Dirty James and the reading of football analytics
James Hanson is the league’s dirtiest player. If you do not appreciate that then you do not appreciate James Hanson.
Statistics leaked out that showed that Hanson had given away more free kicks than any other player in the Football League prompting Phil Parkinson to defend his player against the accusation saying James is the fairest jumper I’ve ever seen. He never jumps with his arms and catches anybody. He’s different class at that but he gets too many fouls against him.
Parkinson continued to say that he was unhappy with the level of protection that Hanson gets from double or triple marking he suffers but eventually sighs that the problem that City have is that the opposition do their homework on how the Bantams will play.
That Hanson gained this label of the league’s most fouling player should be no surprise to anyone who has watched him in his five seasons as a footballer. He commits more fouls in a game that Bruno Rodriguez did in his entire Bradford City career but I find I am not unhappy with that situation.
In fact I find that watching James Hanson jumping for absolutely everything is a more satisfying and inspiring afternoon than watching – for example – Andy Gray being outjumped with his two feet rooted to terra firma. The fact that Hanson wins more than most probably makes his approach more palatable too but there is something to raise the spirits in a player who very obviously throws himself into everything.
Yes James Hanson is dirty, but its the dirty on his shirt and knees from jumping and falling and the dirty under his fingernails from a hard afternoon of graft.
The fact that this statistic has surfaced continues football’s increasingly affection for the world of numbers. Manchester City pushed big data in football into the public arena with the MCFC Analytics project. There is a response to this movement which is summed up in the phrase People who reduce one of Zinedine Zidane’s famous pirouettes to a statistic about completed dribbles don’t deserve football.
The middle ground for this debate is in Everton manager Roberto Martinez reading over reams of stats before concluding that footballers are footballers one day of the week and people six, and that much of the game is instict and not analysis.
The argument against statistics in football is a pointless one. Everything in football can be “reduced” to a dataset be it a jump from Noel Blake or a Cruyff turn but that is not a call towards reductionism and a statement that Zidane’s pirouettes were just “dribbles” just a statement on the nature of statistics as being a method of capturing a record of events.
It might be forever beyond the abilities of statisticians to create a metric on how two dribbles differ but many attributes of a player which were considered unmodellable have now been defined and proved useful.
Jordan Henderson’s move to Liverpool was driven by his “win back in the final third percentage” which made him worth capturing for a club invigorated by analytics convert John Henry. Pure instinct on the player said he had “funny gait”.
A football match generates a multitude of statistics (although it is only defined by two: goals scored for both sides) but what Henry and the Sabermetric devotees in Baseball that he rose out of and their footballing counterparts believe is that some of those, and some combinations of those, can give you insights. Baseball sabermetrics is the quest for the perfect compound statistic like a Holy Grail. Football statisticians are looking for the same.
It is incurious to say the least to present “most fouls” as “dirtiest” and one would love to contrast the fouls given away by Hanson to the headed challenges he wins, the ones he loses, and the goals that come from those challenges and the contrast those with other players in the division.
Similarly as Phil Parkinson is soon to ascend to the being the manager who has been in change of the 7th most Bradford City games – and as those managers are often judged on “win percentage” in isolation – it is worth considering at what other metrics could be added to get a more accurate reading of the value that those managers have brought to the club, or to any club.
Failing to enrich the understanding of statistics in football and how they have to be compounded will lead to the misuse of statistics like (I suspect) labelling James Hanson dirty because he gets involved in play a lot. The worst excess of this is watching Robbie Savage says statistics with increasing volume as if the validity of restating something out of context is dependent on volume.
As analytics begin to play more of a role in football – and they are doing – then supporters will need to get more used to the idea of not seeing a single stat as an end but rather as a part of a wider picture.