I am Arjun Ramaswamy and I am a huge sports enthusiast, so much so that most parts of my vacation life revolve around sports commentary, post-match analysis, player milestones and to a major extent bowing down to the excellence of few individuals on the pitch. I try to utilize as many modes of consuming numbers from the world of sports. I love hearing expert opinions and tactical analysis which believe me is growing out to be an unhealthy obsession. But I love it!
I am the person who social media handles target when they post what has popularly been termed an “ESPN Stat”. Those statistics really don’t change the game. I well and truly believe that even the players don’t think of the game with keeping the ESPN stat in mind. One of my very favourite ESPN stats goes something like this….
Believe me in situations like these the comments sections becomes the funniest place to be in. But not straying too much off topic. We have had a very long journey to reach to a point where data like the one presented above finds it’s day in the limelight.
Stats provide an objective overview of any sport and increasingly it is something adopted by almost everyone in this fraternity for the undeniable advantages that come with it. It is now common place to find a data analyst in a moder day team. Everyone wants a piece of the sweet data pie to just go one step beyond their competition.
Since I am an enthusiast that is very curious regarding the state of sport and how it will grow, I want to take you on a journey what brought us here. How we can expect this space to change and what really does investing in data analysis achieve.
Moneyball
If you have not been living under the rock for this whole time, you are ought to have come across a book called “Moneyball: The Art of Winning an Unfair game”. This book written by Micheal Lewis in the year 2003 presents an overview on the Oakland Athletics Baseball team and their general manager Billie Beane.
In its heart the book looks at how manager Billie Beane and his assistant manager Paul DePodesta use data to identify undervalued players because of their small budget. This coupled with the objective nature of data allowed the A’s to severely reduce risks associated with acquiring undervalued talent, which pushed them towards the roads to success.
The budgets were small and this was the reason Beane had taken such a leftfield method for the time to assemble his team in the most objective way possible. But little did he know that his method will become the norm in years to come.
Moneyball in its truest sense is not about baseball, rather an excellent case study in the advantages of Data-Driven Decision making, challenging conventional wisdom and achieving success in the face of constraints.
In my eyes keeping aside the social impact that both the book and the movie has had with their wide-ranging success, the most important change that Moneyball has had in the sports industry is the wide spread use of Sabermetrics. Tho it is a specifically baseball thing, the term has popularly been adopted in discussions across sports.
At the heart of all of this is the main reason to Moneyball’s success, Player Performance. Talking about which will conveniently lead us to our next point of focus.
Objectivity of Performance Analysis
Objectivity: Freedom from Bias
Data doesn’t lie, it might not always paint the entire picture but it never lies. I enjoy sport for experiencing the beauty of a Virat Kohli Cover Drive, Kyrie Irwing being an absolute menace breaking any and every ankle in front of him, Messi toying with defenders while the ball seemingly is stuck to his feet. Somethings can never be enjoyed in forms of data. They are not objective traits but rather individual brilliance of some very gifted athletes. But they are not to be confused with performance and efficiency. Not everyone is built the same but sport is a great leveller. For every Ronaldinho there is Vincent Kompany, but if you are on a look out for building a team which guarantees performance, often times you might want to leave the spectacle behind and look for certain objective traits.
Performance analysis is everything that the name suggests and then some. Let’s take cricket as the sport in question and look for parameters that a coach might look to build his/her championship winning roster. Averages play a big role in how we perceive a player and their abilities. They provide a good sense of an experienced players quality over a long period of time. In batting you want it to be as high as possible and in bowling it is better to have a sub 25 average. Famously in the realm of Cricket, Sir Don Bradman has a career batting average of 99.94 just missing on a perfect hundred by mere 4 runs on his last ever outing as a professional cricketer.
Reputation has and will always be a factor during selection of players to build your perfect roster and teams today are actively trying to work on striking the correct balance between objectivity and experience. Let us take an example:
In the 70’s Dutch and Barcelona legend Johan Cryuff pioneered the idea of “Total Football”. In his vision for the beautiful game, players would not stick to playing only one position which in time gave birth to players who were multi-faceted. It was common to see players good at playing multiple positions on the football pitch. In contrast today hardly do we see top teams employing players who specialise in more than one position. Roles are defined in a much different manner than back then and many players are unidimensional. On face value that would seem like the sport is moving backwards but this is a big change Data-Driven Decision making has caused since it was implemented by majority of sports teams.
Managers in today’s game like to have players that are great at their positions, gone are the days of every foot behind the ball. Teams play a way more dynamic game with specialist players sprinkled all across the field. Team tactics take into consideration a lot of data about the opposition and player performance.
Look at how we track performance itself, next time you watch your favourite football team practicing, notice the players wearing athletic vests. While being a butt of a lot of childish and light-hearted internet gag they are the corner stones to performance tracking. These vests are skin tight allowing coaches to slip in a GPS tracker on a player’s body. Every metric of a player is measured, their distance covered, heart rate, endurance metrics like periods of high intensity, everything.
We have also seen major improvements in player longevity. Their training and recovery programs is all at an all-time best with the inclusion of data analysis. Hardly are players over used and good teams rely less on an individual’s brilliance and more on holistic contribution. We are able to predict how implementing newer regimes on players changes the course of a player.
