Tennis and badminton are two racket sports that have serves, backhands, forehands... but the similarity nearly ends there. They are vastly different in how they are run, the structures in place, the global spread, the money involved in the sport. But we will not get into all those aspects.
In my previous column, which touched upon what India must do to build on the Thomas Cup triumph to become a badminton powerhouse, I had written about the need for a ‘Moneyball’ approach. Extending that, in this article, I will elaborate one important aspect of that – the use of data – in three different parts.
I was watching Roland Garros a few weeks back and as a spectator, the viewing experience could not be further away from badminton in terms of the data that is provided even to the casual viewers. The watching experience becomes so much more interesting with detailed stats after each set. It helps keep the viewers engaged in the match even more.
Of course, badminton is not there yet in terms of reaching the sophistication of tennis as a product. But it is high time steps are taken to embrace data more. So, let’s talk about how improved use of statistics and analytics will help the sport... not just from a viewer’s perspective but also from a coaching and player point of view.
A spectator’s view
One of the possible reasons for badminton viewership having not reached the length and breadth of a sport like tennis, in my opinion, is the lack of statistical breakdowns that often get the fans talking.
If you have been watching badminton on television for long enough, you’d know that the production set-up doesn’t provide much more to the viewers in terms of visual graphics other than head-to-head information, the score itself, the rally length on a few occasions, and sometimes, the speed at which a winning shot is hit.
It is the bare minimum and it ends up having a spiral effect on the live commentary. There are, for instance, no stats about number of winners/unforced errors from the forehand/backhand side. No stats on what side of the court each player is targeting. No information on points won/lost on serve. And these are not even high-tech requirements. Such lack of statistical discourse doesn’t feel encouraging for someone who is looking to gain technical knowledge of the sport.
Certain systems have been trialled in the past evidently but not much is in place right now for in-match and post-match data. You are often left relying on an impression of what you saw, and this is true for post-match analysis as well. If you’d like to check key stats after the match is over, there is not much information out there.
Ideally, you would want to see things like the total distance covered, number of winners/unforced errors from each side, percentage split of shots played on the forehand and backhand side, number of smashes hit (and percentage of success) so that we know who has taken the more attacking approach in the game. In doubles it could be the average smashes from each pair, number of points won in a row, and, importantly, number of points won in the first 3 strokes of a rally.
Yes, all of this would be expensive, but if we need to break out and drastically increase the sport’s viewership around the globe, then making the broadcast more visually appealing is key. Improving the statistical production value of matches being telecast live is the definite way forward.
Use of data in scouting
We will look at the analytical side of things shortly, but before that, we shall touch upon the importance of data in scouting talent, something that is portrayed brilliantly in the movie Moneyball. A scouting team’s job in a high-performance badminton set-up would be to look for the style of players which the national squad is currently lacking.
So let’s say, we are short in the men’s roster for the mixed doubles team, so the scouting team will ask the kind of statistical attributes needed in a player to make a potential roster. The inputs would come from the coaching team and then the process must begin to look to bolster the roster from the domestic circuit. If the attributes are met, the player could be given a trial at the National camp for the coaching team to see if the player has the potential to be fast-tracked into the set up or not. This method could be used across all events for better talent identification. Again for this to work, the coaching team, the analytical team and the scouting team would need to be in complete sync with each other.
In High Performance Centers
Now this, for me, is the more interesting part.
As written in the previous column, badminton in India must move towards a centralised High Performance Center-type set-up. And here, firstly, we need a proper sports analytical team which would include the head analyst, a few assistant analysts and perhaps a few data-crazy experts who have studied sports analytics and have an understanding of how stats in sports work. The key, then, is to have a database of matches of all players in the Top 100 across all events. There has to be one person from the analytical team who is travelling to tournaments with the primary reason being recording as many matches as possible.
The sports analytical team’s job is then to try and derive as many stats on all players as they can. As part of the data team, they would have no work on court when the players are training. So, once the tournament draws are out for any major event, and the players know who they are playing, the team must hand over the detailed raw data to the coaching team.
They don’t have to be badminton experts but the important aspect is to have an understanding of the sport in terms of the different types of shot. That has been a problem area in the past. Unlike tennis, a forehand in badminton could mean a wide variety of shots: clears, smashes, slices, reverse slices, spinning shots, net dribbles, half-smashes etc. It would be crucial for those doing the video analysis to take into account those variations. But apart from that, to make inferences or form opinions and such, it would be the coaches’ job to figure out how to use the data.
Badminton is a highly instinctive sport and a lot of factors could determine the way the player is playing on a certain day. For example, HS Prannoy lost to Zhao Junpeng at the semifinals of Indonesia Open Super 1000 recently, and it was a performance that he would want to learn from as things didn’t go his way despite being in great form that week in Jakarta.
Now, if Prannoy is scheduled to play Zhao at any tournament in the future, the coaching set-up should get a detailed data packet from their last meeting. A short study which should include number of back-court and front-court winners/unforced errors made by Zhao, the pie-chart percentage of the whole court on where Zhao played throughout the game, percentage of how many shots were played to the back-court and front-court on Prannoy’s serve. Then it is upto the coach to interpret this data and sit with Prannoy and make a plan on how to beat Zhao in their next meeting, and schedule training sessions for key skills in that regard.
It is a big investment but that’s where the future of the sport lies as margins become finer and finer.
There are software applications coming up which could make the life of analysts easy, by taking into account the many intricacies of badminton. It will evidently require a good investment of money and manpower from the federation and Sports Authority of India. But it is an area which could play a major role in pushing India to win more major events in the future.
Shlok Ramchandran is a former Indian doubles player, who reached a career-high world ranking of No 32 in men’s doubles. Having recently retired from the highest level of the sport, Shlok is currently head coach at Triangle Badminton & Table Tennis in North Carolina, USA.