What is Playrs?
Going beyond collecting data and analysing it, the “Moneyball Revolution” in football presents football clubs with ways to implement this raw data into their player-purchasing and on-field strategic approaches.
We at Playrs strongly believe that the football industry as a whole is ripe for a revolution. The current method of collecting and executing player in-game data results in a constrained analysis which does not cover the entirety of a player’s performance during a game.
As a result, a certain football player’s overall performance may be misrepresented in real time, whereby certain actions are not taken into account. This could in turn affect a player’s market valuation and overall ranking on a national and global scale.
Football clubs who wish to scout for a specific type of player with particular abilities can use data to narrow their search down to a shortlist of potential candidates; and even go as deep as using data to help make the decision between two final candidates, thus considerably lowering the risk in player acquisition.
On the other side of the industry, media bodies are increasing their use of data in order to promote their expertise on a team’s performance, or a player’s work rate. Major sports channels use extensive data in order to provide in-depth match analysis on a daily basis. Agents can also use this tool to manage their player portfolio and have a real-time as well as in-depth insight into their clients’ performances and market valuations, based on the most extensive set of data available on the market.
In order to achieve an efficient analysis, whether the goal is to facilitate a manager’s player recruitment decision or for the benefit of a panel’s postmatch analysis; raw data most commonly needs to be collected from a data provider via a live feed. Consider the inevitable 30-45 second delay, and you find yourself with a data source which does not provide you with real-time benefits.
So, how do you achieve real-time team & player information, without having to physically be at the stadium? And more importantly, how do you justify the data’s validity?