Searching and nurturing talent is also something that with the onset of data analysis we are able to perform incredibly.
Scouting and Grassroots Development
In my eyes the aspect of the game that has changed the most in the past few years is Scouting and grassroots development. In the past, talent could pull you to get some opportunities. A lot of players can pass the eye test but when it comes to contribution they might suffer. Newer players are coached differently, they are prepared to play at the bigger stage better because we can today objectively point out what it takes to be successful in sport.
Grassroot level programs in many sports today split positions and roles of their young trainees using body analysis. Whether the trainee is tall, broad, lean, etc. Coaches have found that certain body types perform better at certain positions than others. A very visible example is that of a centre in basketball. They have traditionally been the biggest people on the court. They have better reach for the rim, can easily outpower anyone on the court and don’t move as much as the others which in turn is for their own advantage since moving at that height with some size is not an easy task.
This also actively affects established players. Think of yourself as a journeyman pro for a sec. You want to reinvent yourself because not everyone is gifted the same. Today the first step to take is getting on the whiteboard and start studying data. Forget about what you are already good at and start searching for skills you can offer. Scouts look for specific traits to build rosters, they seldom look for complete players because it is really tough to find someone who is perfect. Only once in a lifetime do we see a Micheal Jordan who could defend and score like a dream, most of the times we find players who are great at a few skills, like Kyrie Irwin (You might have clocked by now that I really enjoy Kyrie), immense scoring and dribbling ability and very ordinary defending and horrible physicality (please stay healthy dude!!!). In short develop useful skills rather than becoming a complete package because it really gives you a better chance to be in a championship level team. Talking of championship level teams, lets look at one such team that uses VR of all things as one aspect of their training.
Tampa Bay Buccaneers and Their unconventional VR training
“We are excited to be coming in on the front end of this new wave of technology that is designed to supplement the on-field and classroom work that our quarterbacks are already doing,”
The above statement is from the General Manger Jason Licht on adopting VR training, making the Buccaneers the first NFL team to make their quarterbacks use VR simulations of in-game situations to train. This method allows coaches to make perfect scenarios for every single opposition and even-if the technology won’t be perfect atleast it gives a better idea than just pen and paper preparation.
“Obviously, there is no real substitute for being on the field when it comes to getting our players ready for game action. However, this virtual reality technology allows us to enhance the learning experience for our quarterbacks without requiring them to put in additional time on the practice fields.”
Also said GM Jason Licht.
The Buccaneers are not alone, Baseball is another sport where VR has been incorporated to some extent in their game prep. The "W.I.N. Series," a virtual reality interactive player development software and simulation solution from EON Sports, has been introduced by the Yokohama DeNA Baystars. The Baystars are the first baseball team in Japan to use this cutting-edge technology, and they join a growing list of professional teams who have done so. Since the 2017 campaign, the team has been training with the system.
These just mark a few examples where data has transformed training in modern professional sport.
Why does it matter?
I started this blabbering fest by pointing out an ESPN stat, and to reach that point of specificity one needs to take in account immense amount of data. Being honest players rarely care about such cherrypicked stats. But their existence is to fulfil someone else, the fan. The spectator, the person who is the stakeholder of sport by investing their time, often times money and a lot of heart into the sport. In the era of social media, the space of debating the latest and the greatest, produces some incredible analysis on players. This is facilitated by statistics and data. I am one, I love to see my favourite players stats, it helps me win online debates, produce compelling evidence to prove my point and ending my day with a sense of false superiority proving another netizen wrong.
While the last statement seems futile, data also facilitates how we view sport now. With working hours increasing, a lot of sports enthusiasts might rarely get their fix of watching the entire game. Ever so often, I as a college student just look at the post-match stat and analyse it to death. Even while watching my subconscious forces me to look at my mobile phone to open say CricBuzz to check how many extras have India given away in a certain World Cup final, or how many turnovers has Eric Dier inflicted today. All this to just fulfil my insatiable need for objective analysis. I am not alone in this at all and people more and more have started giving stats a very important place in their sport consuming experience.
Major debates happen on new scoreboards and how they display information in the most efficient and least distracting manner while also being pleasant to consume all the data they throw at us. Take F1 for example, it is probably the first sport to give data analysis its fair due. It is only fair that the sport that requires it the most has the most complex yet amazingly pleasant leaderboards and players stat.
Data is changing everything that we associate with sport. Well, that previous statement is flawed because data has changed the very fabric of our society as we know it today. Everything that we do in today’s world involves some form of data to be recorded in some server somewhere. But in sport it is visible to the naked eye. It probably is one of the only places where we as humans would give consent to record data.
Sport is changing, becoming a professional at it has changed, the roles in the team have increased while the stakeholders also get their fair share of the pie with incredible viewing experiences. But one should never forget that growing amount of data analytics and data-driven decision doesn’t change the fact that in sport there forever remains mystery and intrigue regarding the events about to follow. At the end of the day the players are human and experiencing superhuman feats from your favourite player is what makes you fall in love with it.
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