football predictions since 1979
ORGANISERS, PAST AND PRESENT MEMBERS,
PROFESSIONALS, HONOUR ROLL

{barTHE ORGANISERS bar} {iMike Phillips i} {iMark Grunwell i} {iNaz Rajan i} (Webmaster) {barFPA MEMBERS bar} Here is a brief summary of the predicting history for each of our current members. This will show any Major or Minor wins and career average (in percent) from the top flight Results League, i.e. not including performances in the former Results League Division One (to be completed). For an all-time average, members need to predict two seasons to be entered in the all-time averages list. Members may also like to submit a one or two line description, such as the team they support and their hopes/comments for FPA and the upcoming season. A photo would be good too. {iTITLES i} refers to the 10 past and present major league and cup titles. There are 5 current leagues: the JP Standard League (JPSL); the Results League (RL); the European Super League (ESL); the Members' Challenge League (MCL). There are 4 current cups: the Joyce Phillips League Cup (JPLC); the European Cup (EC); the F.A.Cup (FAC); the Dave Boston Group Trophy (DBGT). {iOther wins i} refers to all the other awards, from current tables, points and older leagues: the now defunct Amateur Results League (ARL) and there also used to be a Division One with two promoted to the Premier League each season, so there were minor awards for Division One Champion and promotion from Division One as runner up. There are also the Homes, Aways, Draws tables each season, and a host of other awards relating to league performance such as top score, for example. These records are still being updated. There is also a minor cup, the Charity Shield (CS). The following are being updated. Stats relate to the end of 2017/2018. {!memberbios} {bNotesb} All Time Average is naturally enough based on the number of completed seasons in the top flight (old Division One and current Premier League) Results League. You need two completed seasons to acquire an average. The problem with the all-time averages method is that for those who have only ever competed in the minimum number of seasons to qualify, they may have an artificially low or high career average. For example, the 1980s and the early 1990s produced a number of low scoring RL percentage seasons, even for the 'top' predictors, whereas in the 2000s there have been many higher scoring years. Take as an example, Ian Milligan who currently has a good career average based on 7 complete seasons from 2010-2011, with 48.91% - in fact, Ian is now number 6 on the all-time career averages of 55 predictors since 1980-1981, both amateur and pro, who have completed more than one season. Ian has missed many games in three of those seasons, whereas others who completed all the games in this period generally have lower averages (a season usually tends to be high percentages early on, tailing off near the end). The ruling now is that members have to have predicted to within 3 weeks' worth of the end of the season. This adjustment removes all those percentages from members who stopped predicting early in the season or missed too many weeks, giving them an artificially high score. So Ian's predictions for season 2012-2013, where he missed many games and only predicted 209 out of 275 total available games, has not been counted, and his career average is based on 6 out of 7 years. Though actually this favours Ian, as his score for that year was lower at 46.89%, which would bring his career average down. In the last two seasons, the FPA has been joined by a good predictor in Khalid Mowad. In those two seasons he has scored over 50% each year, giving him an average of over 50% and making him the top all-time average. But two years against another top predictor such as Mark Grunwell, who has predicted over 30 seasons, in both good and lean years, is not really a fair comparison. Compare Ian Millligan or Khalid Mowad to say Glen Grunwell, who has over 30 seasons of top flight finishes, and an all-time average of 47.49. For the same 7 year period as Ian, Glen's average is higher at 51.07, because all the low score years from the 1980s-1990s, a disadvantage to long standing member averages, have been removed. But it is certainly not an exact science. Here are all the all-time (formerly called career) averages for amateur and professional predictors who have completed more than one season in the top (Premier) Results League (some members may have spent some of their career time in the former Division One, based on Championship games). Bear in mind, the comments as above. {bAll Time Averages - percentages and number of completed seasons in brackets (to 2017-2018):b}
