A STS scholar by trade, doing online ethnography of forums, focusing on the mutual shapings of scientific modeling and software, Alexandre Hocquet sees Football Manager as a reincarnation of his research topics in the world of soccer.
Football Manager (FM) is a videogame belonging to the sports management genre. When games media talks about football videogames, they more often than not mention FIFA, Pro Evolution Soccer (PES) and FM alongside one another (De la Porte, 2014; Wilson, 2015). They are–after all–the best sellers in their category, and at first sight, they seem to have much in common. Yet, although FIFA and PES are both sports video games and are actually competitors, they are confused or lumped together with FM, a game that not only belongs to another genre, but also to another culture.
Part of this distinction stems from gameplay differences, but also in terms of how the game design interacts with the real world. For FIFA, both gameplay and game design are related to the relationship between the game and football media coverage, or more precisely TV broadcasting. However, for FM, those interactions between the game and the real practice of football management lie in the world of “Big Data” — the quantification of football and its economics. FM and real world football matches have developed a reciprocal relationship due to the accuracy and thoroughness of the game’s quantitative modeling, where both mutually shape and impact the other moving forward.
Even though both are sports-related games, titles like FIFA do not have the same kind of reciprocal relationship with the sport off-screen. Football is depicted in FIFA more as the simulation of a television broadcast of a football match than an actual football match itself. Game elements like camera angles, close-ups, audio commentaries, pre and post match analyses, even goal replays make the gamer feel not like a football player, nor a coach, not even like a supporter, but like a television viewer (Stein, 2013). Such aesthetics were not so dominant in the nineties when numerous football video games were competing (Bogost, 2013). Some of those early football simulations were representing the field as a two-dimensional top view, something radically different from a match TV broadcast. It thus implied a radically different gameplay, where the emphasis was less on the individual player than on team playing, akin to a wargame.
FIFA’s gameplay also closely resembles the summarized highlights of a football match, where scoring opportunities are summed up in two or three minutes of video footage. The game design and match engine are focused on producing as many chances in three minutes of gameplay as possible, much more than is probable in a standard ninety minutes real-life match. Just like the aesthetics of TV broadcasts, goal celebrations take up a large part of these few minutes of gameplay, highlighting players celebrating more than actual football plays.
The way that television broadcasts a football match is akin to a heroic representation of football. The overrepresentation of players’ celebrations is consistent with the mainstream media presentation of football matches as a battle between heroic star players, to the detriment of presenting tactical teamplay, something that would demand more wide shots and fewer close ups. In FIFA, the well-known stars of professional football are essential to the gameplay, and their avatars provide a charismatic hero to identify oneself to (Conway, 2014). Within this logic, the actual simulation of football gameplay is largely dependent on individual characteristics of modeled football heroes more than collective teamplay, a feature that is largely overlooked (Sicart, 2013). This heroic flavour of FIFA vision of football is even more materialised in the latest release of the game series, wherein a “Journey” mode immerses the gamer into a Hollywoodian biopic movie of a rising football star. As Bogost puts it, sports videogames are more “variants” than simulations, arguing that game designers have to make a choice between spectacle and competition. Game immersion requires designers to accommodate both (Bogost, 2013).
The broadcasting influence on gaming is also becoming involved in a mutual shaping between videogame, real life, and TV. For example, the “dead fish” goal celebration performed by Jimmy Briand in front of television cameras has gained celebrity status because the celebration is reproduced from the game. Present-day football players belong to a generation that actually played FIFA and have been playing since a tender age when they were dreaming of becoming football players. This, in turn, influences their way of playing professional football. However, this kind of mutual shaping does not have the same impact or depth as the kind created by FM.
Juxtaposed with FIFA, FM’s gameplay is not based on a televisual football broadcast, although individual football matches are repetitive episodes within the long narration of a team manager’s career. The aim of FM is to simulate a lifelong career. Its ambition is similar to a mathematical system where football players are modelled and quantified and football matches scores are resolved by systems of equations involving the highest possible number of parameters, which makes the game highly demanding in terms of computational power. Even though similar quantifications exist in FIFA, they are not part of the core gaming experience. On the contrary, the FM gameplay resembles the work of a data analyst more than a tracksuit job. To build a successful football team, the gamer has to rely on number crunching, on statistical analysis; this looks more like the job of the data analyst in professional football than the coach’s job on the field (Stewart, 2015).
The representations of football players (and also the clubs, leagues, coaches, etc …) within the game are intended to be accurate quantitative representations of their real player counterparts. That is to say, the model seeks to be the best possible translation of every football player–their style of play, their physical, technical and mental traits–into numbers. This quantification of hundreds of thousands of real football players (some of whom are playing football in obscure championships with very low media access) is the core of the reliability of this database, which is constantly being updated. It is the bedrock of the game experience. FM is about quantitative modeling and the task of completing, tweaking, updating the database involves the whole gaming community (Hocquet, 2016). Football players in FM are not heroic avatars like in FIFA: they are the numerous, anonymous, tiny quantitative representations of an entire footballing world.
