Monthly Archives: September 2012

Premier League 2011-12: Position Analysis SM/WA

Wide midfielders/attackers. This time reviewing the Opta data for those players who started a match on either side of a ‘flat’ midfield 4 or 5 or an advanced 3. As with my earlier post on CMs, I have to admit from the start that the roles these players have can differ widely from team to team – some teams who play a quartet in midfield see the need for defensive-oriented side midfielder(s), whilst in other cases a player may be given a ‘free’ role and won’t actually spend as much time on the flank. As a result, because my system firstly groups the players then looks at the strongest correlations between those player’s actions and winning, the more influential midfielders’ statistics give a sort of bias to the results that mean some midfielders with rarer abilities may not be noticed. This isn’t a defence of Gabriel Obertan, who as we will see later finished at the bottom of the rating, but rather a disclaimer that Obertan might be superb in some areas that:

a) are not covered by the statistical fields Opta have provided or

b) my analysis doesn’t pick them up because it focuses on attributes dominated by players at the top of the rating

Or perhaps Obertan just isn’t very good. Note b above is particularly interesting because at times during my position analysis reviews certain players have been surprising underperformers. I am always sensitive to the results of Newcastle, but it has been rather surprising that for a team which finished 5th in the league so far only 1 player has made the top 10 of any position rating so far (Yohan Cabaye, CM). Newcastle’s uncanny ability last season to score goals despite a low final third pass success rating – as highlighted by Ravi Ramineni’s post here, suggests that Alan Pardew’s team have a unique but effective style that may not be comparable to other teams in the EPL – or maybe Newcastle had an incredibly ‘lucky’ season, as suggested by Mark Taylor.

So, with that kind of disclaimer noted, back to the analysis. This time I introduced some new measures to try to avoid bias for certain players or certain teams since goals, chances created and pass success in opponent’s half were all very significant contributors to performance here – but frankly comparing those statistics directly between a Wolves player and a Man City player would unfairly bias the City player. The measures used are noted below:

Goals rating: goals per big chance per minute (rewarding clinicism, goals out of nothing and profligacy)
Chances created per min: key passes + assists per min
Pass success opp half: as a ratio of unsuccessful passes
Long pass success: as a ratio of unsuccessful long passes
Dribble success: as a ratio of unsuccessful dribbles
Lay-offs success: as a ratio of unsuccessful lay-offs
Through ball per touch
Touches per min
Ground duel ratio
Recoveries per min
Team bonus: 1-20 additional points based on the player’s team

I weighted these factors according to their relative effects on winning/producing goals/conceding goals – then added a bit of a lazy attempt to reward players who play for losing teams by adding a ‘team bonus’.

46 players played more than 1000mins having started in the position of wide midfield or attacker, notable absentees are numerous but include Sessegnon, Modric, Arshavin, Park, Milner, Drenthe, Walters, Adam Johnson, Ramires, Bellamy, Ben Arfa. Some of these players came agonisingly close to qualifiying but just didn’t quite make it:

And the winner is Juan Mata, leading a Spanish top 2 with Silva in second place. Manchester United have an impressive three players in the top 10: Young, Valencia and Nani, whilst QPR’s Adel Taarabt makes 6th place – very impressive considering that without the team bonus he’d still be in the top 10.

Mata leads his peers on chances created, and otherwise scores very well in the key offensive statistics. In dribble success, a quality that doesn’t seem to matter that much but is certainly fun to watch, Nani leads a group of only 8 players who made more successful dribbles than failures (2.3, head and shoulders above the rest). The rest of the group, in order of success, were Larsson, Mata, Pennant, Bennett, Dyer, Valencia and Silva (ranging from a ratio of 1.5 to 1.0).

Arsenal fans may be surprised to see such poor scores from Gervinho and Walcott (or maybe not!). Gervinho may be forgiven considering that it was his first season in England but Walcott’s position just ahead of Obertan is a disappointment despite the fact that he scored 8 and made 8 assists from games in which he started. It may well be that Arsenal’s attack tend to focus through the centre – and as such Gervinho and Walcott do not get on the ball as much (backed up by their relatively low touches per min stats). In any case, this season Wenger has significantly strengthened his attacking midfield with Podolski and Cazorla – whilst Walcott’s contract is due to expire at the end of the season. If Walcott cannot force himself into a central striker’s role at Arsenal then a move away from the club at the end of the season could even be mutually beneficial.

Lastly I have provided a view of the only 2 defensive measures I included to give a different picture of how useful this same group of players are defensively:

Gutierrez leaps up this table, highlighting his defensive contribution to Newcastle’s performances last season, whilst Pienaar, Young, Dyer and Nani make the top 10 in both tables – proving their admirable all-round capabilities. Jermaine Pennant is 2nd, strongly outperforming his Stoke counterpart Matthew Etherington.