{b1b}Khalid Mowad{b52.50b}(2)
{b2b}Sami Almudaris{b50.73b}(2)
{b3b}Mark Grunwell{b49.664b}(32)
{b4b}Fiona Grunwell{b49.657b}(17)
{b5b}Sunday Express (Newspaper){b49.13b}(11)
{b6b}Ian Milligan{b48.91b}(7)
{b7b}Elliott Grunwell{b48.907b}(18)
{b8b}Matt Willing{b48.905b}(16)
{b9b}Mark Crossley{b48.72b}(3)
{b10b}Sunday Mail (Newspaper){b48.69b}(13)
11Mike Phillips48.53(32)
12Danny Thompson48.43(7)
13Rezilta (Online)48.14(3)
14Sunday Mirror (Newspaper)48.12(5)
15Barry Roberts-Jones47.90(11)
16Joseph Grunwell47.74(5)
17Glen Grunwell47.49(30)
18Daniel Grunwell47.43(12)
19Matthew Starling47.35(2)
20Joyce Phillips47.12(23)
21Predict Z (Online)47.06(3)
22Foot Stats (Online)46.94(4)
23Mark Lewis46.92(4)
24Will Hughes46.86(3)
25Daily Mail (Newspaper)46.66(11)
26The Sun (Newspaper)46.61(32)
27Tina Keen46.20(3)
28Fakhar Khalid45.84(5)
29Jason Blackford45.82(3)
30Sunday Times (Newspaper)45.60(16)
31Daily Express (Newspaper)45.47(5)
32Mark Oliver45.40(3)
33Sunday Telegraph (Newspaper)44.883(8)
34Dave Boston44.875(24)
35Daily Mirror (Newspaper)44.58(10)
36Dave Sancto43.952(5)
37Arron Springate43.945(6)
38Rob Slater43.36(3)
39Ted Phillips43.33(3)
40The Telegraph (Newspaper)43.30(7)
41Sunday People (Newspaper)43.06(9)
42Ken Morgan43.03(19)
43Richard Wellings42.68(6)
44News of the World (Newspaper)42.55(10)
45The Independent (Newspaper)42.33(4)
46The Times (Newspaper)42.30(5)
47Darren Sherman41.38(3)
48Darren Parker40.97(2)
49Paul Burch40.73(4)
50Denis Springate40.53(11)
51Ian Humphries40.27(4)
52Mike Sherman39.99(5)
53Evening Standard (Newspaper)39.12(4)
54Crossfire (TV)38.98(2)
55Oracle (TV)38.38(5)
Mike Sherman has the lowest all-time career average of the amateurs with 39.99% from 5 seasons, and the lowest all-time career average for a professional is The Oracle (a former TV teletext-style pundit) with 38.38% from 5 seasons - at 55th, The Oracle is the lowest of ALL amateurs and professionals obtaining a career average (two complete seasons). To improve your all-time average, you obviously need to score a higher percentage in a current season than your overall average listed here. {b Updated for 2018-2019 b} A better way to look at overall predicting performance is to attempt to standardise finishing year percentages (or 'normalise' in scientific terms) and there's more than one way to do this. The first way to do a more realistic comparison is to take everyone's results percentage for the last number of consecutive years when new members joined. For example, we had new members join FPA in the 2016-2017 season, but they have obviously only completed two seasons so will only have an average based on just two years. So we go back two seasons for the last influx of new members, since two seasons is the minumum we can average for. If no new members joined in the future seasons, we'd compare averages going back the number of seasons that we can compare. Example: let's say the last new FPA members joined five years ago; we could then run a five year average comparing everybody's last five seasons of averages. Currently two is the furthest we can go back. As mentioned, the last five to six years have seen exceptionally high percentages compared to those low scoring seasons of the 1980s and 1990s, so this levels the playing field for those who have lower all-time averages as a result of being part of those lower score years. The table is smaller since it can only show those who have predicted the last two seasons, but it now looks quite different: {bCurrent Two Year Average (to 2017-2018):b}
{b1b}Mark Grunwell{b55.40b}
{b2b}Mike Phillips{b53.79b}
{b3b}Glen Grunwell{b53.47b}
{b4b}The Sun (Newspaper){b53.27b}
{b5b}Fiona Grunwell{b52.84b}
{b6b}Khalid Mowad{b52.50b}
{b7b}Ian Milligan{b51.81b}
{b8b}Elliott Grunwell{b51.21b}
{b8b}Will Hughes{b51.21b}
{b10b}Daniel Grunwell{b51.14b}
11Sami Almudaris50.73
12Mark Crossley50.71
13Rezilta (Online)49.84
14Matt Willing49.60
15Foot Stats (Online)49.28
16Fakhar Khalid49.24
17Danny Thompson48.88