It is possible to play FIFA without being particularly interested in football. However, it is a void experiment to play FM without interest in the “beautiful game.” Being unaware of football mechanics, rules, administration or culture largely hinders a FM player’s immersion. To build a tactical setup, to successfully negotiate contracts, to interact with players or agents, all requires an understanding of what is football in real life. Crawford argues that playing FM can be part of a larger football fandom cultural identity. Football fandom is not always satisfied with media narratives like magazines or television, so playing games like FM allows a more thorough construction of fan identity. The FM gameplay thus allows a football fan to build narratives that are more relevant to their expertise and football culture than other media ever could (Crawford, 2006). A sport video game like FIFA achieves this only partially, because it lacks the integration of deep statistical football culture. FIFA‘s focus is on heroes and entertainment. FM‘s focus is on culture and modelisation.
The ambition of modelisation – turning football and football players into numbers – is not a neutral endeavour. It contains values and ideologies, as highlighted by Bagley and Summers in their study of an NCAA college American football game (Bagley and Summers, 2014). For example, relationships between managers and other characters in-game are modelled, but power relationships between managers and agents, or managers and committee chairs are underplayed in order to avoid hindering gameplay. Never in FM would a chairperson intervene directly in the team’s match roster, whereas such an event is commonplace in football. Additionally, FM’s view of football is a very anglocentric one. Many game aspects regarding infrastructure and employment are modeled from a British perspective, which limits its accuracy in other places of the world. For example, wages policies follow British-inspired regulations with no mechanics indicating the law-enforced monthly minimum wage rules that do exist in real life in other countries, like France. Another example is found in club infrastructures: in FM, the structures of youth academies worldwide are designed according to English youth academies standards (Hocquet, 2016). Recently, the Brexit referendum caused such a shock in Great Britain that the game designers strived to include hypothetical employment policies as regulated by Brexit future scenarios, causing turmoil in the gaming community and beyond (Baraniuk, 2016, Kamen, 2016, Khomani, 2016, Tweedale 2016) . Following Bogost, it is safe to say that real life football is multiple, and the FM football is very much a British football (Bogost, 2013).
Big Data Professional Football
In recent years, the success of FM’s database modelling has paralleled the commercial success of the series. Some real-life football players rose to worldwide fame in real life, years after FM predicted they would acquire stardom status (Nakrani, 2013). Obviously, there are also a lot of “future star wonderkids” in FM who eventually turn into anonymous limited players in actual football leagues or even reach the status of famous anti-heroes. Such players may have a feeble presence in the football world due to their modest career, but they can enjoy a huge popularity in the FM gaming community due to ingame fame based on having been dubbed a high-level prospect (Ames, 2015). But these striking examples of success (Lionel Messi is often cited; see Nakrani, 2013) are enough to give FM a credibility that goes beyond the gaming world and begins to be recognized in the real life football world. Within a few years, the quality of the database has acquired fame and a reputation for predicting for future talents in professional football (Parkin, 2015). Some players who blossom in the real world appear to have been notorious “wonderkids” in former versions of the game, even before they are modestly renowned in real life. This led to the game database to be seriously considered as a credible source of information in the football world. In the mid-2000s, it was suspected that football clubs did sign young players on the basis of the FM database. Nowadays, clubs admit it openly (Stuart, 2014).
Parallel to this, “Big Data” hype is spreading gradually in the football world (Sullivan, 2016). Corporations offering comprehensive metrics to evaluate players based on data collected during the matches are flourishing. A situation arises that Joly describes as a market based “techno scientific promise” regime (Joly, 2013): The transfers of football players in professional leagues are valued at tens of millions of euros, and the business of trading is based on an opaque rationality. Clubs’ scouting departments become more and more fond of number crunching in the hope of rationalizing player investments . Moreover, the flourishing industry of sports betting is increasingly paying attention to football metrics definitions to enhance its own calculated profits. There is an enormous global financial challenge at stake, in terms of relationships between football metrics and business models.
From Players to Metrics
It is in this context that the first real world successes of the FM database appear. FM metrics are inspired by football matches but also by their television broadcasts. The popularity of gaming metrics is such that they do influence in turn the definition of football metrics. The same football metrics that the companies which collect data in real matches define (and use) to create football data analyses for professional leagues and clubs (Stuart, 2014). This leads to a situation where the boundaries between football metrics and metrics of FM are blurred (Bleaney, 2014A). This is the second instance of mutual shaping involving the game: FM’s mathematical model is inspired by professional football data analysis, but this model also creates metrics which in turn influence the real world data analysis. Like the first mutual shaping focusing on players and their quantification, this second shaping regards metrics as the result of a reciprocal relationship between the football world and the gameworld. FM is involved in a mutual shaping, not with TV broadcast but with the world of Big data, which in turn impacts professional football.
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