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Data & Analytics Human Performance Performance | 18.02.19

How Manchester City Translate Data into Meaningful Interventions

Nick Chadd, Head of Sport Science at the Manchester City Academy, says that it must come down to the person doing the interpreting.

“Data is great but it can also be difficult to interpret and understand,” says Nick Chadd.


By John Portch

The Manchester City Academy’s Head of Sports Science oversees the data collection of nine teams, from Under-9 through to the Under-23s. That means 200 players and nine different head coaches trying to make sense of the numbers in front of them.

Chadd continues: “We can all put the same set of data in front of everybody but it comes down to the person interpreting that and then translating that into what I would call meaningful interventions.

“One of the things I’m big on is making our data live because there’s no point in collecting all this data, having it sitting in a databank and it not informing anything or not living.”

So how does data ‘live’ at Manchester City and how is its use evolving over time? Chadd, who has been at City since 2016, tells the Leaders Performance Institute that it remains a case of data informing coach intuition, integrating players into your process, and adopting a fully aligned approach across all coaches at the Academy.

How are you making the most of the data you collect?

NC: The strategy that we have put in place is to scale our data collection accordingly. By that I mean we collect less data at certain levels and more data at certain levels depending on the way that we’re resourced and also dependent on some of the key time points in an athlete’s development and as they get closer to being a professional footballer. From that perspective, we tend to collect less data at younger ages and collect more data as they get older and ensure we have a set of comprehensive data to make decisions.

Are you using data better these days that say a year or two ago?

NC: I hope so! I think we’ve put some systems in place that ensure we use the data. For example, we have regular reviews, which isn’t ground-breaking by any stretch of the imagination but we have regular six-weekly training reviews across four different teams. The data that comes out of those reviews is aligned so that we can compare between teams as well. One of the biggest challenges I find is aligning our system across multiple teams to ensure that the athlete is getting a progressive and continual pathway and they’re not chopping and changing the pathway as they go from one set of coaches and practitioners to another. It’s really important to me that they have an experience that is progressively challenging but all in line with the methodology we’re trying to put in place.

Processes evolve over time but are you able to complement historical datasets with the current?

NC: We do and that comes down to having a really robust data collection system in place and being tight and stringent on that regardless of a new coach or a new practitioner coming in. They have to follow this process tightly and stringently because we need the data they collect to be comparable.

To what extent is data used to support intuition? Where is the balance between gut and what the numbers say?

NC: A lot of my data conversations start with the sentence ‘we already know this but this confirms what we’re thinking’. That’s not a bad notion because that means we’ve got people with this skill for picking up certain things; every now and again the data will throw up something that maybe someone hasn’t picked up or something that someone highlighted or just sometimes just having the opportunity to step back and have that helicopter view; as we know when you get into the day to day task you can sometimes miss the bigger picture and that’s where the data can come into play as well.

Do you share data with players directly?

NC: The way it’s scaled is that we tend to collect more data on them as they get older but we do share it with them. We might share any performance-related data with them and we do that in different capacities; so it might be individual one on ones, it might be to create a cultural sense of competitiveness around the building with our data in terms of who’s achieving what and how they are going about doing that. Players are very integrated into the process of our data collection and what it tells them, but if they have the capacity to understand we let them know the pitfalls of the data as well, that it isn’t the be all and end all, that there is error in the measurement. I think once you get the player onboard and integrated into that, they certainly have the capacity to understand that and it can become a very powerful tool.

And a conversation with a coach will differ to that with a player?

NC: You are taking a different approach in each case. Don’t forget that coaches are often ex-players – and very new ex-players as well – so we have to be mindful of their understanding of data as well. Sometimes we assume they’ve been party to the same background or exposed to the same line of data as a sports scientist and that isn’t always the case. If I’m honest, what I’m finding now is the most powerful data is the simplest data. It isn’t always digestible for people and you can’t always see the wood for the trees when there’s an overload of data.

Some sports teams are concerned that data is proliferating faster than they can recruit the expertise to decode it. How do you work to prevent a skills gap?

NC: It’s something that I’m really aware of and it’s about doing simple things really well and effectively, where we’re sure we can rely on the interpretation of that data, that it’s repeatable, that it’s robust rather than do lots of fancy one percenters but not do them very well at all and not be able to rely on them. Unfortunately, it’s not sexy and it’s not what people want to hear but I’ve been to quite a few things where people want to talk about marginal gains and the one percenters and quite often a lot of it comes back to the other 99%. Are we dead set that we’re doing that 99% as well as we can? And if we’re talking honestly then probably not.

Have you enjoyed the support of Manchester City?

NC: 100%. I couldn’t do it without the data insights team and performance analysis team, the club have been absolutely fantastic and integrated with us and want to work with us; there are absolutely no barriers when it comes down to the people and the people want to make this work and get the job done and do the best possible job we can do. And that goes across the whole club, you can see that in the way people work together, and it’s fantastic to be part of.

What do you feel have been some of your biggest challenges in the last 12 months?

NC: Biggest challenges have been getting a uniform, secure and reliable storage point for data and then also getting staff to a place where they can utilise software and databases effectively to be able to interpret that data in a timely manner, not taking up an inordinate amount of their time having to enter data and then analyse it and then interpret it. I think that’s my biggest challenge and my biggest learning has got to be not trying to make it over-complicated; let’s maybe use simple data and effective data that’s reliable make sure it can tell us what it really wants to tell us.

What do you feel have been some of your biggest successes?

NC: We have some really good central databases where we’ve worked with data insights team here at the club and coordinated really closely with them and been proactive in working with them. I think that’s been one of my biggest successes in terms of integrating them really closely to assist us with taking our data management, our data analysis and interpretation to the next level. We now have a system where a new member of staff can drop in, you give them the relative permissions, and then they’ve got access to these databases.

What do you anticipate being the biggest development in data in football in 2019?

NC: From a youth development perspective, I would suggest identifying talent and identifying talent relative to the talent that has been before and looking at profiles of what has been before relative to new talent that’s being identified out there. It’s too easy to go and recruit the biggest athlete in that age group and get them to come in and do a job on that day, but that’s not what we’re here for. The longer term plan and the longer term vision is to create football players of the future, so the future doesn’t necessarily mean they’re here now but it’s being able to identify that through multiple aspects and then having the courage and skill to be able to stick with that.


Nick Chadd also appeared in the Leaders Performance Institute’s Special Report on performance trends to look out for in 2019. Download the report here: