The Science + Football Conference: Day 1

Having never attended this conference before (this was its 3rd year) I didn’t quite know what to expect – that led me to think that the organisers could perhaps make an improvement to the way they advertise and describe what the event actually is! Fortunately the conference name ‘Science + Football’ gives a pretty clear indication of the theme of the 2 days.

The event was held at the Soccerdome in North Greenwich, London with 4 main zones: coaching area, boot room, interactive arena and presentation theatre. Although I tried to see a bit of everything, my interest was mainly in the performance analysis sessions/lectures which took place in the presentation theatre – and luckily for me that was inside rather than outside in the freezing cold! I was also a bit more selective in what I saw. But I am happy to say that the standard of presentations and speakers was of a very high standard – with, amongst many other great speakers, sports science gurus from Manchester United and Manchester City, nutritionists from Arsenal and Bolton, representatives from Prozone, Liverpool FC and even a panel session with former England manager Steve McClaren.

First up on day 1 was a minute’s silence in memory of influential performance director Nick Broad, followed by a coaching session with Tony Strudwick. Strudwick’s session, where he put some youth players through their paces, was incredibly different from his session at SALDN – indicating the contrast between the 2 conferences. The coaching sessions offered good insight into coaching/training tips (less relevant for me) and they are useful in showing how skills are being developed by particular drills. The analyst in me, and this would no doubt irritate the coaches massively, would want to know the relative benefit of each drill and how they are selected – I’m living in a bit of a dreamworld there!

Something that became apparent to me over the course of the conference is how much more of an emphasis there is on coaching 1st, fitness and injury prevention 2nd, then probably psychology and performance data analysis tied in 3rd place. There is still a palpable divide between traditional thinkers (in general driven by coaches) and the appliers of science who seek to optimise the traditional approach. A quote from Steve McClaren confirmed the scale of the divide for me during his opening speech in the Sunday panel session when he stated: “All I want from you science people is fitness and injury stats”. That is the most striking quote I lifted from his talk in which he said many other useful and interesting things about coaching in the modern game but it really does hammer home the reality of how far away Moneyball-type methods are from being integrated into coaching. I will discuss McClaren’s thoughts (or indeed my interpretation of them) in the second part of my review of the conference.

Companies like Opta and Prozone are straddling the gap between conventional wisdom and the analytical approach. They are certainly selling the concept of analytics for football, with varying success, but it is clear from the difference in language used by performance data analysts and, say, sports scientists with a focus on fitness, that the performance data analysts need to heavily soften their findings and vocabulary in order to sell analytical ideas to coaches and teams.

Sometimes the analysis itself is to blame and sometimes the delivery of it misses the mark. That is particularly troublesome for sport when an analyst can easily draw spurious conclusions that undermine his research even before he undertakes the difficult task of translating analysis into something useable by coaches. Jim Hicks, head of coach education at the PFA, gave an encouraging session discussing the use of Prozone data in the Premier League. He looked at:

  1. The location of shots that result in goals
  2. The optimal passing locations that result in assists
  3. The number of touches taken by goalscorers

For me, the conclusions of this analysis could have done with a little more reasoning. I understand that Jim Hicks was using the analysis in order to frame a youth coaching session (which I didn’t watch – so I might well have missed some extra depth) and in that sense the analysis is perhaps more effective if it is short, simple and to the point. But with regards to the position of shots that result in goals it uncovered nothing new to what players and coaches should already know – that more goals are scored in central areas close to the goal than wide areas or outside the box. We can probably take some value in teaching players who consistently shoot from long range or poor angles to stop doing it so frequently. Perhaps that is a small step forward, but do we need stats to tell us? The next revelation was that the best zones for creating an assist are again central but this time just outside the area. Not exactly rocket science, I can imagine that it would be quite patronising for a coach to be told by an analyst to get their players to have more possession in and around the penalty area – particularly in central positions – they will score more goals! The third point was more interesting: the highest proportion of goals scored in the Premier League are those where the scorer has only taken one touch. Even this is heavily influenced by tap-ins but I would suggest that superior technical ability will still enable certain strikers to score more if they are able to make a higher proportion of 1 or 2 touch goals – assuming the volume of goals under pressure is high enough.

Nevertheless, the questions asked of data and indeed the analysis itself has to go much further to be significant. How do we develop strategies to get players into the right positions on the field (with the ball) so that they penetrate the danger zones? Simply encouraging players to get on the ball near the penalty spot in order to score more goals is based on a brief observation of where goals are scored from, with not enough attention paid to the phases of play that most often lead to this kind of opportunity.

