Information Venue Statistics Results History   Contact
Player Played Won Drawn Lost PPG GS AGS HT OG CS CS% Ch% WS% MCW MCL CWLS Pos Late    Rank   
Alan Dam 52 14 17 21 1.1 3 0.2 0 0 10 19% 26% 41% 2 5 -  M 1 - W D W L D
Alessio 30 16 5 9 1.8 17 1.5 0 0 13 43% 18% 0% 4 2 -  AM 7 4 = (-1) W W D L D
Alexander Kowalski 3 1 2 0 - 0 - 0 0 0 - - - 1 0 -  M - - W D D
Alex Gibson 15 8 3 4 1.8 5 1.0 0 0 8 53% 40% 0% 4 2 -  M 5 22 (-4) W D D L D
Alex Marina 123 49 29 45 1.4 25 0.5 1 0 28 23% 22% 26% 7 4 1L  M 8 - W W L W L
Alex Newins 204 81 35 88 1.4 165 2.3 20 0 37 18% 26% 31% 9 5 1L  A 8 7 L L W W L
Ali Pirbudak 188 75 42 71 1.4 46 0.6 2 2 37 20% 33% 19% 6 8 -  M 5 23 = D L W L D
Andrew Twagira 106 42 28 36 1.5 44 1.2 0 0 19 18% 36% 22% 6 6 3L  AM 1 10 = D D L L L
Andy Rowland 320 113 61 146 1.3 1 0.0 0 5 40 13% 21% 30% 4 7 1L  M 2 - D W L W L
Ayo 29 10 8 11 1.3 0 0 0 0 10 34% 20% 10% 2 4 -  DM 2 - L L D L D
Bill Park 146 59 20 67 1.3 14 0.3 0 1 24 16% 30% 29% 6 8 1L  M 3 - L L L W L
Carlton Dickson 108 51 22 35 1.6 17 0.4 0 1 25 23% 31% 12% 5 3 1L  D 1 17 = (+1) W D W W L
Catalin 3 0 2 1 - 0 - 0 0 2 - - - 0 1 -  GK - - D L D
Cathal Wharton 132 41 34 57 1.2 7 0.1 0 0 26 20% 21% 34% 5 6 6L  DM 5 - L L L L L
Chris Kemp 188 79 34 75 1.4 22 0.4 0 0 33 18% 29% 22% 4 8 -  DM 8 3 W D W L D
Christian Williams 12 7 1 4 1.8 0 0 0 0 3 25% 40% 0% 3 1 1W  M 2 - W W W D W
Conor McNamara 74 24 21 29 1.3 13 0.5 0 0 20 27% 22% 33% 5 6 1W  DM 3 - L W D L W
Damilola Owa 77 32 19 26 1.5 17 0.6 1 0 21 27% 43% 25% 5 4 2W  M 1 13 = (+3) D L L W W
Daniel Andreica 79 35 21 23 1.6 1 0.0 0 1 27 34% 28% 10% 4 3 -  D - 33 = (-2) W L D L D
Daniel Mensah 61 21 17 23 1.3 9 0.4 0 0 15 25% 32% 18% 2 4 -  M 4 17 = (-1) D L D W D
David Lilley 158 59 43 56 1.4 0 0.0 0 2 41 26% 29% 30% 5 5 -  D 2 - W D W L D
Eddie Chan 347 139 71 137 1.4 18 0.2 0 1 47 14% 27% 25% 5 6 2W  D 1 19 = (+2) D L L W W
Eddy Mukasa 15 4 2 9 0.9 2 0.3 0 0 3 20% 0% 50% 3 5 1L  M - - D W W W L
Elder Monte 38 17 9 12 1.6 0 0 0 0 18 47% 23% 8% 3 2 -  M - - W W D L D
Emmanuel Oyelowo 9 6 0 3 - 0 - 0 0 4 - - - 5 2 1W  M 1 - W W W L W
Eric Henry 15 8 2 5 1.7 2 0.4 0 0 5 33% 40% 0% 3 2 2W  M - - L W L W W
Ernesto 96 42 27 27 1.6 9 0.2 0 1 32 33% 35% 27% 6 5 1W  DM 1 29 = (+1) W D D L W
Florin Herman 142 53 32 57 1.3 5 0.1 0 1 25 18% 21% 27% 5 8 -  D - - D W D L D
Frederik Lloyd 208 90 47 71 1.5 65 0.8 0 0 41 20% 28% 18% 6 4 1W  M 17 8 = (-1) W W L L W
Gabriel Paun 196 75 38 83 1.3 3 0.0 0 1 31 16% 24% 27% 4 4 1L  D 1 - W L L W L
George Laird 43 15 10 18 1.3 11 0.7 0 0 14 33% 20% 40% 3 5 1L  AM 3 13 = (-1) D W L W L
Hassan Shah 220 90 47 83 1.4 106 1.2 2 1 47 21% 31% 23% 5 5 2W  AM - - D W L W W
