Originally Written: December 2004
It is not often that a sports book becomes a national bestseller in the business book lists but Michael Lewis has achieved that unusual feat with Moneyball: The Art of Winning an Unfair Game (Norton, London, 2003). Moneyball has caused as much interest and controversy in American B-Schools as it has at the ballpark. Why? It tells the David-and-Goliath story of how a small-market team, the Oakland A’s, is taking on the New York Yankees and the other big-market baseball teams and winning, regularly getting to the post-season playoffs on a player budget only around a quarter of that of the Yankees. It’s about trying to do things differently to create a sustainable competitive advantage. Moneyball is a case study of successful corporate strategy, organisational learning and industry resistance to change, and set in the context of America’s traditional pastime. Little wonder that it has had such an appeal to B-Schools.
The central character in Moneyball is Billy Beane, the general manager of the Oakland A’s. Beane, a former major leaguer himself, is the leader-entrepreneur with the creative vision that the organisation can perform better by making much more extensive use of player performance statistics to assist decisions on player recruitment, team selection and tactics, and player remuneration. Beane tapped into sabermetrics, the statistical study of baseball, which had previously been ignored by the pro baseball industry as a rather esoteric pursuit of the sport’s anoraks. Beane was the first practitioner to recognise that sabermetrics could provide valuable industry knowledge. For example, he revolutionised his team’s approach to recruiting young players, moving away from a reliance on highly subjective qualitative assessments of high-school players to a greater emphasis on the hitting and pitching records of college students. Beane is also a wheeler-dealer, looking to bring in players undervalued by the market and sell them on when they are too valuable to retain.
Applying quantitative analysis to the national pastime on this side of the Atlantic is still in its infancy. My research over the last eight years or so has focused on trying to develop formal techniques for the valuation of sporting intangible assets. Initially I focused on the transfer valuation of football players. Statistical analysis showed that the transfer market is highly systematic despite public belief to the contrary. The average level of transfer fees has risen in line with industry revenues mainly driven by the growth in the value of football TV rights. The differences in transfer fees between individual players are systematically related to the player’s age and experience, his appearance rate, his goal-scoring record, international recognition, and the size and divisional status of the buying and selling clubs. The systematic nature of transfer fees is not really surprising. It only reflects the fact that clubs engage in benchmarking. When trying to value players clubs look at the recent transfer deals for similar players and use these as benchmarks. It is an anchor-and-adjustment process common in all types of asset markets.
The academic research on transfer fees led on to the development of a transfer value benchmarking system that has been employed within the football industry for a variety of purposes. A similar approach was applied to benchmarking player wages in the Scottish Premier League. Of course, any benchmarking system has to assume that the general level of valuations (i.e. the anchor) has been set appropriately by the market. But it is clear in the football industry that the competitive pursuit of sporting success has created a winner’s curse with player wages bid up beyond a financially sustainable level. So the question remains. Is it possible to devise a method for formally calculating the financial value of a football player? Can the Moneyball philosophy be imported into the beautiful game to use player performance statistics to formulate “intelligent” player contracts?
Research on the financial value of players goes back to the early 1970s with pioneering work by Gerald Scully in baseball. The advantage of baseball (and, for that matter, cricket) is that it is a simple bat-and-ball game in which the individual game contributions of players are easily identified and measured by pitching/bowling and hitting/batting statistics with insignificant player interdependency effects. Scully calculated the incremental contribution of each player to their team’s overall winning percentage and converted this into a financial value using estimates of the sensitivity of team revenues to the team’s sporting performance. Scully’s approach provides an important starting point for the application of standard discounted cash flow (DCF) techniques to derive a fundamental valuation of individual players.
The major difficulty of deriving fundamental valuations of football players is that complex “invasion” team games such as the various forms of football involve a much greater range of player actions with significant player interdependency effects. These identification, monitoring and attribution difficulties have only recently been resolved thanks to technological advances in computer image recognition that have allowed the commercial development of sophisticated player tracking systems for the various forms of football. In the FA Premier League player performance statistics are provided by ProZone, the market leader in providing player tracking information to clubs, and the Opta Index (part of Sportingstatz) that provides a selection of key player performance statistics and player ratings to the clubs and the media.
Evaluating the financial value of a player’s on-the-field contribution draws on both sports science and sports finance. Calculating an individual player’s incremental contribution to the team’s performance requires the development of a complex statistical model that links the myriad of player actions to goals scored and conceded, and game and tournament outcomes. This hierarchical structural model of player and team performance must then be embedded in a financial model of the club’s cash flows before standard DCF techniques can be applied. Of course, the science of player valuation is the relatively easy task. The much more difficult task is the art of developing a practical methodology that Premiership clubs can be persuaded to adopt alongside their existing sporting and financial decision-making tools. As Billy Beane found in baseball, it isn’t easy going against conventional industry wisdom but success on the field certainly facilitates the conversion of non-believers. And just as in major league baseball, competitive pressure is forcing the smaller clubs in the English Premiership to become more innovative in finding “David” strategies to take on the Goliaths in London, Manchester and Liverpool. Bolton Wanderers and Charlton Athletic are showing that it is possible to compete on a relatively tight budget. Sam Allardyce, the Bolton manager, makes extensive use of ProZone as a coaching aid, and employs a sports psychologist as part of his backroom staff of sports scientists. Moneyball and the art of applying science to achieve sporting success looks set to intrigue and provoke a whole new readership in Premiership bootrooms and British B-Schools.
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