= | 2 strokes | Jane Geddes
row 2 : May 31, 1987 | LPGA Corning Classic | –13 (70-69-69- | 1 stroke | Jane Geddes , Betsy King
row 3 : May 14, 1989 | Chrysler-Plymouth Classic | –5 (70-72-72= | 2 strokes | Laura Davies
row 4 : May 20, 1990 | Planters Pat Bradley International | 25 points (3-4-12-6) | 1 point | Beth Daniel
row 5 : Aug 18, 1991 | Northgate Computer Classic | –13 (75-68-68= | Playoff | Jody Anschutz , Beth Daniel [/Table] Answer this question based on the above table: Who was the runner(s)-up when the winning score was –13 (75-68-68=211)?

Answer: none
[Table] header: Date | Tournament | Winning score | Margin of victory | Runner(s)-up row 1 : Feb 21, 1987 | Tsumura Hawaiian Ladies Open | –9 (69-71-67= | 2 strokes | Jane Geddes
row 2 : May 31, 1987 | LPGA Corning Classic | –13 (70-69-69- | 1 stroke | Jane Geddes , Betsy King
row 3 : May 14, 1989 | Chrysler-Plymouth Classic | –5 (70-72-72= | 2 strokes | Laura Davies
row 4 : May 20, 1990 | Planters Pat Bradley International | 25 points (3-4-12-6) | 1 point | Beth Daniel
row 5 : Aug 18, 1991 | Northgate Computer Classic | –13 (75-68-68= | Playoff | Jody Anschutz , Beth Daniel [/Table] Answer this question based on the above table: What tournament had a 1 point margin of victory?

Answer: Planters Pat Bradley International
[Table] header: Date | Tournament | Winning score | Margin of victory | Runner(s)-up row 1 : Feb 21, 1987 | Tsumura Hawaiian Ladies Open | –9 (69-71-67= | 2 strokes | Jane Geddes
row 2 : May 31, 1987 | LPGA Corning Classic | –13 (70-69-69- | 1 stroke | Jane Geddes , Betsy King
row 3 : May 14, 1989 | Chrysler-Plymouth Classic | –5 (70-72-72= | 2 strokes | Laura Davies
row 4 : May 20, 1990 | Planters Pat Bradley International | 25 points (3-4-12-6) | 1 point | Beth Daniel
row 5 : Aug 18, 1991 | Northgate Computer Classic | –13 (75-68-68= | Playoff | Jody Anschutz , Beth Daniel [/Table] Answer this question based on the above table: What tournament was Laura Davies the runner-up?

