A January Transfer Window Analysis
With the January transfer window fast approaching, Prozone analysis is being utilised to supplement the intuition of scouts and managers as clubs look to increase their due diligence and accountability with regard to player assets and player trading.
The recent release of 'Moneyball' – the cinematic account of the Oakland Athletics’ implementation of statistical methods in baseball recruitment in order to improve efficiency in terms of both finance and performance – has raised some important questions in a European football community not necessarily familiar with Billy Beane and his lauded use of sabermetrics.
Analyzing the impact that January transfer activity has had on league position within the Premier League over the last five years, there are several trends which come to light. While there is a general trend towards January recruitment having a negative influence on team performance, when we look at the statistics for clubs in the bottom four at the start of the window we see strong improvements in results, the average win percentage rising from 19% to 27% post-window. Interestingly, the teams which appear to gain the most from recruitment in the New Year are those who bring in between three and four players, a figure which suggests that, given the delicately balanced nature of many squads, there may be an optimum level of recruitment for the mid-season transfer window.
Looking at the data more closely, what becomes apparent is the correlation between effectiveness in recruitment and Premier League survival. Fulham, one of the teams in the bottom four at the end of January last season, used newly recruited players for a higher percentage (51%) of their remaining games than their bottom 4 counterparts and survived, whereas Birmingham City and West Ham United – both ultimately relegated – each gave a lesser percentage of match time to the January recruits.
Having gathered a wealth of data for the bottom four teams over the past five years, Prozone can begin to assess the potential impact of new recruits on team performance at a much greater level of detail. For example, when we look at the most significant attacking variables for those teams striving to maintain their position in the upper echelons of the game, we can see that the figures for shooting accuracy, the number of goals, total shots and shots inside the box all increase post-January. Similarly, defensive statistics such as the average numbers of tackles and possessions gained also rise, data which suggests a marked improvement in performance following the opportunity for recruitment which is presented by the transfer window.
While the varying levels of financial freedom between Premier League clubs determine just how expansive their respective recruitment policies can be, the data indicates that the business done in January has the most profound effect on those clubs struggling at the foot of the table. What this suggests is that reactionary short-term planning can have an instantly positive effect on performance, although that should not be seen as a guarantor of improved results over a sustained period of time.
What is able to be concluded is that, by optimising transfer strategies with tools such as Prozone RECRUITER, teams can identify an optimum level of business for themselves and then qualify the effect those new players have on the team’s performance over the remainder of the season. Empirical approaches to recruitment may not be as firmly ingrained in football as they are in the world of 'Moneyball', but statistical analysis is fast becoming a vital tool for clubs looking to enhance the due diligence process around player trading as they re-shape themselves for the future; applying to football the approach to recruitment enshrined in the 'Moneyball' philosophy with a similar level of effectiveness.
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