Michael Edwards secret weapon reveals what FSG told him about first Liverpool transfer plan

Michael Edwards secret weapon reveals what FSG told him about first Liverpool transfer plan


When Dr Ian Graham arrived at Liverpool in 2012 he had a blank canvas.

A club that had not invested much into data analytics previously was now attempting to chart a new course, one that owners Fenway Sports Group had managed to introduce with great success at their Boston Red Sox baseball team.

FSG supremo John Henry had long been enamoured with the idea of ‘Moneyball’, where using data and statistical analysis shaped decision making when it came to finding the right players for the squad for the right price, helping to reduce the risk on poor decisions in the transfer market.

The model has had its critics but it has undoubtedly been a major factor in Liverpool’s success in recent years, with FSG having set their sights on nobody else other than Jurgen Klopp to oversee their way of working.

Even recently the impact of Luis Diaz has shown how adding players who fit the Liverpool mould and who are the right age and profile can pay dividends.

The £36.5m paid for Diaz already seems like it will be a snip, and the same can be said of deals down the years for the likes of Mohamed Salah, Sadio Mane, Roberto Firmino, Andrew Robertson, Fabinho and others.

But what is the process behind the data and how much does it inform Liverpool’s decision making process when it comes to recruitment?

Dr Graham, in his role as director of research at Liverpool, has been working alongside the likes of outgoing sporting director Michael Edwards for the best part of a decade.

Where data analytics for some clubs had been seen as a box that needed to be ticked, Dr Graham was afforded time to get a system up and running that would make a difference to Liverpool moving forward. It was a key part of the FSG strategy.

“Our objectives are clear as to win. What we try to do is maximise performance as cost effectively as possible,” said Dr Graham, speaking at the Financial Times’ Business of Football Summit.

“In terms of areas where the data team helps out, it is tactical, on-pitch performance about the performance of Liverpool players and our opponents game to game.

“We work closely with the Academy to provide data to help develop players as well as the fitness and medical departments.

“But really in terms of impact versus costs, recruitment and squad planning is where you can make the maximum impact.

“If you don’t have the correct players in the squad that are able to challenge for Champions League places and to win competitions then you are severely limited.

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“My first year at Liverpool in 2012, the first 12 months was exclusively built on recruitment applications. I told our owners it would take a year to build that stuff and they said ‘fine’.

“That long-term planning and adoption of data was rare at football clubs at the time and luckily for me the owners saw the value in it and we have had some success with that approach.

“Liverpool is a lucky place to be. When I arrived there was very little in terms of anyone doing anything with data in any sort of systematic way.

“Coming into an organisation that doesn’t have data meant that we could build it in the way that we wanted, which really meant we didn’t have the silo problems like the medical data being separate, or the physio department being separate.

“We spend a lot of time building data pipelines to take in reports from scouting to medical. Staff can see all our data in one space.”

“We are mostly focused on the first team but we have one staff member that spends part of his time working with the Academy.

“If I can approve extra budget then the next hire will be to get someone to work full-time with the Academy. We don’t give them enough service.

“The same data we get for the first team, aside from tracking data, we collect down to under-16 level.

“We have done that for the past 10 years so we have built a good picture of how performances at U16 level translate into U18, U20, U21 and the first team to help us understand the development profile of players and where might be a good landing point for a player we might want to put out on loan to help their development.”

While data allows for Liverpool to make more informed judgements on where to place their young players and where they might fit in future development, the best use of data still exists in navigating the transfer market and whittling down recruitment options.

“Recruitment is the best use case for lots of reasons,” said Dr Graham.

“There are so many thousands of players playing for different teams that the basic filtering of making a shortlist of players and understanding the cost is something that naturally data analysis is very suited to.

“What makes a good player will be pretty similar to what makes a good player for Liverpool. We will have our own requirements but generally the pattern of what makes a good performance is the same across a number of leagues.

“In terms of working with Jurgen and his coaching team, we don’t work with them directly.

“Very occasionally there will be a specific question that they want answered and we are always happy to answer it but it isn’t the case where I have a data debrief after a game or I talk about upcoming opponents.

“The way the process works is that our data analysis and those meetings happen with the performance analysis staff or the recruitment staff.

“They spend a lot of time understanding what that data is saying. Data informs their reports and their meetings with the coaching staff.

“Occasionally there might be some statistic or metric in a report, but equally as often there might be no mention of metrics or statistics to the coaching staff because they aren’t data science people and it isn’t a great use of their time to make them do a statistics course to understand the details of what we are talking about.

“That statistical analysis informs the report and that data might come out in a video clip that gets played or for recruitment, talking about a particular strength or weakness of a player.

“There are two sides to data. The analysis and the synthesis. We spend a lot of time trying to have one football language to speak in, so we speak in terms of goal difference as getting a high goal difference is what wins you more games.

“Our ratings for players are in terms of how much goal difference they will add to a team and that can be split up into many different factors to tell us how they are providing that goal difference.

“In order to get a list of players from one to 100 is the first think you rank them on. If they come to Liverpool how will they improve the team and improve the goal difference.”



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As football has moved with the times, so has data analytics.

The ‘Moneyball’ approach, popularised in the movie of the same name that followed the exploits of the Oakland Athletics baseball team under the stewardship of baseball analytics pioneer Billy Beane, a man who Henry, portrayed in the movie by actor Arliss Howard, had tried to lure to the Red Sox, wasn’t so widespread in football when FSG took ownership of Liverpool in 2010.

That has changed, and while many clubs now claim to have adopted the analytical approach, Dr Graham believes there are only a select few who use it to truly inform their decision making process.

“Over the past 10 years the biggest difference has been what data is available,” he explained.

“Back in 2012 we only had event data which showed us where the ball was which made it difficult to measure defensive performance for example, where a lot of important things that defenders do are not on the ball.

“As you get new sources of data we have developed our models to take advantage of them and learn difficult lessons along the way.

“So, a player we analysed 10 years ago as the best in class maybe weren’t the best in class because we couldn’t see some of the vital things that they were doing.

“The treadmill is can you stay on top of the latest data, and the artwork is what data is worth making use of.

“In terms of Moneyball, it is absolutely still possible. Lots of clubs say that they do analytics, but just having an analytics person in your club is not the same as having your decisions influenced by analytics.

“Like sports science 15-20 years ago, because Manchester United were successful using it a lot of clubs tried it, and I’m sure most of them had it as a box to tick for their owners to say that they were doing it.

“The trick is the implementation, you need the owner or sporting director to change their decisions based upon the analytics are saying.”





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