Brian Little

01 Mar 2015

PERSPECTIVES: DATA

Data can be a valuable asset or an unnecessary complication depending on how and why you use it. We ask leaders in sport and business how to harness data for better decision making and peak performance.

Brian Little

As well as trying to raise the profile of football in Jersey and set up a games programme to give the senior side more competitive experience, part of my remit is to increase the quantity and quality of data available for analysis. The players are looking forward to receiving more detailed and informative statistics on their performance, and the coaches need that data to influence and support their decisions around how the team can improve.

Things have changed a lot since my days as a player, especially in terms of how coaches help the players build health and fitness and the information we have on performance. Back then, we were told to eat steak and toast before a game, and even to drink Guinness at half time. I used to enjoy getting the basic breakdown of performance on a Monday morning; it was interesting to see who in the side, for example, had covered the most ground and who had most possession. It was groundbreaking at the time and very useful. Today, though, the players are all in great shape and they and everyone around them are more aware of their fitness and individual performances. That's partly because of the data and analytical tools that are now available.

It has made an impact across the board. Tactically, everyone has become more aware and astute. Players and managers are able to analyse the opposition – how they play, what changes they might make, and where they like to play the ball in set pieces. Back in the day, a scout would go to a game and come back to us with a one-page report.

However, while data can help players perform better on the pitch, they still fundamentally need to be able to play good football. And while it can be invaluable in helping the manager or coach to make decisions, their personal touch, impulse and feeling, and ability to make gut decisions on the spur of the moment are essential.

You need the human side in order to put context to any statistics you have. For example, numbers around a player's performance in training won't tell you that their son or daughter is ill or that their partner just left them. You have to get to know each player as an individual, because there may be reasons behind their performance and it takes something different to make each one of us tick.

Brian Little has been a reserve team coach, youth coach and first-team coach, and has managed in every division of the football league, including long stints at Leicester City, Aston Villa and Tranmere Rovers. He was appointed Jersey FA's director of football in November 2014.

 

Bernard Marr

Increasingly, everything we do leaves a digital trace, which we can analyse and use. It is not the amount of data that is making the difference, but our ability to analyse vast and complex data sets without needing super-computers. This means that any business can now use data to assist its decision making. 

The big players are already making a splash – Amazon believes it will soon be able to predict what you will buy accurately enough to despatch it to you before you have even bought it. 

In sport it is an indispensable tool; I worked with an Olympic cycling team that collects and analyses performance data from sensors fitted to the pedals, monitoring how much acceleration or forward thrust every push generates. The team can analyse the performance of every cyclist in every race and training session, integrating it with health and fitness data gathered from wearable devices. The latest innovation is to integrate analysis of social media to understand the emotional state of athletes. 

But, while most business leaders know about big data, many have no idea what to do about it. Apparently we now generate in two minutes the same amount of data that was created from the beginnings of time until the year 2000. Yet less than 10 per cent of the data held by companies is used to inform decision making. 

The reality is that most businesses are data rich, but insight poor. Just because we can measure, monitor and access everything doesn’t mean we should. The danger is we get lost in a sea of data that delivers no value. The key, then, is to focus not on big data, but smart data. Don’t start with the data - you will find yourself lost in an impossible rabbit warren of options - start with your strategy. Be clear about what you need to know and why. 

Data is a new currency and analytics is here to stay; the ability to analyse data allows us to review evidence and make better decisions based on fact, rather than assumption or gut feeling. 

Bernard Marr advises leading brands on performance management and is the author of Big Data: Using SMART Big Data, Analytics and Metrics to Make Better Decisions and Improve Performance. bernard.marr@ap-institute.com

 

Blake Wooster

Data offers unprecedented opportunities for discovery and insight and, when used the right way, can help us understand what happened, why it happened and what will happen tomorrow. It can help us foresee problems and potential through correlations and connections we weren’t aware of. It can rinse our eyes and overrule our cognitive biases. 

As we enter a world of big data, we are being driven towards numbers and extensive analysis. Numbers are supposedly uncontaminated by bias, judgement or opinion. They are objective and objectivity is scientific. Science equals robust. 

But without context data is meaningless, irrelevant and even dangerous. Creating competitive edge with data requires a new type of intelligence - 'contextual intelligence'. 