Answer: Chrysler-Plymouth Classic
[Table] header: Date | Venue | Score | Result | Competition row 1 : 26 June 1955 | Råsunda Stadium , Stockholm | 1–0 | 6–0 | Friendly
row 2 : 26 June 1955 | Råsunda Stadium , Stockholm | 2–0 | 6–0 | Friendly
row 3 : 26 June 1955 | Råsunda Stadium , Stockholm | 4–0 | 6–0 | Friendly
row 4 : 16 September 1955 | Dynamo Stadium , Moscow | 2–0 | 11–1 | Friendly
row 5 : 16 September 1955 | Dynamo Stadium , Moscow | 4–0 | 11–1 | Friendly
row 6 : 16 September 1955 | Dynamo Stadium , Moscow | 7–0 | 11–1 | Friendly
row 7 : 23 October 1955 | Dynamo Stadium, Moscow | 1–1 | 2–2 | Friendly
row 8 : 23 May 1956 | Dynamo Stadium, Moscow | 3–0 | 5–1 | Friendly
row 9 : 15 September 1956 | Niedersachsenstadion  | 1–0 | 2–1 | Friendly
row 10 : 24 November 1956 | Olympic Park Stadium , Melbourne | 2–0 | 2–1 | 1956 Summer Olympics
row 11 : 5 December 1956 | Olympic Park Stadium, Melbourne | 1–1 | 2–1 | 1956 Summer Olympics
row 12 : 1 June 1957 | Central Lenin Stadium , Moscow | 1–1 | 1–1 | Friendly
row 13 : 21 July 1957 | Vasil Levski National Stadium , Sofia | 1–0 | 4–0 | Friendly
row 14 : 21 July 1957 | Vasil Levski National Stadium , Sofia | 3–0 | 4–0 | Friendly
row 15 : 15 August 1957 | Helsinki Olympic Stadium , Helsinki | 6–0 | 10–0 | 1958 World Cup qualifier
row 16 : 15 August 1957 | Helsinki Olympic Stadium , Helsinki | 8–0 | 10–0 | 1958 World Cup qualifier
row 17 : 22 September 1957 | Népstadion , Budapest | 2–1 | 2–1 | Friendly
row 18 : 24 November 1957 | Zentralstadion , Leipzig | 1–0 | 2–1 | 1958 World Cup qualifier
row 19 : 23 October 1966 | Central Lenin Stadium, Moscow | 1–0 | 2–2 | Friendly
row 20 : 3 June 1967 | Parc des Princes , Paris | 4–2 | 4–2 | Friendly
row 21 : 11 June 1967 | Central Lenin Stadium, Moscow | 4–3 | 4–3 | Euro 1968 qualifier
row 22 : 8 October 1967 | Vasil Levski National Stadium, Sofia | 1–1 | 2–1 | Friendly
row 23 : 17 December 1967 | Estadio Nacional de Chile | 2–0 | 4–1 | Friendly
row 24 : 17 December 1967 | Estadio Nacional de Chile | 3–0 | 4–1 | Friendly
row 25 : 17 December 1967 | Estadio Nacional de Chile | 4–0 | 4–1 | Friendly [/Table] Answer this question based on the above table: What is the venue of the game that was played on 23 October 1966?

Answer: Central Lenin Stadium, Moscow
[Table] header: Date | Venue | Score | Result | Competition row 1 : 26 June 1955 | Råsunda Stadium , Stockholm | 1–0 | 6–0 | Friendly
row 2 : 26 June 1955 | Råsunda Stadium , Stockholm | 2–0 | 6–0 | Friendly
row 3 : 26 June 1955 | Råsunda Stadium , Stockholm | 4–0 | 6–0 | Friendly
row 4 : 16 September 1955 | Dynamo Stadium , Moscow | 2–0 | 11–1 | Friendly
row 5 : 16 September 1955 | Dynamo Stadium , Moscow | 4–0 | 11–1 | Friendly
row 6 : 16 September 1955 | Dynamo Stadium , Moscow | 7–0 | 11–1 | Friendly
row 7 : 23 October 1955 | Dynamo Stadium, Moscow | 1–1 | 2–2 | Friendly
row 8 : 23 May 1956 | Dynamo Stadium, Moscow | 3–0 | 5–1 | Friendly
row 9 : 15 September 1956 | Niedersachsenstadion  | 1–0 | 2–1 | Friendly
row 10 : 24 November 1956 | Olympic Park Stadium , Melbourne | 2–0 | 2–1 | 1956 Summer Olympics
row 11 : 5 December 1956 | Olympic Park Stadium, Melbourne | 1–1 | 2–1 | 1956 Summer Olympics
row 12 : 1 June 1957 | Central Lenin Stadium , Moscow | 1–1 | 1–1 | Friendly
row 13 : 21 July 1957 | Vasil Levski National Stadium , Sofia | 1–0 | 4–0 | Friendly
row 14 : 21 July 1957 | Vasil Levski National Stadium , Sofia | 3–0 | 4–0 | Friendly
row 15 : 15 August 1957 | Helsinki Olympic Stadium , Helsinki | 6–0 | 10–0 | 1958 World Cup qualifier
row 16 : 15 August 1957 | Helsinki Olympic Stadium , Helsinki | 8–0 | 10–0 | 1958 World Cup qualifier
row 17 : 22 September 1957 | Népstadion , Budapest | 2–1 | 2–1 | Friendly
row 18 : 24 November 1957 | Zentralstadion , Leipzig | 1–0 | 2–1 | 1958 World Cup qualifier
row 19 : 23 October 1966 | Central Lenin Stadium, Moscow | 1–0 | 2–2 | Friendly
row 20 : 3 June 1967 | Parc des Princes , Paris | 4–2 | 4–2 | Friendly
row 21 : 11 June 1967 | Central Lenin Stadium, Moscow | 4–3 | 4–3 | Euro 1968 qualifier
row 22 : 8 October 1967 | Vasil Levski National Stadium, Sofia | 1–1 | 2–1 | Friendly
row 23 : 17 December 1967 | Estadio Nacional de Chile | 2–0 | 4–1 | Friendly
row 24 : 17 December 1967 | Estadio Nacional de Chile | 3–0 | 4–1 | Friendly
row 25 : 17 December 1967 | Estadio Nacional de Chile | 4–0 | 4–1 | Friendly [/Table] Answer this question based on the above table: Where was the friendly competition on 17 December 1967 played at?