Premier League 2011-12: Position Analysis DM

Having completed analysis on centre midfielders, I discovered that by grouping all central midfielders together the defensive midfielders were unfairly compared to their more offensive partners.

As a result, my previous standards/classifications needed adjustment to obtain a reasonable range of data with which I could review defensive midfielders. This is for 2 reasons: primarily, the playing time of players in the position of DM (as considered below) was insufficient – only Arsenal and Swansea had players who played in this position for more than 1000mins; secondly, I wanted to include additional data from the defensive midfielders that I had previously categorised in the CM analysis.

Whether or not a midfielder is defensive or not is arguable in some cases, and you may disagree with some of the names I have included here. But this is my analysis, so I added the CM statistics for the following 17 midfielders to the DM stats:

Alejandro Faurlin Karl Henry
Cheik Tioté Lee Cattermole
Craig Gardner Lucas Leiva
David Fox Mohamed Diamé
Fabrice Muamba Scott Parker
Gareth Barry Shaun Derry
Jack Colback Steven N’Zonzi
Jay Spearing Youssuf Mulumbu
John Obi Mikel

Nigel de Jong failed to make the 1000mins cut as he only played a combined total of 885mins in the DM or CM position (not including substitute apps). In total, 5 premier league teams did not have a player who qualified for this list: Aston Villa, Everton, Fulham, Man Utd and Stoke City. These teams generally seemed to fill the centre of the park with midfielders who do a bit of everything.

To redress the balance from the CM analysis, I focused on DM actions that correlated negatively with goals conceded first – then appraised the effect on W/D/L and goals for in order to come up with my shortlist of statistics. As a result defensive attributes dominate this particular review, with only ‘goals from open play’ (which are infrequent for DMs so do not have much significance) and ‘passes forward’ (as a proportion of all passes) the 2 offensive fields that contribute to the DM analysis. It could be argued that even these offensive stats are dependent on the quality of the attacking players ahead of the DM.

‘Touches’, ‘short pass success’ and ‘lay-offs’ are the neutral fields considered – since being comfortable in possession, or at least in distributing it to the next player (or to safety) is a important part of the DM’s game.

The full list of all fields shortlisted, including those used, is shown below:

And the results are here:

So, Lucas Leiva, who actually had the lowest playing time in this list (1135mins) is rated #1. Had he not sustained a serious injury in November 2011, it is likely that Liverpool’s fortunes in the league would have been significantly improved. He topped the charts for total tackles (with 59 tackles won he was also 6th in that list despite playing fewer games than anyone else), duel success ratio of 1.86 (Derry was second with a ratio of 1.50) and passes forward. There is a clear link between pass success and passes forward, for example Joe Allen and Leon Britten top the charts in pass success but are bottom of the table in passes forward – indicating that the difficulty of their passes was generally probably not that high – however Lucas has above average short passing success despite playing 42% of his passes forward.

Second in the list is Gareth Barry, meaning that in every position analysis I have written so far (5), Man City have managed a player in the top 2 every time. He is also the highest placed English player, ahead of the widely praised Scott Parker. They are, however, within 5pts of one another for every field except headed clearances and passes forward – in which Barry is much stronger than Parker.

Brendan Rodgers’ signing for Liverpool of Joe Allen is rather significant because if he can develop a strong partnership with Lucas this season (assuming Lucas can stay injury-free), on the basis of their form last season they would be a formidable pairing (both scored higher than Arsenal’s pairing of Arteta and Song).

Finally, as a Newcastle fan my hopes that Cheick Tioté would prove his class amongst his peers was a little disappointing. On the plus side, 2 Sunderland players were in the bottom 4! Rumours abound over the summer that Chelsea/Man Utd/Man City/Arsenal were interested in Tioté in a £20m+ deal do not really stand up to the stats. If he is sold, and I know that Mike Ashley likes a good deal, WBA’s Youssuf Mulumbu would appear to be a good contender as a cost effective replacement.

Premier League 2011-12: Position Analysis CM

Reviewing Opta statistics for goalkeepers, central defenders and full backs was easier in terms of how to classify each position because as I explained in my first post on formations, almost every team lined up with a back four last season (on only 21 occasions out of 760 did a team not start with a back four).

Now that we are looking at midfielders, although four ‘flat’ midfielders was also the most common line-up, in general there was a lot more variety. A defensive midfielder should not really be compared with a winger, so I have had to be more careful when it comes to classifying the position that a midfielder plays depending on his position in the team’s formation. As we will see later, by pigeon-holing players in this way the review may be flawed for some players who qualify for the CM category but in reality are more defensive than average.

For transparency, I have listed my classifications below:

As we can see from the above list of CMs, which is fragmented by the formations, it was more of a challenge to remove the players who did not play in this position from the initial correlation review – due to the less consistent position ids. I also removed players with fewer than 1000mins in the position of CM in order to maintain consistency with my previous reviews .

I found that offensive statistics for CMs dominate defensive statistics. For example, goals, assists, through balls and big chances were all slightly more important to picking up points than the most significant defensive fields such as headed clearances and ground duels. This seems to suggest that the all-action central midfielder is more important in attack than defence. As a result my rating has 5 offensive statistics which rate the 48 midfielders with points from 1-6 (worst to best), 1 neutral field (pass success rate, middle third), and 3 key defensive statistics each with a maximum of 6pts on offer for the best 8 midfielders in each category. Errors leading to goals and red cards were so infrequent that it seemed unfair to apportion too much significance to them to I simply deducted a point per occurance for each player.

The final table is below. Note the absence of any Swansea or Arsenal players from the list: this is because neither team set up with a formation including a CM as per my definition – both Rodgers and Wenger prefer to employ the 4-2-3-1 formation.

The winner is another Manchester City player: Yaya Touré. Touré was without doubt instrumental to City’s success last season and as we can see from the rating he was excellent in all the categories that matter in my chart. I am starting to wonder if there is an inherent bias in the data MCFC have made available to the public considering how many categories City are dominating! The reality however is that the best players in the best teams should generally stand out in this type of analysis. Arguably Touré’s best statistic is middle third passing success, in which he was 2nd best overall. On average he completed 17.1 passes in the middle third before one was misplaced which compares to an overall average of 7.5 (successful passes:unsuccessful passes). However the winner in that category was the influential Paul Scholes, who on average completed a colossal 23.3 passes before one was misplaced!

Notable players in the top 10 include Stiliyan Petrov (whose season was sadly cut short due to his diagnosis with leukaemia) and Wes Hoolahan, both of whom were key midfielders who played for bottom half teams. Petrov was strong in most fields, but had a particularly low rate of being dispossessed, whilst Hoolahan was very strong in offensive categories – with similar attacking qualities to Frank Lampard.

Steven N’Zonzi, who was the player from a relegated club with the highest position, rated =14th in the list despite being considered by many to be a defensive midfielder – a significant result considering the general lack of more defensive-oriented CMs in the top half of the list.

For the second post running a Newcastle player finished last – surely not?! Rated by many to be one of Newcastle’s outstanding players, Cheick Tioté’s qualities are clearly not suited to this system. As we might expect, Tioté’s offensive statistics were poor: he didn’t score, he made one assist and played one through ball all season. What is perhaps more surprising is his below average middle third passing success ratio (6.5), the fact that he lost more ground duels than he won (169 to 122) and he was dispossessed more times than any other CM (69 in total).

And another surprise in the form of Luka Modric, who might be assumed to perform well in this model but only rated 33rd. These players deserve better, and so at a later date I will look to ascertain the qualities that set them apart from the crowd.

Premier League 2011-12: Position Analysis CB

By now, some of the features of my analyses are starting to become consistent. As before, I have filtered out any players with fewer than 1000mins playing time in the position of centre back. This means any player with postion ids 5 or 6 (always centre back regardless of whether or not the team plays a back 3,4 or 5). Then I also added players who played position 4 in a defensive 3 or 5. The most notable absence from this list is Nemanja Vidic who only managed 502mins playing time last season.

Next I reviewed strong correlations between wins/draws/losses, goals for and goals conceded against this shortened list of players. I sorted the list by the strongest negative and positive correlations to try to ascertain the key contributing attributes of central defenders to winning games. As ever, several passing fields showed up (all of whom also have strong cross-correlations), so I have been selective in which passing fields I kept and which I removed in order to reduce the bias to teams that either pass much more than average or whose central defenders have more work to do. Any fields that I was able to use a success rate ratio (eg. tackles lost vs tackles won) I did, otherwise I generally used a rate per minute measure.

Much like my previous system for full backs, I split the players into sectors and gave them points (1-6, worst to best) depending on how good they were relative to their peers. Then I added/deducted bonus points. In a similar vein to the full backs analysis, the bonus points cover goals scored, assists, errors leading to goals, penalties conceded and red cards.

Compared to full backs, heading statistics are much more important for centre backs. Headed clearances and aerial duels both had relatively significant correlations to winning games – and not only defensively, but about 2/3 of the goals scored by central defenders (40 out of 62) came from headers. As a result I used both headed clearances and aerial duels in my model, even though they are probably closely correlated. Similarly, ground duels, tackle success and challenges lost may also all be closely linked, but I considered this such an important part of central defender’s role that I included all three – thereby artificially increasing the weighting to those fields.

The final scores are below for all 54 central defenders analysed by this system, with something of a surprise at the top!

Yes, according to my system, Clint Hill was the best centre back last season. Having spent the first part of the season in the Championship (on loan at Nottingham Forest) he came back into favour under Mark Hughes’ reign but still only just played more than 1000mins to qualify for this list (1080mins to be exact). Say what you want about Clint Hill, but he was certainly consistent across most areas, dominating clearances, aerial duels and tackles. Touches per minute and passing success were relative weak points to his game but in a struggling QPR team that is probably not much of a surprise – it seems as though when he did touch the ball, he cleared it! UBT, if you are wondering, stands for ‘unsuccessful ball touch’, another area in which Hill does well.

For those of you doubting my system due to its unconventional winner, the rest of the top 10 (or so) may comfort you, particularly as Kompany and Vermaelen are joint second on 42pts. Kompany didn’t clear the ball anywhere near as frequently as Hill, or indeed most other centre backs, but he excelled in every other area.

By including both clearances and headed clearances I have effectively doubled the contribution of 2 fields which are very closely linked and also related to the team in which the defender plays – this is food for thought if I revisit this rating system in the future, considering that both Kompany and Vermaelen were certainly disadvantaged by this.

For a Newcastle fan, it is sad to see Coloccini sitting rock bottom of the list, particularly as his performances won so much praise in leading Newcastle into 5th place last season. Mike Williamson, his partner for much of the season, was only a few places above in 49th position. Also, England’s centre back pairing at Euro 2012, John Terry and Joleon Lescott (14th and 25th respectively) underperformed several other English defenders – including Rio Ferdinand who was controversially left out of the squad.

Premier League 2011-12: Position Analysis FB

Full backs. This position is played by Opta’s classified position ids 2 & 3 in any formation which has a back four or five.

In much the same way as my goalkeeper analysis I began by looking at the fields with the strongest positive or negative correlations to wins (where a draw counts as half of a win), goals for and goals conceded. Passing success and number of touches on the ball play a large role here, which is unsurprising really as the best teams are generally better at keeping the ball – so a lot of the time full backs in strong teams will have more time on the ball to pick a pass, and will spend more time attacking in the opponent’s half. Some of the more significant correlations are listed below:

In order to reduce the bias to the best teams, I removed some of the passing statistics that might artificially add to a defender’s score, eg. successful passes, of which there are many categories, all correlated with team wins but I chose to include ‘all successful passes’ and ‘successful passes middle third’. For these categories I incorporated the ratio of successful passes to unsuccessful passes to further try and remove ‘big club bias’.

I also filtered out any players who played fewer than 1000mins in the full back position. As a result some notable names are missing from my FB analysis including Boyata, Ivanovic, Santos, Smalling and Kolarov. I was left with 50 players to try and determine the best full backs (or at least most consistent) in the league last season.

I am experimenting with a few different techniques as I analyse the different positions. This time I used the following fields, and I split the players into 5 groups of 10. The best group received 5pts, and the worst performing group 1pt.

  • Touches opposition box per min
  • Ratio successful passes to unsuccessful passes all
  • Ratio successful passes to unsuccessful passes middle third
  • Headed clearances per min
  • Ratio duels won/lost
  • Ratio tackles won/lost
  • Yellow cards per min
  • Challenge lost per min
  • Touches per min

To explain some of the stranger measures in my analysis, I have included yellow cards with an equal weight to everything else, not only because of its correlation to goals conceded but it also makes a certain amount of sense. Although in some instances I would agree that a yellow card is preferable to allowing an opposing attacker past in a potentially threatening situation, in general I would assume that frequent yellow cards show those defenders who are caught out more easily, and perhaps not able to adapt quickly in difficult situations.

Readers with a keen eye will have spotted the odd correlations between aerial duels lost in the above table, and no mention of it in my key factors. I hypothesize that this aerial duels lost gives a ‘false’ correlation. A defender that loses more aerial duels is probably not a favourable quality! Perhaps the correlation arises from losing opposition team’s propensity to play the long ball in desperation, which puts full backs under aerial threat. Either way I have taken the analyst’s prerogative here and chosen to focus on the wider ‘duels’ stat instead.

Then we have 4 further fields: goals, assists, errors leading to goals and red cards. None of these fields occur particularly often for any full back, so I gave any player with a goal or assist an extra point, and deducted points for errors leading to goals and red cards.

The final list, in order of rank, is shown below:

Player Total Pts Team
1 Micah Richards 41 Manchester City
2 Patrice Evra 40 Manchester United
3 Bacary Sagna 39 Arsenal
4 Kyle Walker 36 Tottenham Hotspur
5 Stephen Ward 36 Wolverhampton Wanderers
6 Russell Martin 36 Norwich City
7 John Arne Riise 36 Fulham
8 Phil Jones 35 Manchester United
9 José Enrique 35 Liverpool
10 Kieran Gibbs 35 Arsenal
11 Glen Johnson 34 Liverpool
12 Pablo Zabaleta 34 Manchester City
13 Benoit Assou-Ekotto 33 Tottenham Hotspur
14 John O’Shea 33 Sunderland
15 Gaël Clichy 32 Manchester City
16 José Bosingwa 32 Chelsea
17 Stephen Kelly 32 Fulham
18 Tony Hibbert 32 Everton
19 Angel Rangel 31 Swansea City
20 Liam Ridgewell 30 West Bromwich Albion
21 Leighton Baines 29 Everton
22 Martin Olsson 29 Blackburn Rovers
23 Nicky Shorey 28 West Bromwich Albion
24 Davide Santon 28 Newcastle United
25 Nedum Onuoha 28 Queens Park Rangers
26 Neil Taylor 27 Swansea City
27 Phillip Bardsley 27 Sunderland
28 Kyle Naughton 27 Norwich City
29 Paul Robinson 27 Bolton Wanderers
30 Emmerson Boyce 27 Wigan Athletic
31 Maynor Figueroa 26 Wigan Athletic
32 Steven Reid 26 West Bromwich Albion
33 Stephen Warnock 26 Aston Villa
34 Armand Traore 26 Queens Park Rangers
35 Ashley Cole 25 Chelsea
36 Kieran Richardson 25 Sunderland
37 Marc Tierney 24 Norwich City
38 Luke Young 24 Queens Park Rangers
39 Ronald Zubar 23 Wolverhampton Wanderers
40 Ryan Taylor 22 Newcastle United
41 Alan Hutton 22 Aston Villa
42 Grétar Steinsson 22 Bolton Wanderers
43 Taye Taiwo 22 Queens Park Rangers
44 Sam Ricketts 20 Bolton Wanderers
45 Danny Simpson 20 Newcastle United
46 Billy Jones 20 West Bromwich Albion
47 Richard Stearman 18 Wolverhampton Wanderers
48 Jason Lowe 18 Blackburn Rovers
49 Marc Wilson 16 Stoke City
50 Andy Wilkinson 12 Stoke City

So Micah Richards and Patrice Evra are my top full backs from last season. Micah Richards’ relative weaknesses in duels won and touches per min were well compensated by a high level of consistency elsewhere and a contribution of 6 bonus pts for a goal and 5 assists. This attacking threat bonus was only matched by Ashley Cole, Leighton Baines and Benoit Assou-Ekotto.

Interestingly, Wolves’ Stephen Ward and Norwich City’s Russell Martin make 5th and 6th place respectively. Ward was consistent in all categories, only falling into the bottom 40% for tackles won/lost. Martin made the top 20% for duels, challenges and yellow cards.

At the bottom of the pile sit 2 Stoke City players, which perhaps suggests a bias in my model which does not reward the tactics Stoke play to. Both players made the top group for headed clearances, but scored poorly in pretty much every other category.

Perhaps the biggest surprise is Ashley Cole’s rank of 35th. Arguably one of the best left-backs in the world, he scored poorly in headed clearances, duels, tackles won/lost, yellow cards and challenges lost.

**UPDATED: Full player table now below for those interested:

Premier League 2011-12: Position Analysis GK

I have decided to put team/manager based analysis on hold for the time being so that I can switch focus to a review of some of the key performance statistics for each major playing position that contributed to points in last season’s premier league.

Gavin Fleig has now released ‘tier one’ of the advanced data set, which will no doubt start to divide my attention, but I will stick to posts on the basic data for now.

The next few posts will group players by position, and I intend to review correlations of the key fields in the MCFCAnalytics/Opta excel data set to determine their relative contribution to picking up points. The most interesting findings I will share with you on the posts which follow.

Below is a table of correlations between goalkeepers vs team results. For the WDL correlation I scored wins as +1, draws as +0.5 and losses as 0, following the methodology popularised by Soccernomics.

Listed above are some of the key fields that I believe will be useful in appraising goalkeeper performance, at least in the 2011-12 season. However, clearly some of the fields need manipulation before we can look at keeper performance, for example ‘goals conceded inside box’ is always going to be worse for a keeper playing in a team which concedes more than average – but if we use the ratio of saves inside box to goals conceded inside the box we can review which goalkeepers save a higher proportion of shots.

Aside from goals conceded in/outside the box, I found errors, ground duels and short passes to be particularly important. I also found a curious (albeit small) correlation between GK long passes and goals conceded: it appears as though the more often a goalkeeper kicks long, the more likely his team are to lose – regardless of whether or not the kicks are successful or unsuccessful. It could be argued that this is largely dependent how how good a team’s defence is at making themselves available for the short pass and may not purely reflect on the keeper.  What is beyond doubt is that a significant part of the goalkeeper’s job is in possession/distribution of the ball.

Another surprising correlation is the frequency of GK punches to wins. I am still struggling to work out this one!

On to the rating. Firstly, I removed any keepers who had played fewer than 1000mins (approx 11 games), leaving 22 players. Then I gave points of 1-22 (1 worst, 22 best) for each key measure and weighted this by correlation to goals conceded. According to my ‘on-the-fly’ system, I can now reveal that Joe Hart was the best goalkeeper last season, closely followed by David de Gea and Michel Vorm. Paul Robinson sits rock bottom, scoring poorly in almost every field except for ground duels.

The biggest underperformer, based on team performance, was Arsenal’s Szczesny who finished 17th out of 22.

Premier League 2011-12: Game changers pt2

This post reviews sendings off in the 2011-12 season: which teams lost or profited most?

To breakdown the MCFC/Opta data this time I filtered out any sendings off which occurred with less than 10 minutes of the game to go. Why? We can learn more from games where the team with a numerical advantage has longer on the field, and therefore a better opportunity to capitalise on their opponent’s weakness. I am most interested to see if any particular managers/teams seem to be better or worse at coping when a game becomes 11 vs 10 or even 11 vs 9 as happened in the QPR v Chelsea game last season at Loftus Road.

Last season a player was sent off with more than 10mins remaining a total of 51 times. QPR were the worst culprits, with their players sent off a total of 7 times before the 81st minute.  Interestingly, all of these red cards occurred in 2012, Mark Hughes being in charge for 6 out of the 7 games. If Mark Hughes specifically promoted the tactic of being more aggressive in the tackle, it was certainly a costly tactic as QPR lost all but 1 game in which they had a player sent off* (*with more than 10mins to go). In fact, in the only game they won from this situation they were already in front against Spurs and the red card for Adel Taarabt occurred in the 78th minute – only just meeting the constraints of my rule. Delving further into the stats on points gained/lost/unchanged, based on the score at the time of the sending off to the final score, QPR lost 2 games in which they were in a winning position until a player was sent off (at home to Norwich and Wolves) and 2 further games lost from a position of drawing a game (Man Utd and Man City – the famous conclusion to the season). Hence we can say that QPR had a -8pts swing, no doubt impacted by the red cards in those games. As it was, QPR only just survived relegation, yet with 8 more points to their total they would have been equal with Sunderland and Stoke in 13th/14th place.

Compare QPR’s stats to Spurs, who were much more disciplined last season with only 1 red card before the 81st minute: Danny Rose vs Aston Villa. On this occasion Spurs were actually able to turn their losing position to a draw, thereby gaining a point. The only other team to seemingly benefit from having a player sent off was Blackburn (vs Fulham, home). Here, Steve Kean’s team actually won having been level with Fulham when Yakubu was sent off.

55% of the time the red card did not change the result, in 41% of the matches the team with the player sent off lost points and 4% of the time the team actually gained (the 2 aforementioned).

Perhaps Bolton can count themselves unlucky – they had players sent off* in 5 games but no team had a player sent off* against them. On the other hand, Fulham’s players did not get sent off once with more than 10mins to play, but they benefited on 4 occasions, taking 9pts but arguably dropping 1pt against Steve Kean’s Blackburn.

At the top of the table, Arsenal were involved in 4 games in which they had a player sent off and 4 games in which the opposition had a man sent off*. In the games they had a player sent off they took only 1pt, but with the opposition down to 10 men they managed 3 wins and a draw. Manchester United’s opposition had players sent off 6 times; in these games although the result was often in their favour already, Man Utd took 16pts (5 wins, 1 draw). Man City and Chelsea both took maximum points in games where opposition players were sent off (6 and 9pts respectively), and City had an excellent record in games they had players sent off: 6pts from 3 games.

Any attempt to make a serious claim on which team or manager is best or worst at dealing with situations of 10 vs 11 players is flawed due to the small sample size.  But why not throw some names into the hat anyway?! Adding together the points swing after a player was sent off for either side shows that Chelsea come out on top (+6pts) and QPR bottom (-8pts). These teams both had manager changes during the season but for Chelsea Andre Vilas-Boas was the dominant force in their positive statistic, whilst Mark Hughes was in charge for most of the games that contributed to QPR’s poor points swing result. A special mention is reserved for Martin Jol’s disciplined Fulham side, as discussed earlier, who acheived a points swing of +4 from 4 games.

Team # players sent off* (a) Points (a) Points swing (a) # opposition players sent off* (b) Points (b) Points swing (b) Points swing (a) + (b)
Chelsea 3** 3 0 3 9 6 6
Fulham 0 0 0 4 9 4 4
Liverpool 4 3 -1 3 6 4 3
West Bromwich Albion 1 0 0 1 3 3 3
Manchester United 1 0 0 6 16 2 2
Newcastle United 2 1 0 3 5 2 2
Swansea City 2 3 0 2 3 2 2
Everton 1 0 -1 1 3 2 1
Manchester City 3 6 -1 2 6 2 1
Sunderland 1 1 -1 2 6 2 1
Tottenham Hotspur 1 1 1 5 12 0 1
Wolverhampton Wanderers 4 1 -2 2 3 3 1
Blackburn Rovers 4 4 0 2 3 0 0
Norwich City 2 1 -3 3 9 3 0
Stoke City 2 0 -2 2 2 2 0
Wigan Athletic 3 1 -2 2 1 1 -1
Arsenal 4 1 -4 4 10 2 -2
Bolton Wanderers 5 0 -2 0 0 0 -2
Aston Villa 1 0 -3 2 4 0 -3
Queens Park Rangers 7 3 -8 2** 3 0 -8
*with more than 10mins of normal time remaining
**Chelsea had 2 players sent off against QPR at Loftus Rd

*Sent off refers to my definition of sendings off with more than 10mins of normal time remaining.

Premier League 2011-12: Game changers pt1

Having used the MCFC Analytics / Opta data for my previous post on team formations, I am continuing to collate and group it into team data sets to try and see if I can find any interesting trends or analyses that may help to highlight manager/team strengths and weaknesses.

This post reviews substitutions: the frequency they are used, average playing time and goals scored.

Team # substitutions Subs per game Sub mins Ave mins per sub Sub goals Goals per sub Winning goals by sub 0 subs?
Arsenal 109 2.87 1959 17.97 6 0.06 3
Aston Villa 94 2.47 1815 19.31 2 0.02 1
Blackburn Rovers 87 2.29 2151 24.72 3 0.03 0 1 vs MU (H)
Bolton Wanderers 104 2.74 2056 19.77 2 0.02 2
Chelsea 105 2.76 2299 21.90 7 0.07 2
Everton 111 2.92 2081 18.75 10 0.09 3
Fulham 85 2.24 1521 17.89 1 0.01 0 2 vs WBA, Bolton (H)
Liverpool 91 2.39 1720 18.90 4 0.04 1
Manchester City 110 2.89 1952 17.75 15 0.14 2
Manchester United 100 2.63 2194 21.94 7 0.07 0 1 vs Liverpool (H)
Newcastle United 112 2.95 2158 19.27 6 0.05 2
Norwich City 111 2.92 2350 21.17 9 0.08 2
Queens Park Rangers 92 2.42 1867 20.29 7 0.08 2 1 vs Swans (A)
Stoke City 107 2.82 2372 22.17 4 0.04 1
Sunderland 92 2.42 1824 19.83 4 0.04 1
Swansea City 94 2.47 1859 19.78 3 0.03 1
Tottenham Hotspur 94 2.47 1719 18.29 5 0.05 1
West Bromwich Albion 101 2.66 1733 17.16 6 0.06 0
Wigan Athletic 102 2.68 2080 20.39 5 0.05 1
Wolverhampton Wanderers 108 2.84 2278 21.09 3 0.03 1
Total 2009 2.64 39988 19.90 109 0.05 26 5

Of course, in a premier league game a manager can make 3 substitutions. Last season, the average subs used per game by each team was 2.64 i.e. on most occasions a manager uses his full allocation of substitiutes. The managers most likely to use all 3 subs were Alan Pardew (Newcastle, 2.95 subs per game), Paul Lambert and David Moyes (Norwich and Everton, both 2.92). Substitutions are clearly of partcular importance to these managers, whether for tactical reasons, to help combat fatigue, squad rotate or simply run down the clock towards the end of a game. In Alan Pardew’s case I suspect the latter tactic was possibly used more than most, since the average number of minutes a Newcastle substitute played was 19.3mins, below the league average of 19.9mins.

The managers least likely to use all 3 subs in a game were Martin Jol, Steve Kean and Kenny Dalglish (2.24 subs per game, 2.29 and 2.39 respectively). Martin Jol used his bench warmers less than average, and unfortunately for them they were given a paltry 17.9mins playing time per game. Although Steve Kean didn’t use his subs as often as most managers, when he did he made sure they got a decent runaround: his substitutes had easily the longest average playing time in the league of 24.7mins.

Only on 5 occasions last season did a team not make any substitutions (Fulham: 2, Blackburn, Man Utd, QPR: 1).

Those statistics on substitutes will probably only interest the most serious football nerds (like me), so how about some information on managers who brought on super-subs? Well, this paragraph belongs to Roberto Mancini. An amazing 15 substitutes for Man City scored after being brought on, well above the average of 5.45 substitute goals. Dzeko’s contribution to the mayhem on the last day of the season was probably his most important goal from a total of 4 he scored coming off the bench. Perhaps you would think that since Man City won the league the statistic of 15 goals from substitutes isn’t that impressive, however for Ferguson and Wenger who both made an almost identical number of substitutions, their subs only scored 7 and 6 goals respectively. Certainly the attacking firepower Man City had on the bench last season was a significant weapon, perhaps if Jol had Aguero/Balotelli/Dzeko/Tevez on his bench throughout the season he would have used his substitutes more! Nevertheless the 8 goal differential between City and Utd from substitutes also tallies with City’s superior end of season goal difference of +8 that handed the title to the sky blues.

