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The success of Major League Baseball (MLB) team Oakland Athletics in 2003 sparked a league-wide data-driven recruitment arms race. Other sports have been slower to adopt data-driven recruitment strategies, but have finally begun to catch up in the last decade. As a result, more modern digital recruitment platforms are appearing, and their usage is becoming more widespread across sports and leagues outside of the MLB.
Athlete Recruitment is a fast-growing market, set for a 10% CAGR from 2023-2028. The growth is driven by 2 factors: ever-increasing player spending, and an increase in the use of analytics platforms for recruitment as major sports teams have begun to shift to taking a more data-driven recruitment strategy. It is this segment we shall focus our attention on.
The Oakland A’s 2002 league record of 20 consecutive victories was enabled by the leveraging of “Sabermetrics” – an analytical approach to find undervalued players performing highly on specific key metrics. This enabled the Oakland A’s to have a competitive edge whilst keeping within their restricted payroll budget. Since this success, MLB teams have been locked in an analytical arms race in order to compete.
This story was massively popularised by the book, and later the film, Moneyball, which detailed their success in the face of difficult odds with their restricted budget. The figure below illustrates just how well the Oakland A’s utilised such a limited budget compared with the league’s highest spenders.
More recently, the Tampa Bay Rays have experienced an historic play-off run, reaching the play-offs for five consecutive seasons (2019-2023). This run has been achieved whilst maintaining double the league’s average wins per $1m spent, with 1.2 vs 0.6 wins per $1m spent. This shrewd success has been partly attributed to their enormous analytical team, which consists of 39 employees.
It is not that the rest of the MLB does not employ large analytical teams; in 2022, leading teams had around 18 full time employees. Compare this with the average NFL team with just under 3 analytics staff in 2022, and the NBA’s average of just over 4 per team. Lagging further behind is the Premier League; in 2021 only Manchester City and Liverpool were touted as having even NBA-sized analytical teams.
Analytical team size does not wholly reflect the differences between sports in their willingness to take on a data-driven approach; as we will next detail, sports such as football have recently leaned into this transition through widespread adoption of external recruitment platforms.
Digital Recruitment Platforms
The use of Hudl’s Wyscout platform is pervasive amongst top football teams, and this isn’t just exclusive to the Premier League either – over 400 professional clubs use the video scouting platform. Wyscout provides access to footage and statistical reports from both professional and youth football, and its database contains over 400,000 players. This acts as a useful tool for coaches, scouts and performance analysts to identify players which fit their specific needs.
Sportradar’s Synergy Sports in the US is another prime example, being utilised by all 30 MLB teams, all 30 NBA teams, and nearly all NCAA D1 baseball teams. Synergy Sports provides a globally-reaching database of player profiles, video and statistical analysis, and even provides custom scouting reports – largely for the same purpose as Wyscout.
It is important to note that both Synergy Sports and Wyscout were acquired by large Sports Analytics players – Sportradar and Hudl.
Emerging Platforms
With the rapid developments in AI video analysis, platforms which provide automated insights into talent identification are emerging. These platforms provide more than a simple player profile database, and offer greater predictive power.
Ai.io, for example, automates the talent identification process, using AI to generate insights from mobile phone video footage – identifying metrics predictive of a player’s talent. This democratises the recruitment process, meaning that players only need access to a mobile phone to be discoverable – this in turn, expands the net cast by recruiters. So far, Ai.io have partnered with Chelsea, Burnley and Major League Soccer.
The Major Challenge
The overwhelming challenge which these newer platforms face is competing with established platforms on reputation, and their extensive club and player networks. Established platforms have had much of the last decade to acquire the buy-in of many clubs, and their reputation is further strengthened by the name of their parent company. The value in the player network sizes of established platforms is now well-recognised, and emerging players may need to offer similar coverage – or an explicitly different offering to compete.
It remains to be seen to what degree established platforms expand across sports and achieve lower league penetration, and whether they will be able to overcome the friction to uptake when dealing with clients of potentially lower budgets, for whom a change in recruitment practice holds greater risk.
It also remains to be seen whether more innovative platforms emerge, and what sort of success they’ll enjoy. There is risk that they struggle to gain a foothold against the now established digital platforms.
Lastly, it will be interesting to follow the path which emerging platforms take, will it be the same one which Wyscout and Synergy Sports have already taken?