Answer: Estadio Nacional de Chile, Estadio Nacional de Chile, Estadio Nacional de Chile
[Table] header: Tournament | 2006 | 2007 | 2008 | 2009 | 2010 | 2011 | 2012 row 1 : Grand Slam Tournaments | Grand Slam Tournaments | Grand Slam Tournaments | Grand Slam Tournaments | Grand Slam Tournaments | Grand Slam Tournaments | Grand Slam Tournaments | Grand Slam Tournaments
row 2 : Australian Open | A | A | A | A | A | A | A
row 3 : French Open | A | A | A | A | A | A | Q1
row 4 : Wimbledon | A | A | A | A | A | A | Q1
row 5 : US Open | A | A | A | A | A | Q2 | Q1
row 6 : SR | 0 / 0 | 0 / 0 | 0 / 0 | 0 / 0 | 0 / 0 | 0 / 0 | 0 / 0
row 7 : Win–Loss | 0–0 | 0–0 | 0–0 | 0–0 | 0–0 | 0–0 | 0–0
row 8 : ATP World Tour Masters 1000 | ATP World Tour Masters 1000 | ATP World Tour Masters 1000 | ATP World Tour Masters 1000 | ATP World Tour Masters 1000 | ATP World Tour Masters 1000 | ATP World Tour Masters 1000 | ATP World Tour Masters 1000
row 9 : Indian Wells | A | A | A | A | A | A | Q1
row 10 : Miami | A | A | Q1 | A | A | Q1 | Q1
row 11 : Madrid | A | A | A | A | A | A | A
row 12 : SR | 0 / 0 | 0 / 0 | 0 / 0 | 0 / 0 | 0 / 0 | 0 / 0 | 0 / 0
row 13 : Career Statistics | Career Statistics | Career Statistics | Career Statistics | Career Statistics | Career Statistics | Career Statistics | Career Statistics
row 14 : ATP Tournaments Played | 1 | 0 | 1 | 0 | 0 | 1 | 1
row 15 : ATP Finals Reached | 0 | 0 | 0 | 0 | 0 | 0 | 0
row 16 : ATP Tournaments Won | 0 | 0 | 0 | 0 | 0 | 0 | 0
row 17 : Statistics by surface | Statistics by surface | Statistics by surface | Statistics by surface | Statistics by surface | Statistics by surface | Statistics by surface | Statistics by surface
row 18 : Hard Win–Loss | 0–0 | 0–1 | 0–1 | 0–0 | 0–0 | 0–0 | 0–0
row 19 : Clay Win–Loss | 0–1 | 0–0 | 0–2 | 0–0 | 0–0 | 0–1 | 0–1
row 20 : Grass Win–Loss | 0–0 | 0–0 | 0–0 | 0–0 | 0–0 | 0–0 | 0–0
row 21 : Carpet Win–Loss | 0–0 | 1–0 | 0–0 | 0–0 | 0–0 | 0–0 | 0–0
row 22 : Overall Win–Loss | 0–1 | 1–1 | 0–3 | 0–0 | 0–0 | 0–1 | 0–1
row 23 : Win (%) | 0% | 50% | 0% | 0% | 0% | 0% | 0%
row 24 : Year-End Ranking | 936 | 638 | 578 | 770 | 603 | 172 | 144 [/Table] Answer this question based on the above table: What 2009 has statistics by surface in 2012?