Ibrahim 44 13 12 19 1.2 2 0.1 0 0 15 34% 0% 27% 2 3 -  M - - W L D L D
Ivan Epifanio 3 0 0 3 - 0 - 0 0 0 - - - 0 3 3L  M - - L L L
Ize Kole 260 95 56 109 1.3 20 0.2 0 2 51 20% 29% 32% 6 6 1L  M 29 - D W W W L
Jacob Parsons 25 11 6 8 1.6 0 0 0 0 11 44% 11% 0% 2 2 1W  GK 2 32 (-1) L W W L W
Jen fung Pang 76 27 12 37 1.2 6 0.2 0 0 21 28% 21% 28% 4 5 1W  M 2 - L D L L W
Jeremy Steel 3 2 1 0 - 1 - 0 0 2 - - - 1 0 1W  M - - W D W
Joseph Williams 3 0 0 3 - 0 - 0 0 0 - - - 0 3 3L  M - - L L L
Junior Osivaya 3 1 1 1 - 1 - 0 0 2 - - - 1 1 1W  M - - D L W
Lekan Olukotun 256 103 56 97 1.4 22 0.2 0 2 54 21% 30% 28% 6 6 1L  DM 1 29 = (+2) L W W W L
Liam Rumsey 30 13 6 11 1.5 2 0.2 0 0 11 37% 20% 20% 4 3 1L  AM 1 - W W W W L
Lucien Cab 9 3 1 5 - 4 - 0 0 1 - - - 1 2 1L  M 2 - W L L W L
Luso Adey 56 19 18 19 1.3 0 0 0 0 15 27% 26% 26% 4 3 1W  D 7 - D D D L W
Mansingh 26 10 6 10 1.4 0 0.0 0 1 10 38% 44% 44% 3 4 1L  D 7 - W D L W L
Manuel Cao 263 100 73 90 1.4 235 2.4 24 0 47 18% 29% 22% 5 6 1W  A - 8 = (-1) D L D L W
Mark Barber 57 23 14 20 1.5 0 0 0 0 19 33% 30% 18% 3 3 2W  D 10 19 = (+2) L W L W W
Mark Lascelles 333 131 77 125 1.4 5 0.0 0 3 65 20% 31% 29% 7 6 1W  D - 13 = (+1) L L D L W
Max Arinaitwe 275 109 66 100 1.4 80 0.9 1 0 57 21% 27% 25% 6 5 -  AM 19 2 L W W L D
Max Reeve 15 5 4 6 1.3 2 0.4 0 0 5 33% 20% 20% 1 3 1L  M - - D D W D L
Michael Brerro 266 100 56 110 1.3 14 0.2 1 1 46 17% 26% 25% 4 5 2W  DM 2 - W L L W W
Michal Krol 23 7 6 10 1.2 6 0.5 0 0 4 17% 32% 18% 3 5 1W  M - 13 = (+1) W L L L W
Mondli Mahlangu 3 1 0 2 - 0 - 0 0 0 - - - 1 1 1L  M 1 - L W L
Motty 88 37 15 36 1.4 0 0.0 0 1 12 14% 37% 28% 4 5 1W  D - - L L L L W
Mustapha 105 41 24 40 1.4 0 0 0 0 20 19% 24% 14% 3 4 2W  D 1 19 = (-1) W D L W W
Muz Ngwenya 209 92 51 66 1.6 67 0.8 2 0 43 21% 36% 15% 5 4 1L  DM 2 1 D W L W L
Nasir Pasha 42 11 14 17 1.1 3 0.2 0 0 11 26% 13% 31% 2 4 -  M 5 - D L W W D
Nathan Holland 8 3 2 3 - 1 - 0 0 1 - - - 1 2 1W  M - - W D L L W
Neef 68 19 17 32 1.1 3 0.1 0 0 15 22% 25% 45% 2 6 1L  D 2 - W D L W L
Niall Wharton 156 65 36 55 1.5 2 0.0 0 1 50 32% 25% 25% 5 5 -  D 6 23 = W W W L D
Nicholas Ofonagoro 16 8 5 3 1.8 7 1.2 0 0 4 25% 50% 0% 4 1 1L  M 1 23 = L D W D L
Ola Mi 3 0 0 3 - 0 - 0 0 0 - - - 0 3 3L  M - - L L L
Ore Sokoya 147 54 39 54 1.4 33 0.6 1 0 31 21% 32% 28% 6 7 -  AM 24 - D L W L D
PJ Okonmah 3 2 1 0 - 0 - 0 0 1 - - - 1 0 1W  M 1 - W D W
Pravas Rijal 3 1 0 2 - 0 - 0 0 1 - - - 1 2 2L  M 1 - W L L
Rafhael Nogueira 6 4 0 2 - 5 - 0 0 2 - - - 3 1 1L  AM - - L W W W L
Ravi Singh 251 100 42 109 1.4 102 1.1 5 0 43 17% 26% 28% 5 6 1L  A 2 - W L L W L