18Predict Z (Online)48.31
19Matthew Starling47.35
20Ken Morgan47.03
Now all the long standing members are more accurately compared to those who have predicted only the last two higher scoring years. Khalid Mowad and Sami Almudaris are now placed sixth and eleventh respectively. The second method is to say that anyone only predicting the last two seasons now have their two all-time high scores (including their personal best). So let's take the two best high scores for each member from all their FPA complete seasons, and compare those with the those who have only completed two years. Note that some former member members will show in this table, if they predicted a minimum two seasons: {bBest Two Years Average (to 2017-2018):b}
{b1b}Mark Grunwell{b57.98b}
{b2b}Mike Phillips{b57.25b}
{b3b}Elliott Grunwell{b56.23b}
{b4b}Joyce Phillips{b55.40b}
{b5b}Glen Grunwell{b55.21b}
{b6b}The Sun (Newspaper){b54.81b}
{b7b}Fiona Grunwell{b54.63b}
{b8b}Sunday Mail (Newspaper){b54.29b}
{b9b}Matt Willing{b54.05b}
{b10b}Sunday Express (Newspaper){b52.78b}
11Ian Milligan52.64
12Khalid Mowad52.50
13Danny Thompson52.32
14Sunday Times (Newspaper)52.28
15Will Hughes51.21
16Daniel Grunwell51.14
17Joseph Grunwell50.96
17Sunday Mirror (Newspaper)50.96
19Sami Almudaris50.73
20Dave Boston50.72
21Mark Crossley50.71
22Daily Mail (Newspaper)50.69
23Barry Roberts-Jones50.66
24Ken Morgan50.34
25Rezilta (Online)49.84
26Foot Stats (Online)49.28
27Fakhar Khalid49.24
28Dave Sancto48.52
29Predict Z (Online)48.31
30Daily Express (Newspaper)48.30
31Sunday Telegraph (Newspaper)47.70
32Daily Mirror (Newspaper)47.56
33Tina Keen47.42
34Matthew Starling47.35
35Arron Springate47.03
36The Telegraph (Newspaper)47.00
37News of the World (Newspaper)46.60
38Jason Blackford46.50
39Ted Phillips46.33
40Sunday People (Newspaper)46.31
41Mark Oliver46.14
42The Times (Newspaper)45.59
43Richard Wellings44.32
44The Independent (Newspaper)43.90
45Dennis Springate43.16
46Mike Sherman42.90
47Ian Humphries42.41
48Vic Hatherley42.29
49Darren Sherman42.17
50Paul Burch41.79
51Oracle (TV)41.77
52Darren Parker40.97
53Evening Standard (Newspaper)40.70
53Crossfire (TV)39.98
A familiar pattern begins to emerge with many of the same names appearing in the top 10 of the last two tables which more accurately reflects overall performance, rather than merely two good seasons of predicting. Of course, over time, given enough seasons for the newer members, their averages should equalise, since not every season will be a high scoring (say 50% plus) one. These latter tables also give a chance for former members with a good predictions history (title winners or regular high placings) such as Joyce Phillips, Barry Roberts-Jones and so on, to be better represented. Finally, as mentioned above, recent seasons, certainly since the 2000s, have been 'easier' to achieve a higher season's score, evidenced by all the 50%+ years. This puts good predictors no longer with us (either left the FPA or passed away) at a disadvantage as they can obviously never improve their average; likewise, current members who predicted through many 'lean' seasons of the 1980s and 1990s need a better way to be compared with more recent members to the FPA who have had two or more good years. {barTHE PROFESSIONALS bar} Professional entrants have a long history in the FPA, with the first entrant being The Sun (at that time represented by tipster Peter Campling) in the early years, and since then between four and ten professionals every season. The professionals have won the Standard League once (The Sun) and the Results League five times over all the years: The Sun three times; Sunday Express and Sunday Mirror once each. So this means that the 'amateur' members usually beat them - and unlike the professionals, we don't get paid for it. I have written to selected professionals occasionally, informing them of this fact and had some interesting replies (which will be added here in time). I also congratulated The Sun's Gerry Skinner for his win in 1996 and had a nice reply which will also appear here (on the Records page). In recent years we also included have Mark 'Lawro' Lawrenson, from the BBC, in our competitions, as well as some online predictors. Note that we dropped The Sun from the JPSL for 2012-2013. In 2011-2012 we reintroduced The Sun to the JPSL, since it is the