Feature
Football is big business and
mistakes can cost clubs millions. How do teams make the best of their resources
and identify areas for improvement?
The secret to improving
performance on the pitch starts with understanding the gap between a team’s
current level of effectiveness and the level they want to reach.
Teams monitor their own
players via wearable sensors like the Catapult Sports OptimEye S5 and analyse
their opponents using statistical data from InStat, Opta and Prozone.
When Liverpool FC’s Philippe
Coutinho scored a free kick against Brighton in December 2017 by firing his
shot underneath the jumping defensive wall, Jurgen Klopp credited his analysts
for pointing out the opportunity.
Data was also instrumental
when Hearts ended Celtic’s 69 game unbeaten run last year. Hearts Manager Craig
Levein revealed that Anderlecht's 1-0 victory over Celtic in the Champions
League had pointed the way.
"The analysis of the Anderlecht
game," revealed the BBC[1], “showed that the Belgians played a pressing
4-3-3 and that the three midfielders and three attacking players covered an
average of 11.8km per man when hustling and harrying Celtic out of
possession."
Thanks to their own club
analytics, Levein and his coaching staff knew that they had players who could
cover that sort of distance. So, the strategy was to "hit the 11.8km
average, frustrate Celtic, press them high up the pitch, cut out the passing
route to their most dangerous players, refuse to let them settle and force some
errors."
Using data from a football
database like InStat, teams can analyse multiple aspects of player performance.
Football has become
increasingly data-driven and Hearts drew upon InStat’s vast database of
football statistics to help mastermind their victory.
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technologies can unlock the potential of your business data ›
More than 1,500 clubs and
national teams use the system, which features information on more than 400,000
players. According to InStat, over 6,000 new video records are added to the
database every month and the company employs 500 people in its Production and
Data Center to analyse and document every sprint, kick, dribble, challenge, and
pass.
While InStat data can prove
vital in areas such as opposition analysis, match preparation, scouting and
player recruitment, clubs also assess the performance of their own players using
wearable sensors and analytics.
A typical Catapult Sports
wearable vest with an embedded OptimEye S5 device, for example, can collect up
to 1,000 data points per second. It can measure fitness and skill levels,
response to specific training techniques, tactical performance, and risk of
injury.
Bournemouth striker Jermaine
Defoe trains in a smart vest, incorporating a Catapult Sports OptimEye
S5.[Image copyright Catapult Sports (catapultsports.com)]
The STATsports Apex pitches
itself as the ‘most powerful wearable in sport’ and can calculate over 50
metrics in real time on the device. In addition to core performance indicators
such as max speed, sprints, heart rate, and step balance, it can also number
crunch factors including High Metabolic Distance and Dynamic Stress Load.
“These show how hard a
player is working,” say STATsports, “and how much a session has affected them.
GPS tracking isn't just about how far a player has run, but how they have been
affected by the exercise. Crucially, this data can be viewed as training is
happening, due to the on-board data processing power [of the Apex module.]”
Data from the Apex modules
is stored in the STATsports cloud infrastructure, allowing coaches and managers
to access the information anywhere, anytime and on any device.
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It’s never been easier to
generate and access footballing data. But it’s what you do with the data that
counts. To some extent, an analysis of past performance can inform predictions
for the future – which players to buy, formations that work best against a
certain opponent, the percentage chance that crosses (rather than through
balls) will result in a goal.
“If I have a football club
and our objective is to get into the Champions League,” analyst Rory Campbell
told the Independent, “there are loads of things that are going to control
whether or not that happens.
“How many points do we need
to get into the top four? We can work that out. Then how many goals are we
going to need to score? What is our goal difference going to be? Then let’s
drill down to think about exactly how many shots we are going to need to have,
and how many shots we are going to concede. And work back from there.”
Football
The STATsports Apex tracker
can deliver over 50 physical metrics to coaches in real-time. (statsports.com)]
With measurable objectives
to aim for, a football club could then assess its own resources and see how
much of a gap there is between where they are today and where they want to be
tomorrow. If a team isn’t creating enough goal-scoring opportunities, for
example, can that be improved by a change of formation or a new striker with a
higher shots percentage?
Of course, with so many
variables in the average football match, analytics isn’t a magic bullet.
Statistical predictions can be upended by simple human error – a missed shot, a
poor pass, a clever dive or a contentious refereeing decision. Or they can just
as easily be defined by a moment of brilliance from a world class player.
But, used intelligently,
analytics technology can give teams an edge over their rivals. Sensor data from
training sessions -- along with what players eat and how much they sleep – can
be combined with cloud-hosted, instant-access statistics from the likes of
Opta, InStat and Scout7 to help identify in-form players, define personalised
training regimes and improve physical performance.
A football match seems
impossible to model - 22 players (with their own strengths and weaknesses),
three officials (ditto), contrasting formations, luck, randomness, pitch conditions,
weather effects, crowd noise, the cumulative behind-the-scenes impact of
coaches, doctors, physiotherapists, masseurs, kit managers, nutritionists,
analysts and sport scientists.
But with a combination of
cloud computing and big data analytics, teams are beginning to understand the
probability of success and, more importantly, what they can do to improve it.
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Sources
1.
http://www.bbc.co.uk/sport/football/42395891
2.
http://instatsport.com/en/
3.
https://www.catapultsports.com/
4.
http://statsports.com/apex/
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