Answer: Statistics by surface
[Table] header: Tournament | 2006 | 2007 | 2008 | 2009 | 2010 | 2011 | 2012 row 1 : Grand Slam Tournaments | Grand Slam Tournaments | Grand Slam Tournaments | Grand Slam Tournaments | Grand Slam Tournaments | Grand Slam Tournaments | Grand Slam Tournaments | Grand Slam Tournaments
row 2 : Australian Open | A | A | A | A | A | A | A
row 3 : French Open | A | A | A | A | A | A | Q1
row 4 : Wimbledon | A | A | A | A | A | A | Q1
row 5 : US Open | A | A | A | A | A | Q2 | Q1
row 6 : SR | 0 / 0 | 0 / 0 | 0 / 0 | 0 / 0 | 0 / 0 | 0 / 0 | 0 / 0
row 7 : Win–Loss | 0–0 | 0–0 | 0–0 | 0–0 | 0–0 | 0–0 | 0–0
row 8 : ATP World Tour Masters 1000 | ATP World Tour Masters 1000 | ATP World Tour Masters 1000 | ATP World Tour Masters 1000 | ATP World Tour Masters 1000 | ATP World Tour Masters 1000 | ATP World Tour Masters 1000 | ATP World Tour Masters 1000
row 9 : Indian Wells | A | A | A | A | A | A | Q1
row 10 : Miami | A | A | Q1 | A | A | Q1 | Q1
row 11 : Madrid | A | A | A | A | A | A | A
row 12 : SR | 0 / 0 | 0 / 0 | 0 / 0 | 0 / 0 | 0 / 0 | 0 / 0 | 0 / 0
row 13 : Career Statistics | Career Statistics | Career Statistics | Career Statistics | Career Statistics | Career Statistics | Career Statistics | Career Statistics
row 14 : ATP Tournaments Played | 1 | 0 | 1 | 0 | 0 | 1 | 1
row 15 : ATP Finals Reached | 0 | 0 | 0 | 0 | 0 | 0 | 0
row 16 : ATP Tournaments Won | 0 | 0 | 0 | 0 | 0 | 0 | 0
row 17 : Statistics by surface | Statistics by surface | Statistics by surface | Statistics by surface | Statistics by surface | Statistics by surface | Statistics by surface | Statistics by surface
row 18 : Hard Win–Loss | 0–0 | 0–1 | 0–1 | 0–0 | 0–0 | 0–0 | 0–0
row 19 : Clay Win–Loss | 0–1 | 0–0 | 0–2 | 0–0 | 0–0 | 0–1 | 0–1
row 20 : Grass Win–Loss | 0–0 | 0–0 | 0–0 | 0–0 | 0–0 | 0–0 | 0–0
row 21 : Carpet Win–Loss | 0–0 | 1–0 | 0–0 | 0–0 | 0–0 | 0–0 | 0–0
row 22 : Overall Win–Loss | 0–1 | 1–1 | 0–3 | 0–0 | 0–0 | 0–1 | 0–1
row 23 : Win (%) | 0% | 50% | 0% | 0% | 0% | 0% | 0%
row 24 : Year-End Ranking | 936 | 638 | 578 | 770 | 603 | 172 | 144 [/Table] Answer this question based on the above table: What 2001 has a ATP World Tour Masters 1000 2007?