only newspaper we know of that forecasts the exact scores, not just Pools 1-2-X. However since there are so many fewer games for the Pools (and therefore Results League) than for the JPSL, The Sun missed many games from the JPSL in the 2011-2012 season. The Sun therefore had no real chance of winning this league so will remain as a 1-2-X Predictor in the Results League with the other newspapers. It looks as if the Sun's famous 1994-1995 title year win will therefore never be repeated, with the newspaper tipsters only ever being in the Results League. In recent seasons, The Sun also suffered from the fact we started to predict all Saturday and Sunday games for the Results League, the same number as the Standard League, instead of following the traditional British Pools system, where a game or two is often not forecast by the Pros. This also put the other newspaper Pros at a disadvantage and we dropped them, in favour of some online predictors. At one time we even considered dropping The Sun, but as our best all-time Pro, and for historic reasons, we kept it. This all changed in 2018-2019 where we reverted to the 'traditional' Results League, predicting only the games the professionals do (specifically, the newspaper predictors), which follows the English Pools system. This give the chance back to The Sun and other professionals to win the Results League again from an equal number of games. The Professional Biographies and Statistics: {o} Newspaper professionals have their total seasons marked with an asterisk*, since more than one staff member/tipster has represented that newspaper over the years. {o} Mark Lawrenson's career average is marked by two asterisks** since his statistics are only relevant to the Lawro Results League which has less games than the Results League, so a direct comparison can only be made with other member averages from the same league i.e. LRL .The LRL member results percentages show a higher performance than for RL, as predicting Premier League with Gillingham FC is harder than predicting Premier alone! This is interesting though as it shows that all our career averages would probably be higher if we didn't predict Gillingham FC games. {!memberbiosp} {barFPA HONOUR ROLL : Members Remembered bar} {!memberbiosh} {barPredictions Theory bar} We have come a long way since the FPA started in 1979, and since then many other amateur and professional forecasters have joined the fold. Much has changed since those early days and we have learnt a lot. When we examine our FPA records, the same people (amateur members and professionals) seem to win, or get the highest averages, or usually finish near the top. Why? Over the years people have developed methods and strategies to come up with their predictions and to work out what they think teams will do. Not only in this organisation, but if your search online under football predictions you will find a large number of predictions sites, all offering the chance to predict and some of them offering theories on how to win at predicting, in the football pools or at the bookmakers. Naturally some of those, and our systems, work better than others, and what works for one person may not always work again or in the same way. Here we look at a few theories of predicting. {bThe Result or the Score?b} Should you focus on the result - home, away, draw - or the score? Does it matter? Obviously they are linked. In the FPA we have one main league based on pure results (the Results League) and one main one based on exact scores (the JP Standard League). Some feel it is best to focus on the result, work out whether it will be home, away, draw then worry about the exact score afterwards. Others feel that if you focus on the score, the results will take care of themselves. If we have a season with many goals per game then it may be hard to predict too many draws since we do not get many 3-3s or even 2-2s. On the other hand, a low scoring season will tend towards 0-0 draws and 1-0, 0-1 scores for homes and aways, respectively. {bPacker Theory, or {iThe Packer Lawi}b} It was Bill Packer way back in the 1980-1981 season who said if you put a row of 2s for the home team and a row of 1s for the away team, you can always get some points, and he became the first proponent of homes wins with a 2-1 score. Others followed suit and