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The success of Major League Baseball (MLB) team Oakland Athletics in 2003 sparked a league-wide data-driven recruitment arms race. Other sports have been slower to adopt data-driven recruitment strategies, but have finally begun to catch up in the last decade. As a result, more modern digital recruitment platforms are appearing, and their usage is becoming more widespread across sports and leagues outside of the MLB.
Athlete Recruitment is a fast-growing market, set for a 10% CAGR from 2023-2028. The growth is driven by 2 factors: ever-increasing player spending, and an increase in the use of analytics platforms for recruitment as major sports teams have begun to shift to taking a more data-driven recruitment strategy. It is this segment we shall focus our attention on.
The Oakland A’s 2002 league record of 20 consecutive victories was enabled by the leveraging of “Sabermetrics” – an analytical approach to find undervalued players performing highly on specific key metrics. This enabled the Oakland A’s to have a competitive edge whilst keeping within their restricted payroll budget. Since this success, MLB teams have been locked in an analytical arms race in order to compete.
This story was massively popularised by the book, and later the film, Moneyball, which detailed their success in the face of difficult odds with their restricted budget. The figure below illustrates just how well the Oakland A’s utilised such a limited budget compared with the league’s highest spenders.
More recently, the Tampa Bay Rays have experienced an historic play-off run, reaching the play-offs for five consecutive seasons (2019-2023). This run has been achieved whilst maintaining double the league’s average wins per $1m spent, with 1.2 vs 0.6 wins per $1m spent. This shrewd success has been partly attributed to their enormous analytical team, which consists of 39 employees.
It is not that the rest of the MLB does not employ large analytical teams; in 2022, leading teams had around 18 full time employees. Compare this with the average NFL team with just under 3 analytics staff in 2022, and the NBA’s average of just over 4 per team. Lagging further behind is the Premier League; in 2021 only Manchester City and Liverpool were touted as having even NBA-sized analytical teams.
Analytical team size does not wholly reflect the differences between sports in their willingness to take on a data-driven approach; as we will next detail, sports such as football have recently leaned into this transition through widespread adoption of external recruitment platforms.
Digital Recruitment Platforms
The use of Hudl’s Wyscout platform is pervasive amongst top football teams, and this isn’t just exclusive to the Premier League either – over 400 professional clubs use the video scouting platform. Wyscout provides access to footage and statistical reports from both professional and youth football, and its database contains over 400,000 players. This acts as a useful tool for coaches, scouts and performance analysts to identify players which fit their specific needs.
Sportradar’s Synergy Sports in the US is another prime example, being utilised by all 30 MLB teams, all 30 NBA teams, and nearly all NCAA D1 baseball teams. Synergy Sports provides a globally-reaching database of player profiles, video and statistical analysis, and even provides custom scouting reports – largely for the same purpose as Wyscout.
It is important to note that both Synergy Sports and Wyscout were acquired by large Sports Analytics players – Sportradar and Hudl.
Emerging Platforms
With the rapid developments in AI video analysis, platforms which provide automated insights into talent identification are emerging. These platforms provide more than a simple player profile database, and offer greater predictive power.
Ai.io, for example, automates the talent identification process, using AI to generate insights from mobile phone video footage – identifying metrics predictive of a player’s talent. This democratises the recruitment process, meaning that players only need access to a mobile phone to be discoverable – this in turn, expands the net cast by recruiters. So far, Ai.io have partnered with Chelsea, Burnley and Major League Soccer.
The Major Challenge
The overwhelming challenge which these newer platforms face is competing with established platforms on reputation, and their extensive club and player networks. Established platforms have had much of the last decade to acquire the buy-in of many clubs, and their reputation is further strengthened by the name of their parent company. The value in the player network sizes of established platforms is now well-recognised, and emerging players may need to offer similar coverage – or an explicitly different offering to compete.
It remains to be seen to what degree established platforms expand across sports and achieve lower league penetration, and whether they will be able to overcome the friction to uptake when dealing with clients of potentially lower budgets, for whom a change in recruitment practice holds greater risk.
It also remains to be seen whether more innovative platforms emerge, and what sort of success they’ll enjoy. There is risk that they struggle to gain a foothold against the now established digital platforms.
Lastly, it will be interesting to follow the path which emerging platforms take, will it be the same one which Wyscout and Synergy Sports have already taken?
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