Answer: ATP World Tour Masters 1000
[Table] header: Tournament | 2006 | 2007 | 2008 | 2009 | 2010 | 2011 | 2012 row 1 : Grand Slam Tournaments | Grand Slam Tournaments | Grand Slam Tournaments | Grand Slam Tournaments | Grand Slam Tournaments | Grand Slam Tournaments | Grand Slam Tournaments | Grand Slam Tournaments
row 2 : Australian Open | A | A | A | A | A | A | A
row 3 : French Open | A | A | A | A | A | A | Q1
row 4 : Wimbledon | A | A | A | A | A | A | Q1
row 5 : US Open | A | A | A | A | A | Q2 | Q1
row 6 : SR | 0 / 0 | 0 / 0 | 0 / 0 | 0 / 0 | 0 / 0 | 0 / 0 | 0 / 0
row 7 : Win–Loss | 0–0 | 0–0 | 0–0 | 0–0 | 0–0 | 0–0 | 0–0
row 8 : ATP World Tour Masters 1000 | ATP World Tour Masters 1000 | ATP World Tour Masters 1000 | ATP World Tour Masters 1000 | ATP World Tour Masters 1000 | ATP World Tour Masters 1000 | ATP World Tour Masters 1000 | ATP World Tour Masters 1000
row 9 : Indian Wells | A | A | A | A | A | A | Q1
row 10 : Miami | A | A | Q1 | A | A | Q1 | Q1
row 11 : Madrid | A | A | A | A | A | A | A
row 12 : SR | 0 / 0 | 0 / 0 | 0 / 0 | 0 / 0 | 0 / 0 | 0 / 0 | 0 / 0
row 13 : Career Statistics | Career Statistics | Career Statistics | Career Statistics | Career Statistics | Career Statistics | Career Statistics | Career Statistics
row 14 : ATP Tournaments Played | 1 | 0 | 1 | 0 | 0 | 1 | 1
row 15 : ATP Finals Reached | 0 | 0 | 0 | 0 | 0 | 0 | 0
row 16 : ATP Tournaments Won | 0 | 0 | 0 | 0 | 0 | 0 | 0
row 17 : Statistics by surface | Statistics by surface | Statistics by surface | Statistics by surface | Statistics by surface | Statistics by surface | Statistics by surface | Statistics by surface
row 18 : Hard Win–Loss | 0–0 | 0–1 | 0–1 | 0–0 | 0–0 | 0–0 | 0–0
row 19 : Clay Win–Loss | 0–1 | 0–0 | 0–2 | 0–0 | 0–0 | 0–1 | 0–1
row 20 : Grass Win–Loss | 0–0 | 0–0 | 0–0 | 0–0 | 0–0 | 0–0 | 0–0
row 21 : Carpet Win–Loss | 0–0 | 1–0 | 0–0 | 0–0 | 0–0 | 0–0 | 0–0
row 22 : Overall Win–Loss | 0–1 | 1–1 | 0–3 | 0–0 | 0–0 | 0–1 | 0–1
row 23 : Win (%) | 0% | 50% | 0% | 0% | 0% | 0% | 0%
row 24 : Year-End Ranking | 936 | 638 | 578 | 770 | 603 | 172 | 144 [/Table] Answer this question based on the above table: What 2010 has an A 2006 & 2011?