have had much success with it over the years, Mark Grunwell most notably amongst them. However over many years there have been seasons with 1-0 or 2-0 dominating and in other seasons, many goals flying in and 3-2 and 4-3 being almost common. To stop anyone putting all the same score every week, and to avoid an endless set of predictions of say ten 2-1s, 2-0s or the same draw or away score, we introduced the 75% rule that says you can only use the same score for 75% of your predictions. That keeps it interesting and different, and the Premier League does seem to produce many more high scoring games these days: probably due to the difference between the mega-stars of the Manchester and London clubs (Arsenal and Chelsea) coming up against strugglers. At any rate there is no pattern to what scores will pop up each week. Some years ago I used to bet on exact scores at the bookmakers and had some success, but you do not get good odds for predicting any game with fewer than four goals in it! {bReverse Packer Lawb} There is an argument that there are times when a team finds it a disadvantage to win at home and they are doing better away, for an extended period. This Reverse Packer Law then favours aways and a mirror score to Packer theory would be 1-2. This has certainly happened in recent years with some Premier teams having a stronger away record than their home form. Also Gillingham FC were for a couple of seasons very poor away and had the worst away record in all the four main leagues. Then suddenly they had a season where they hardly lost away but struggled at home. However to have a bit of an insight into whether the Reverse Packer Law is taking place, a bit of knowledge of team form is required. {bRajan Theoryb} This is only called a theory and not a law, as this was an experiment tried by our Webmaster Naz Rajan in 1980-1981, the first of his two seasons. Naz argued that since most people that year were favouring homes (Packer Theory), he would try putting mostly 1-1 draws (back then there was no 75% rule so this was possible). Unfortunately, apart from some basic information we have, most of the records for that first full season are lost now, but we know that Naz did not make the top four so it clearly was not a winning theory back then! {bTeam Formb} The most common sort of information on a team is form. The newspapers and internet tipsters always offer the last 5 games (sometimes 6) for every team, home and away. On the internet sites it is possible to adjust this to as many or as few recent games as desired. But how many recent games influence a team's performance? Is it more important to look at all a recent team's form or divide it into home and away? If they won their last 3 away games does it mean they have a good chance of winning the next away game? Bearing in mind a team usually plays at home every other week, an away win 3 games ago might be 6 weeks back, so how relevant is that game to now? {bLeague Tablesb} It is usually true that a higher team in the league may have a good chance of beating a lower one, and you may look at how many points above a team another team is. {bHistoric Formb} Another popular system is to consider historic form. For example, a team has not won away at a particular ground for say 25 years, or a team can't score more than a certain number of goals home or away or against a certain opponent. There may be some merit in this but it takes a lot of research. Many of the online previews of games usually provide some of these details. {bTeam Newsb} Are the players happy with their manager, team rotation, form - is their morale good? Are they missing their star striker, defender, goalie? If so that could influence a game. You look at the team news in the morning and may see that half of the team is out with the flu - could that influence your prediction? {bTeam Managerb} A team could be doing very well, or struggling, based on the manager and their relationship with the players. A team having to play just after their manager has been sacked could have a detrimental effect on moral. On the other hand, players may try extra hard to impress a new manager. And on that note, would players try harder if they knew their national manager, such as for England, was present at the game? {bStatistical Analysisb} Various predictions sites out there advocate studying the results statistically. This was tried in the FPA for a brief experiment in the 1990s, where a computer programme called 'Poolswinner' was purchased and entered into the former Division One. It did win the league but despite having all the results constantly updated, it always favoured homes over aways and draws (and we don't need statistics to tell us there are generally more homes), and hardly ever forecast a draw - so much for a 'pools winning' programme! No doubt there are other methods and algorithms where trends could be studied similar to those methods applied to the money markets. {bMethod Predictingb} Here you come up with a plan and stick to it. You feel for example there will always be about half homes, a quarter aways and a quarter draws, and that's what you put each week regardless. You have to work out which will be which of course, but once you have your 'banker' teams to win at home and away, filling in the undecided games as draws is then made easier. Like a Foreign Exchange trader, you don't change the method even when you have a week when your trade strategy is not working (i.e. there are 80% draws or aways in a weekend's games - it happens). This can work, but takes nerves of steel to stick with it week in, week out. {bEnd of Season Patternsb} Often the final league placings are not decided until the last few weeks or even the last week. Teams near the top are still playing for those sought after European places, whilst teams that have been doing badly near the foot of the table suddenly get a new lease of life and their form jumps as they fight to avoid the drop. {bCupsb} All of the above can apply, but there are always some givens. We know that in the (Capital One) League Cup and in the F.A. Cup the big teams of the Premier League will probably get to the latter stages, the non-leaguers going out first, followed by the lower division teams. However these cups are knock-out competitions and there are always some upsets, particularly in the League Cup in September where every year at least one Premier League team will slip up, and a manager may be saving the better players for an upcoming Premier or UEFA fixture. Likewise in the 3rd Round of the FA Cup, always early in January, where a major Premier team, used to good passing on a nice pitch, has to go to some windswept lower team ground in cold, wet conditions, can often be the victim of a giant-killing side. But which big team will it be to fall? 'The cup is great leveller!' {bThe Europe Effectb} A team on the road in Europe may have to play on a Wednesday or Thursday night then play a big Premier League game on the following Saturday, with players fatigued or injured from their European exploits. {bYour Own Performanceb} You may find you have more of a 'knack' for predicting homes, or aways, or draws. You could then predict more of those. How can you find out? Have a look at the Homes, Aways, Draws tables (based on the Results League) that follow the RL and LRL tables each week. {b'Gut Instinct'b} There are those who feel you should ignore all these details and just go with what your gut tells you, and the first score or result that jumps into the thoughts. For example, in 2001-2002, I was living abroad and did not have internet at home, did not see any English football on TV or in the papers, and only glanced at the Premier table once a week on a Friday night at work. If on a Saturday I would walk to work in the morning, have a quick look online at the games, and put down the first idea I had for the result and score. No form, no team news, no stats. That year I won the Standard League, so it goes to show you don't always need to be a football 'statto' to win. Go with what feels right! Mike Phillips {barComplete Members List bar} Here is a list of all members who have ever taken part in the FPA, past and present, full or part seasons, amateur and professional. {bBold textb} = Members participating in the current season (P) = Professionals (F) = Founder members from the first full season Note that The Sun is represented more than once, where we know the name of a Sun tipster for a particular year (we have historical records for some of the other newspaper tipsters too, to be added). 115 amateurs and professionals have now passed through the FPA competitions.
