Moneyfootball: The Importance of Data and Analytics for Agents


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Data in Football

The iconic Moneyball film (2003) was a major contributor to the ‘data revolution’ that has been seen in sports across the world in the 21st century. It popularized the idea of collecting, analysing and using data to gain an advantage over opponents. Lots of books have also been written about the importance of the data concept and the place that it has within sport.

Football has adopted data analysis. Clubs, managers, scouts, players, financial departments and physios all use statistics to increase efficiency and performance within the football environment. In recent years, significant sums of money have been invested into the data sector of football clubs who employ an ever-increasing team of analysts.

One of the many ways in which data can be used in football is in player recruitment, Clubs such as Brentford and Leicester have reputations for ‘smart-scouting’; identifying players who’s underlying stats and performances are of considerably higher value than their cost. This kind of recruitment allows clubs to increase transfer returns, buying top class players cheaply before they fulfil their potential and then selling them for large profits. One of the best examples of this is Leicester’s acquisition and selling of Riyad Mahrez. Using data in this way and for digital scouting means that clubs that may not have the budget of some of the biggest clubs can still compete at the highest level through smart, data-driven business.

Football can produce almost an infinite number of data sets. Both in training and in games, a player can be scrutinized based on the data they produce such as distance covered, expected goals, threat, interceptions and anything else one might want to analyse. Data is objective and measurable which is why it is such a useful tool in football.

Whilst it is possible to explore the vast array of data usage in football, in this blog I will focus upon the ways in which data can be used by agents within their field of work and the future of data usage in transfers and contract negotiations.

How Can Data be Utilised by Agents

            The value of data analytics is not lost on football agents. Agents going into negotiations with a football club over a player would automatically be disadvantaged if they didn’t have access to the data that clubs have. Clubs assess and use data to recruit players, so an agent needs the same data to keep up. In order to give themselves an edge in negotiations they must have a detailed understanding of data and what it means. Raw data is pointless but once it is interpreted and analysed it becomes actionable and helps agents make better decisions.

There are four main ways in which data can be used by agents:

  1. Agents can use data to help them in scouting and recruiting new clients. By analysing statistics they can identify players with the potential to be a success in the highest level of football. Lots of agents use digital data and analytics in their recruitment processes.When working with their clients, agents also use data to improve the standard of the service they provide. They use data analytics to help improve their client on and off the field from match performance to social media outreach.
  2. In transfers, agents must use data to present a persuasive case around the value of their client to prospective clubs.
  3. For brokering deals for clubs, agents use available data to find the right fit for the buying or selling club. Analytics help agents make decisions on players and targets as well as evaluating the best monetary solutions for transfer fees and wages.

            The number of data platforms available for football agents has grown substantially in the 21st century. Wyscout, Instat, SciSports, Statsbomb, Analytics FC and other well-known platforms all offer a range of services for agents to subscribe to. They use this data to gain insights into the underlying statistics of their clients and other players or even potential new clients. By comparing and contrasting statistics with other players, agents are able to determine the ‘worth’ of their player. They use this knowledge in negotiations to leverage their client and demonstrate to the club the value that they will add to the team. This means they are at an advantage in seeking higher salaries, bonuses and other fees.

Data is now considered essential in a transfer or contract negotiation. Agents should have a sufficient understanding and knowledge of data in order to improve the work they do for their clients. The statistics allow agents to see if the objective data matches their general feelings about a player and helps a club understand what they are paying for. If the data does not match, then the agent can use other statistics to solve the discrepancies and present a powerful negotiation to a club.

The Future of Data for Football Agents

            The data revolution in football is set to continue. Digital scouting is become a preferable option over physical scouting, especially since the COVID-19 pandemic and as the quality and range of statistics available continues to improve, the use of data analytics will also rise.

            It is expected that the ongoing development of data collection and interpretation will include algorithms and tools to predict the future success of players and clubs with increasing accuracy. These predictive models also turn data into practical guidance for future decisions. Agents can use this to their advantage to project their client’s influence upon a club and the contributions they are expected to make to the future success of the team. This provides agents with even more leverage in negotiations, transfers and for finding new clients with big potential. It should also bridge the gap between agents, analysts and coaches as the understanding of data usage widens across the industry.

            The future of data will hopefully allow agents to make better and more informed decisions on behalf of their players.

But what if the need for agents is removed by data analysts?

Manchester City’s Kevin De Bruyne’s recent contract negotiation was well publicized as he didn’t use an agent to secure his £83million, 4-year deal. Instead, he employed data analysts to present to the club to show how vital he was to the future success of the team and compare his worth with other superstars in the Premier League. They also used data to then predict KDB’s value which allowed him to negotiate such a lucrative deal.

Conclusion

            It is clear that data plays a now-essential role in football and is continuing to grow. The expansion of data usage and increase in available platforms and data sets will be significant in the future of football agents.

            Agents must learn to work with and understand the invaluable insights that data can give them into their client’s performances and worth to a club. Statistics will benefit the quality of work that agents do for their players and assist them in dealings with clubs.

2 Comments
  • The use of data and analytics seems to be one way that teams with lesser monetary resources can somewhat level the playing field with much wealthier clubs by finding undiscovered/unrecognized talented players and acquiring them at bargain prices (which better suits their budgets).

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