When S Ramakrishnan, or Ramki as he is known, headed to National Cricket Academy in 2003, he had a dream-Express News Service)
Technological innovations have made it easier for coaches to plan. Venkata Krishna B finds out what goes on behind the scenes and how experts compile a massive database to feed the players and teams with all the information they need…
When S Ramakrishnan, or Ramki as he is known, headed to National Cricket Academy in 2003, he had a dream. To feed the kind of data that would make a small but important contribution in separating the best from the good. It was supposed to be a 45-minute session, to introduce coaches like Roger Binny, Balwinder Singh Sandhu, Bharath Reddy, Sandeep Patil to data analytics, with John Wright overseeing what was going on. It turned out to be a day-long event once the coaches started realising how helpful this could be.
Back then, data analysts were unheard of in any sport in the country. That it took Wright, who hails from a country which had invested in the technology, almost three years into his India stint to include Ramki into the team fold tells how slow India was in embracing it. “After the presentation, Wright asked me if I could join the team,” Ramki says. While he jumped at the first opportunity, the New Zealander had made one aspect clear. “The pay won’t be good.” So when Ramki officially joined the Indian team for the two-Test series against New Zealand in 2003, his first pay package was Rs 30,000.
There was another important task that lay ahead.
“I need to win the trust of the players. I was not an ex-cricketer. If I go up and tell them ‘this isn’t working for you, you can try this instead’, the first reaction would obviously be what credentials you have. At that time, the team had so many stars.” But with the likes of Sachin Tendulkar and Rahul Dravid around, Ramki’s job would get easy. It had its struggles too. While the rest of the support staff would stay in five-star team hotels, Ramki would be put up in ordinary lodges. “I would often shuttle between my hotel to the one where the team was staying because some player or the other would seek help. It was all about analysing the footage and learning by watching the patterns.” Ramki was part of the team without getting to wear the team kit or the BCCI logo, as he was still considered an outsider in the set-up.
Today, Ramki’s brainchild Sport mechanics is a pioneer in data analysis. Their analysts in Chennai spend days examining the patterns, trends, conditions along with the weaknesses of the opposition. Other than the Indian cricket team, the national hockey side, Mumbai Indians, International Cricket Council Academy in Dubai, Reliance Youth Sports Foundation (football) are among their clients. From an organisation with only five members to start with, they now have nearly 50 professionals who have their eyes glued to matches around the globe.
Chief among them is CKM Dhananjay, hailed as India’s most successful analyst. Fondly called DJ, he is in his second stint with Team India. An MBA graduate, he took over after Ramki left and was with the team when they won WT20 in 2007 and the World Cup in 2011. Last year before the South Africa tour, the team brought him back. He has been sitting in his workstation at Sportsmechanics for the past 15 years. When the whole of India, including the players, were busy with the IPL, DJ was finishing his homework.
That involved reading each of India’s nine opponents at the World Cup: 135 players, six venues and the conditions they offer. He will place the details before the coaching staff to help them strategies.
“When we watch the footage, we look for patterns and explore why it happens. Our engines identify those and how each player reacts in certain situations. We then devise a plan, which is based on data. We leave out the cricketing acumen because that lies with the experts — coaches and players. Once we have a definitive plan, we put it across the coaches, who can build on it. They are the ones best suited to draw strategy. But what they use to devise it is where we come in. We converse a lot before it reaches the players. If we spot something in the opposition that the team can work on, we present them with the possibilities and options. There on, they choose what is best. There is a domain aspect and data aspect. When these two combine, it becomes more powerful. Players are the ones who take decisions at pressure points. If you empower them with credible data, their instinct becomes stronger. We are not challenging their instincts or intelligence, but providing data that is digestible for their own preparation,” DJ reveals.
Example in real time: During the IPL, Lasith Malinga bowling round the wicket to Andre Russell. It was data driven as the Sri Lankan had never offered him that sort of angle. Russell kept swinging for the hills, but connnected only with air.
As the IPL was growing into a beast, Ramki remembers knocking the doors of each team to use data-driven coaching. His introduction would begin with a simple question: “Have you watched Moneyball?” If the answer was no, Ramki would hand out a DVD and ask them to come back later. There is a reason why he chose the Hollywood hit to drive home a message to owners, who spend millions each year to assemble a squad. The baseball-centric movie revolves around how a low-budget club attempts to put together a squad completely based on data.