Raz Nganga 55 27 10 18 1.7 10 0.6 0 0 13 24% 17% 15% 5 3 1L  M 10 33 = (+1) W W W W L
Roemello 6 3 2 1 - 0 - 0 0 3 - - - 1 1 1W  D 1 - L D W D W
Ryan McNamara 212 79 43 90 1.3 29 0.4 0 0 39 18% 24% 33% 5 4 1W  M 8 - L L D L W
Said Khan 287 121 62 104 1.5 76 0.8 2 0 54 19% 30% 25% 7 5 1L  A 15 29 = (-6) W L L W L
Sam Holloway 184 74 42 68 1.4 112 1.5 10 0 36 20% 27% 24% 5 4 1L  AM - 23 = W L W W L
Sam Skinner 84 28 19 37 1.2 13 0.4 0 0 30 36% 21% 39% 2 3 1L  M - - D W L W L
Sean Laird 37 12 5 20 1.1 1 0.1 0 0 9 24% 14% 57% 2 3 1L  M 2 - L L L W L
Shawn Kelly 15 9 3 3 2.0 6 1.2 0 0 6 40% 40% 0% 7 1 1L  M - 33 = (+1) W W W W L
Shirwan Didar 268 102 58 108 1.4 5 0.1 0 2 50 19% 26% 29% 5 6 1L  D 3 - W W W W L
Shpend Nova 20 9 6 5 1.7 7 0.9 0 0 6 30% 25% 13% 3 2 1L  M - 23 = W W W D L
Simon Holmes 114 56 24 34 1.7 16 0.3 0 1 25 22% 36% 18% 5 3 3L  M - - W D L L L
Smari 51 30 10 11 2.0 11 0.6 0 0 16 31% 33% 0% 7 2 1W  M 1 10 = D W W L W
Stef Spain 16 5 3 8 1.1 1 0.2 0 2 2 13% 17% 33% 2 3 1L  DM - - L D W D L
Stevey Yeung 198 80 44 74 1.4 20 0.4 0 0 37 19% 27% 21% 5 6 1W  M 6 23 = L W L L W
Tariq McDaniel 3 1 0 2 - 0 - 0 0 0 - - - 1 1 1L  M 1 - L W L
Theo Thoudam 109 40 21 48 1.3 8 0.2 0 0 33 30% 22% 38% 3 4 2W  DM 17 - W L L W W
Tim Lowther 178 61 45 72 1.3 15 0.2 0 0 43 24% 20% 30% 4 7 -  DM 1 - W W W L D
Tom Bridger 311 117 69 125 1.4 35 0.3 0 0 46 15% 23% 27% 7 7 1W  M 2 - L W D L W
Tom Cecil 3 2 1 0 - 1 - 0 0 3 - - - 2 0 -  M - - W W D
Tom Colbourne 3 1 2 0 - 0 - 0 0 1 - - - 1 0 -  D 1 - W D D
Tom Colgan 290 118 58 114 1.4 158 1.6 11 0 54 19% 30% 28% 7 7 1W  AM 2 4 = (+1) W D D L W
Vinny Philips 139 64 27 48 1.6 112 2.2 7 0 34 24% 33% 13% 7 4 2W  A 7 4 = (+2) L W L W W
Wojciech Podjaski 3 1 1 1 - 0 - 0 0 0 - - - 1 1 -  GK 1 - L W D
Yury Vorobev 8 2 3 3 - 1 - 0 0 2 - - - 1 3 -  M - - L L L D D
  • Players: Active players are those who have played at least once in the prior 10 weeks.
  • Player: Click on one or more players to highlight and compare them. Click the column headers to sort.
  • PPG: Average points per game. 3 for a win, 1 for a draw. Shown where at least 10 matches have been played.
  • GS: Total goals scored by the player
  • AGS: Average goals scored by the player per week, since we started recording scorers. Shown where at least 10 matches have been played.
  • HT: Total personal hat-tricks scored
  • OG: Total personal own goals scored
  • CS: Clean Sheets
  • CS%: Percentage of the players' matches that end in a Clean Sheet. Shown where at least 10 matches have been played.
  • Ch%: Percentage of weeks the player's team won the Championship
  • WS%: Percentage of weeks the player's team claimed the Wooden Spoon
  • MCW: Maximum consecutive wins.
  • MCL: Maximum consecutive losses.
  • CWLS: Current Win Loss Streak.
  • Pos: Position, which is used by the algorithm to create evenly balanced teams (see below). Players are manually assigned a position based on their observed playing styles
    • GK: Goal Keeper
    • D: Defender
    • DM: Defensive Midfielder: Usually plays in midfield but will fill in defensively if the team is short of recognised defenders.
    • M: Midfielder
    • AM: Attacking Midfielder: Plays in midfield and has an average goals scored per game greater than 0.5
    • A: Attacker
  • Rank: Each player has a rating that is used to select fair teams. This is adjusted following each match, so that over time, the rating should become more accurate and the teams more equal. The rankings of the top 30 players are shown. Only players who have played at least 10 matches, and at least once in the past 10 weeks are ranked. The other stats, are more down to who's been selected in your team, and should even out over time but the ranking will reflect how well you're playing compared to the other players, and so hopefully adds some longer term interest.
  • History: The results of a players most recent 5 matches are shown. Hover over each to see the date and the score.
  • Team Selection Algorithm: AKA 'The Algo' - tries to choose fair teams based on who is present on the morning:
    • The sum of the ratings of each teams' players will match as closely as possible. Even when teams have different numbers of players, e.g. 9v8, the totals will match - the team of 8 will have, on average, slightly stronger players than the team of 9.
    • As well as the total for the team, it will also even out as far as possible the combined ratings of the following:
      • Goal Keepers
      • Defenders
      • Defenders + Defensive Midfielders
      • Attackers + Attacking Midfielders
      • Attackers
    • Players making their debut are spread as evenly as possible across all teams as their ratings are not well known.
    • Groups of two or more friends can be set up. On days when we have more than 2 teams The Algo will try and ensure that anyone in a group is playing in a team with at least one other player from their group. Feel free to ask me if you're in a group, or to set one up for you.
    • Players who are late will be divided across teams (so a team doesn't end up waiting for 2 players for example). As an incentive to arrive on time, The Algo will try not to put late players on a team which has a dedicated goal keeper and it may ignore their friend groupings.