By applying contextual intelligence, we resist the temptation to undertake retrospective analysis without first understanding the problem we're trying to solve. This avoids both confirmation and hindsight bias; affirmation of the narrative we wanted to see. Contextual intelligence encourages us to begin with the end in mind and seek first to ask the right questions before embarking on our journey of data exploration. 

Contextual intelligence is also about the long-term. It champions a performance-driven (strategic) approach, as opposed to being results-driven (reactive), forcing us to delve deeper and focus on the underlying performance factors that lead to success. 

For example, statistics will tell us that in the Barclays Premier League there is a strong correlation between a club’s wage bill and its final points total. This would assume that teams could lift themselves up the league table by simply offering higher salaries to attract better players. However, this overlooks the fact that there is a divide between ‘rich’ and ‘poor’ clubs, and that when we examine these groups individually there is a much weaker relationship between wages and wins. In fact, there are numerous cases of teams being able to perform much better than their rivals despite having comparable or lower player costs. 

Competitive edge can mean different things at different clubs, too. Context is key. If Club A has succeeded on a lower wage bill through the development of young talent, we must ask: what are the contextual factors that led to this success? Perhaps Club A has few competitors in its catchment area, and the benefit of good schools and open spaces. Club B may not have such luxuries; its own competitive edge may instead be created through the development of a long-term succession plan to capitalise on its limited talent pool or by using data to find inefficiencies in the transfer market. 

By applying contextual intelligence, we begin to uncover the circumstances under which a club can achieve and sustain an advantage and render the correlation between money and success close to irrelevant on an individual level. Do it well, and bridges will appear to help you cross the perceived chasm between rich and poor. 

The meaning in your data comes from applying contextual intelligence to a problem; enabling business leaders and football managers to make better-informed decisions. 

Blake Wooster is the co-founder and CEO of 21st Club - a management consultancy and software business that works in football: www.21stClub.com

 

Dougie Freedman

As a coach you must have a good eye for how your players are performing, but data can be useful in backing up that view. It’s important, though, to use it that way around, because data can also be misleading. For example, it might tell you about the overall intensity of a player's training, but as a coach you also need to think about when they are performing most intensely and with most speed. I trust my own judgement to tell me that, and if the data doesn’t support my view I'll examine why and what I might have missed. 

Fundamentally, though, you always have to rely on your instinct, and on the knowledge and understanding of people that you have gained through experience. My eyes often pick things up that data cannot. 

Data can also be useful in motivating the players, because you can tell them what you've seen in their performance and what they need to do to improve, and then show them the proof. You can also use data to show them the strengths and weaknesses of their opponents; the kind of detail that many players these days expect. 

Players today don't just want to be told what to do or how to play; they are very open to discussion and data can be very helpful in that process. 

Dougie Freedman managed at Crystal Palace and Bolton Wanderers before becoming manager of Nottingham Forest in February 2015.

 

Alex McLeish

It is now so easy to access and use data in football.

In training, it is helpful to be able to split players into different groups according to their individual needs. For example, members of one group might need to work on their core training, while others might concentrate on power. With data analysis, individual players can be tested so that we know what their weaknesses are and where the focus of their training should lie.

At Racing Genk, data is particularly useful in youth development. We are bringing in a lot of teenagers, and data is helping us to identify areas for improvement. In the first team, it can also be invaluable in supporting our decisions on when to rest players, which is especially important for young players in the first team. 

But, while data is an integral part of the game today, it is not the be all and end all. My long career in management has given me a feel for players – their individual needs, work rates and performances. Sometimes I may think the opposite of the sports scientist about what a player should focus on, because I know what that individual needs in order to improve.

You can't argue with the data, but I might feel that an older player, for example, could miss a group session or ease off on training in order to keep his mind sharp and prevent him from feeling stressed about following the squad's programme. I take individual decisions based on my know how, feel for a situation and experience, and the fitness coach respects that. With experience you learn to read situations and to trust your knowledge and opinion.

In Alex McLeish's 20-year career he has managed at eight clubs, including a spell with Scotland in 2007 and since then at Birmingham City, Aston Villa and Nottingham Forest.