Mumbai Indians are the most successful IPL team with four titles. It isn’t a coincidence that their run of success began after they leaned heavily on data analytics. They are the model team for data-driven coaches, who are coming up more and more through the system. Much of what the Indian team does today can be credited to DJ and Ramki, who were finding new ways to change the role of a video analyst. “If we don’t add value, it’s better to walk away,” says Ramki.
Gradually, the Indian team has evolved a system where data exists in the planning stage as much as cricketing aspects. DJ aligns with the philosophy of the coaches on to what degree they can incorporate data into preparation in consultation with the leadership group before passing it on to the team. Before each series, DJ with the help of his team in Sportsmechanics puts together the necessary data. On tours, he is in constant interaction and discussions with Sanjay Bangar (batting coach), R Sridhar (fielding coach) or Bharathi Arun (bowling coach), often around to develop strategies. While it is common for players to access data at this level, the simplicity of the process is most striking. Today an India cricketer has access to footage and figures dating back to 2007 on his mobile. If need be, the coach can send a player a certain video and even have a video tutorial sitting anywhere in the world.
“How do you know the holy hour of a player? Nobody will know that. So you have to provide it in his handset and make yourself redundant. It’s an art of storytelling.
The only difference is, I’m using cricket data and cricketing intelligence and delivering it to coaches to formulate strategy. We can’t ask (Jasprit) Bumrah to bowl an outswinger just because a particular batsman struggles against such deliveries, since it is not his stock ball. All of this data is personalised and handed to the player depending on his game plan. For example, Kuldeep (Yadav) will see only his kind of bowler bowling to a right-hander. If Rohit (Sharma) wants to see shots played on a slower wicket, he can get that. You can go by condition, venue, weather and lot of other variants. When we say deep dive, we really do. It is an ocean of data that we have. We only made it easier with a mechanism where it is in their mobiles to start with. It has helped them increase productivity by 400 per cent. We only contribute one per cent, 99 per cent is done by the team. But without that one per cent we can’t get 100,” DJ says.
Example of a player who has benefited immensely: Bumrah. The ace pacer likes to learn only by watching. All the vital statistics against different batsmen. One click and he gets the video with relevant data.
Today, India are regarded as a tactically well-equipped team. Their bowlers are a testimony to that. “Since Arun’s entry, taking 20 wickets has been happening regularly. There is a role everyone is playing. Bowlers, coaches, data.”
When BCCI began to tweak its operative system by going digital, it opened a gold mine of data for analysts and domain experts. Earlier, selectors and coaches were going by numbers which weren’t backed by enough data or didn’t actually paint a true picture of a player’s potential. As the BCCI moved to live scoring of all domestic matches — a system developed by Sportsmechanics — it widened their scope of work. With all the matches recorded on six cameras, there was ball-by-ball data for any given match that a selector or coach could revisit. Taking a cue from the Indian team, the state associations of Karnataka, Tamil Nadu and Haryana have started investing in data-driven coaching.
“We are helping their cricket operations with regards to scheduling, cost-cutting, evaluation of umpires and referees. Data analytics is going to play a more significant role. We have data from all matches which have live updates.
It is beginning to enter school-level tournaments. That is a huge base. A school-level cricketer as he moves up the ladder will become part of this data-driven culture and by the time he graduates to the senior level, he will be his own analyst. Like any planning implementation, people involved need to believe data is there to help. We have rewired a few of our analytics. We have given it a twist with Artificial Intelligence where the outcomes are coming out really well. For example: If you want to show the area in which a batsman scores in the air, the engine will do it in seconds. He is going to have a virtual analyst who can tutor him by sitting anywhere. We want to start a revolution at the grassroots because that will benefit many. Future coaches will have data in their armoury. I foresee a big change in this area where former players will see this role as career opportunity like we have (there are former state cricketers working for their company),” says DJ.
Needless to say, data-driven decision making and analysis will become non-negotiable for next generation coaches. “This must be part of their education from Level 1 onwards as former players turning into coaches is a trend that will usher in a huge change in the coaching scope system and we are excited to be playing a role in this change.”
Smart coaches, smarter players.
(The article first appeared in The New Indian Express dated 24th May 2019)