{-} Alderson, Tracey {-} {bAldhamen, Khalidb} {-} {bAlmudaris, Samib} {-} Arena, Hughie (F) {-} Babinet, Luke {-} Bailey, Daniel {-} Baker, Steve {-} Ballard, Martin {-} Bentley, Roy [Sun] (P) {-} {bBlackford, Jasonb} {-} Boston, Dave {i'DB'i} {-} Brinson, Paula {-} Burch, Paul {i'Burchy'i} {-} Burrluck, John (F) {-} Campling, Peter [Sun] (P) {-} Ceefax (P) {-} Clare, Paul {-} Clarke, Chris (F) {-} Cross, Mel {-} Crossfire (P) {-} {bCrossley, Markb} {-} Crowther, David {-} Daily Express (P) {-} Daily Mail (P) {-} Daily Mirror (P) {-} Dale, Bert (F) {-} Dawson, George (F) {-} Dolal, Dhowal {-} Dummott, Alan (F) {-} Enwright, Gordon (F) {-} Evans, Dave (F) {-} Evening Standard (P) {-} {bFootStats.comb} (P) {-} {bFoster, Alanb} {-} Free, Michelle {-} Frost, Clive {-} Golloghly, David {-} {bGrunwell, Danielb} {-} {bGrunwell, Elliottb} {-} {bGrunwell, Fionab} {-} {bGrunwell, Glenb} (F) {i'Eddie Endsleigh'i} {-} Grunwell, Joseph {-} {bGrunwell, Markb} (F) {i'The Emperor'i} {-} Grunwell, Tracey {-} Guardian (P) {-} Hannan, James {-} Hatherley, Vic {-} Horton, Brian (F) {-} {bHayas, Motebb} {-} {bHughes, Willb} {-} Humphries, Ian {-} Independent (P) {-} Jones, George {-} Keen, Malcolm {-} Keen, Tina {-} Kent Evening Post (P) {-} Kent Today (P) {-} Keohane, Nina {-} {bKhalid, Fakharb} {-} Knapp, Lewis {-} Lawrenson, Mark [BBC] (P) {-} {bLewis, Markb} {-} Lovelock, Helen {-} Lowrie, Jim {-} {bMilligan, Ianb} {-} Morgan, Ken {-} {bMowad, Khalidb} {-} Muggridge, Jamie (F) {i'Jeb'i} {-} News of the World (P) {-} Oliver, Mark {i'Ollie'i} {-} Oracle (P) {-} Packer, Bill (F) {-} Parker, Darren {-} Parker, Melanie {-} Phillips, Joyce (F) {i'Joycee'i} {-} {bPhillips, Mikeb} (F) {-} Phillips, Ted (F) {-} {bPredict Z.comb} (P) {-} Rajan, Naz (F) {-} Reid, Jeff (F) {-} Rezilta.com (P) {-} Sancto, Dave {-} Roberts-Jones, Barry {i'BRJ'i} {-} {bSalter, Robb} {-} Scott, S {-} Sherman, Darren {-} Sherman, Mike {-} Shrubsole, Brian (F) {-} Skinner, Gerry [Sun] (P) {-} Slater, Paul {-} Slater, Rob {-} Smith, Anthony {-} Springate, Arron {-} Springate, Dennis {-} Springate, Susan {-} {bStarling, Matthewb} {-} {bSunb} [overall] (P) {-} {bSunday Expressb} (P) {-} {bSunday Mailb} (P) {-} Sunday Mirror (P) {-} Sunday People (P) {-} Sunday Telegraph (P) {-} Sunday Times (P) {-} Taylor, Paul {-} Telegraph (P) {-} {bThompson, Dannyb} {-} Tidy, Mike (F) {-} Times (P) {-} Today (P) {-} Turnbull, John {-} Wallbank, Mark {-} Wallbank, Matt {-} Webb, Dave (F) {i'DJ Webb'i} {-} Wellings, Richard {-} Williams, Neil {-} Williams, Tony {-} {bWilling, Mattb} {-} Young, Dave (F) {-} Young, Johnny (F)
{line}{pfootballfire.jpgp}
Information on past and current members. This page is being updated for 2017-2018


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