Answer: A, A, A, A, A
[Table] header: Tournament | 2006 | 2007 | 2008 | 2009 | 2010 | 2011 | 2012 row 1 : Grand Slam Tournaments | Grand Slam Tournaments | Grand Slam Tournaments | Grand Slam Tournaments | Grand Slam Tournaments | Grand Slam Tournaments | Grand Slam Tournaments | Grand Slam Tournaments
row 2 : Australian Open | A | A | A | A | A | A | A
row 3 : French Open | A | A | A | A | A | A | Q1
row 4 : Wimbledon | A | A | A | A | A | A | Q1
row 5 : US Open | A | A | A | A | A | Q2 | Q1
row 6 : SR | 0 / 0 | 0 / 0 | 0 / 0 | 0 / 0 | 0 / 0 | 0 / 0 | 0 / 0
row 7 : Win–Loss | 0–0 | 0–0 | 0–0 | 0–0 | 0–0 | 0–0 | 0–0
row 8 : ATP World Tour Masters 1000 | ATP World Tour Masters 1000 | ATP World Tour Masters 1000 | ATP World Tour Masters 1000 | ATP World Tour Masters 1000 | ATP World Tour Masters 1000 | ATP World Tour Masters 1000 | ATP World Tour Masters 1000
row 9 : Indian Wells | A | A | A | A | A | A | Q1
row 10 : Miami | A | A | Q1 | A | A | Q1 | Q1
row 11 : Madrid | A | A | A | A | A | A | A
row 12 : SR | 0 / 0 | 0 / 0 | 0 / 0 | 0 / 0 | 0 / 0 | 0 / 0 | 0 / 0
row 13 : Career Statistics | Career Statistics | Career Statistics | Career Statistics | Career Statistics | Career Statistics | Career Statistics | Career Statistics
row 14 : ATP Tournaments Played | 1 | 0 | 1 | 0 | 0 | 1 | 1
row 15 : ATP Finals Reached | 0 | 0 | 0 | 0 | 0 | 0 | 0
row 16 : ATP Tournaments Won | 0 | 0 | 0 | 0 | 0 | 0 | 0
row 17 : Statistics by surface | Statistics by surface | Statistics by surface | Statistics by surface | Statistics by surface | Statistics by surface | Statistics by surface | Statistics by surface
row 18 : Hard Win–Loss | 0–0 | 0–1 | 0–1 | 0–0 | 0–0 | 0–0 | 0–0
row 19 : Clay Win–Loss | 0–1 | 0–0 | 0–2 | 0–0 | 0–0 | 0–1 | 0–1
row 20 : Grass Win–Loss | 0–0 | 0–0 | 0–0 | 0–0 | 0–0 | 0–0 | 0–0
row 21 : Carpet Win–Loss | 0–0 | 1–0 | 0–0 | 0–0 | 0–0 | 0–0 | 0–0
row 22 : Overall Win–Loss | 0–1 | 1–1 | 0–3 | 0–0 | 0–0 | 0–1 | 0–1
row 23 : Win (%) | 0% | 50% | 0% | 0% | 0% | 0% | 0%
row 24 : Year-End Ranking | 936 | 638 | 578 | 770 | 603 | 172 | 144 [/Table] Answer this question based on the above table: What 2009 has a 0 in 2008 & 2010?

Answer: 0, 0
[Table] header: Player | Country | Year(s) won | Total | To par | Finish row 1 : Jack Nicklaus | United States | 1962 , 1967 , 1972 , 1980 | 280 | E | T6
row 2 : Johnny Miller | United States | 1973 | 285 | +5 | T23
row 3 : Gary Player | South Africa | 1965 | 286 | +6 | T26
row 4 : Jerry Pate | United States | 1976 | 286 | +6 | T26
row 5 : Hubert Green | United States | 1977 | 288 | +8 | T37
row 6 : Andy North | United States | 1978 | 290 | +10 | T43
row 7 : Hale Irwin | United States | 1974 , 1979 | 292 | +12 | T58 [/Table] Answer this question based on the above table: What was the finishing position of Hale Irwin, of the United states?

Answer: T58
[Table] header: Player | Country | Year(s) won | Total | To par | Finish row 1 : Jack Nicklaus | United States | 1962 , 1967 , 1972 , 1980 | 280 | E | T6
row 2 : Johnny Miller | United States | 1973 | 285 | +5 | T23
row 3 : Gary Player | South Africa | 1965 | 286 | +6 | T26
row 4 : Jerry Pate | United States | 1976 | 286 | +6 | T26
row 5 : Hubert Green | United States | 1977 | 288 | +8 | T37
row 6 : Andy North | United States | 1978 | 290 | +10 | T43
row 7 : Hale Irwin | United States | 1974 , 1979 | 292 | +12 | T58 [/Table] Answer this question based on the above table: Where did the player who won in 1965 finish?

Answer: T26