When it comes to goals per substitution, Mancini is easily top with 0.14 goals per sub, whilst David Moyes follows with 0.09. Martin Jol comes out worst with 0.01 goals per sub (no wonder he didn’t want to use his subs too often).

Winning goals scored by substitutes are harder to come by (and therefore more difficult to apportion any meaningful insight). However, Mancini doesn’t fare quite so well here, with only 2 out of the 15 subs goals scored classified by Opta as a winning goal (Balotelli’s efforts at home against Everton and Spurs). Wenger and Moyes topped the charts with 3 winning goals per sub apiece – very memorably for Arsenal fans this included Thierry Henry’s late winner at Sunderland in February. Four managers failed to bring on a sub who scored the winner: Ferguson, Hodgson, Jol (surprise, surprise) and Kean.

Premier League Formations 2011-12: Two banks of four

First of all many thanks to Gavin Fleig and the teams at MCFC Analytics and Opta for making so much quality data available to the public.  I received the ‘basic’ form of the data at the start of the week and intend to write a few posts on my findings over the coming weeks, covering a range of areas.

My initial analysis using the data began by looking at team formations, where I found that the overwhelming favourite amongst EPL managers remains the 4-4-2 (accounting for 33% of team line-ups) followed by 4-4-1-1 (21.7%) and the 4-2-3-1 favoured by Arsene Wenger and Brendan Rodgers (16.4%). It certainly seems as though most EPL managers believe that two banks of four provide a superior foundation for success in the premier league, considering that 54.7% of the time last season a premier league team lined up with two banks of four. Only two teams did not use either 4-4-2 or 4-4-1-1 throughout the year: Arsenal and Chelsea.  Special mentions go to Sir Alex Ferguson, Martin Jol and Tony Pulis for fielding two banks of four in over 85% of their games. Indeed, Tony Pulis’ Stoke City used the pure 4-4-2 in 36 out of 38 games, experimenting wildly(!) with a 4-5-1 formation away at Arsenal and Liverpool (Lost 1-3, Drew 0-0 respectively).

Nevertheless, in terms of consistency in formation, Tony Pulis takes second place. Arsene Wenger appears to have such an unshaking belief in the 4-2-3-1 formation that he used it in every game, and undoubtedly this style of formation is important to Arsenal’s famed passing game and control of possession. Brendan Rodgers’s Swansea City, who also dominated possession statistics last season, lined up with the same formation 87% of the time.

Only 5 teams experimented with 3 or 5 players in defence: Blackburn Rovers, Liverpool, Norwich City, Swansea City and Wigan Athletic. Of these teams, only Wigan used any system with 3 or 5 at the back more than once, for the rest it was an experiment to be forgotten as none managed to win the games in which they used this new formation. Roberto Martinez’s decision to try 5-4-1 a total of 7 times from February 2011, despite using it earlier in the season at Old Trafford and losing 5-0, helped Wigan to gain revenge against Manchester United and also beat Arsenal and Newcastle. In a remarkable turnaround to their season, Martinez’s Wigan used 7 different formations in their last 14 games earning 27 points in the process – form which over the course of a season would yield somewhere in the region of 72pts, enough to finish 3rd in the league table.

It may be interesting as well to look at the average points per game for each formation, I have copied this below.  Unsurprisingly, the formations preferred by certain teams distort the analysis here. For example, the 4-2-3-1 preferred by Wenger, or the 4-4-1-1 preferred by Roberto Mancini lifts the average points per game for that formation. It would be folly to say without further analysis that had Wolves used the 4-2-3-1 throughout the season they would have had more success. It is also difficult to conclude anything from the the results from those formations used less than say 30 times.

Total times used Ave. Pts per game
4-1-2-1-2 6 1.67
4-2-3-1 125 1.50
4-4-1-1 165 1.47
5-4-1 9 1.44
4-4-2 251 1.40
3-4-2-1 3 1.33
4-3-3 72 1.22
4-5-1 94 1.19
4-1-4-1 26 1.15
3-4-3 3 1.00
5-3-2 6 0.83

My last note is an ode to Terry Venables. I am afraid El Tel that your beloved Christmas Tree formation, 4-3-2-1, was not used even once last season.

Welcome to my blog

I am a former financial performance analyst turned part-time sports analyst.  Although I’d be the first to admit that my instincts and passion for sport at times produce an overwhelming partisan bias, the more serious of my posts will centre upon logical and rational analysis.  It’s up to you to recognise the posts that are based on numbers vs those fantastical opinions that my own brain tells me to write.