Garry Gelade, who has colloaborated with Chelsea and more recently PSG in player recruitment analysis, proved that in some cases there is indeed more than meets the eye in terms of analytics at top level clubs. His presentation discussed a valuation of goals scored across the top European leagues. For his research, he cross-referenced a high volume of matches in the top leagues plus games between them at Champions League and Europa League level to infer rankings (a bit like the UEFA coefficient) for defence and attacking ability. From this he was able to make a judgement on the average level of defensive and offensive strength in each league and also how many goals a striker could be expected to score in the Premier League (on average) if they have scored say 15 in a season in the Eredivisie. That kind of a question, although subject to the same old criticism of the use a mean value where the variation in individual cases can be large, still serves as a great example of the use of analytics to hone player recruitment strategy. It also gives a nod and a wink to the kind of research that does happen at top football clubs – despite the veils of secrecy in place. How much it is applied is another question, however as outside observers we can all recognise the probable application of a player recruitment strategy at Newcastle United today – where they are clearly uncovering value in Ligue 1 in particular. There is little question in my mind that this is the result of an analysis-informed approach.

Rasmus Ankersen, apart from trying to sell his book (The Gold Mine Effect, sounds quite interesting actually!) told us about the pitfalls of talent identification and scouting. His prime example was Simon Kjaer, who even at 15 years old was not recognised for his talent and high potential by any of his coaches at the time (including Ankersen himself). Ankersen discussed many hidden factors that can be missed when we look purely at qualifications or conventional wisdom in evaluating talent. He used many examples, including one from Jamaican national team sprint coach Stephen Francis who identified 2 sprinters, 1 who runs 100m in 10.2secs and another who can run 10.6secs. Which sprinter would you prefer to train? Of course, it should depend on the circumstances in getting those times: if the 10.2s runner trains in world class facilities to strict regimes then perhaps his potential is much lower than a 10.6s runner who has developed his own style with indisciplined training. Francis would likely select the 10.6s runner who is slower on paper but has the potential – the runner in this anecdote being former world record holder Asafa Powell. The main theme of Ankersen’s work looks at the environmental, geographical and unique factors that breed success in particular ‘gold mines’ throughout the world, like the Jamaican sprint team and Ethiopian long distance sprinters, many of whom come from the same small town of Bekoji. I guess I’ll have to buy the book to find out if Ankersen offers further guidance on how to spot these hidden talents!

All in all it was a very enlightening day 1 of the conference with both encouragement and discouragement for the use of analytics in sport in equal measure. Obviously I am a little behind in posting this considering the conference came and went at the weekend – but for all those interested I expect to have another review for day 2 written up in the next couple of days.


4 thoughts on “The Science + Football Conference: Day 1

  1. differentgame

    Hi chris

    Interesting comments on the shot position stuff. One main theory from moneyball ( yes yawn!) was ‘you don’t teach guys’. In the main they are what they are. Putting a number on it, can give good indication in player recruitment – buy the ones who don’t shoot from anywhere – and there are loads that do. Apart from the obv ones like taraabt, Suarez etc its difficult to tell by eye who does what. If a player makes same patterns over time and even across diff teams its a good indicator

    The shots stuff deconstructed has also led to me questioning goalkeeping techniques from range. If there’s something in it, it could lead to new ways of coaching. Are clubs looking at these things deeply enough or just going game to game. I don’t believe you can optimally analyse games until you know how difficult an action is, and you only know that by putting a number on it

    The assists position stuff is interesting too as I have just started to count these up!

    From the outside it seems that the clubs don’t dig deeply enough to integrate the info. The players on the field are still shooting nearly half the time from distance and winging cross after cross in at packed defences from v wide areas

    1. thepowerofeleven Post author

      Thank you for your notes – you definitely make a compelling argument for its use. I suppose my criticism/discussion of shots positioning is more to do with the relative benefit of shooting vs alternatives that an attacker has, which is harder to quantify. For example, let’s say that a player scores on average 10% (1 in 10) of his long range shots – already fairly unlikely but bear with me. If the build-up play from that position onwards has a lower average result in goals scored (i.e. the alternative passing/dribbling options result in a goal only 1 in 13 times) then perhaps we would prefer that player to shoot from range because the scoring potential is still more likely than the alternative! My point is not that this theory is necessarily right, but I would still push for more evidence and analysis to give the best answer possible.

  2. differentgame

    i agree. The type of football analysis we bloggers (and hopefully clubs in the future) should be championing should be eventually to be able to measure the pay off between pursuing x as opposed to y at point z in a game. i’m still trying to measure x and will increasingly be trying to introduce z in future with SPAM. it can be done to a decent extent if you put the work in, even without more detailed opta feeds that bloggers crave.
    Without numbers, professionals are just guessing, and with their experience they’re probably 75% right. But decent analysis hopefully improves this % for decision making in games and recruitment, and future coaching set up. Well, it sounds good in theory doesnt it?!

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