Author: Ramkumar Ananthakrishnan
Data Analytics in cricket, especially in the immensely popular T20s, such as the Indian Premier League (IPL), has become very critical today. Unbeknown to the hundreds and thousands of fans watching this global sporting event from their homes, a mind-boggling amount of data is being collected and analyzed every step of the way.
However, to those of us who enjoy numbers and also live and breathe cricket, what happens behind the screens is just as exciting as what happens on the pitch. How these numbers make or break a game can be exhilarating, which we will explore in this article. Though Covid-19 bowled over IPL this time, suspending the event midway, there’s no reason why we can’t use this time cooped up indoors to better understand the role of data analytics in cricket, and why analysts are so sought-after today.
Picture this: It is a bright, sunny day. You are confidently walking onto the pitch to face your arch-nemesis in the fifth and final match of the series, the one that makes or breaks the game. You are holding the ball now, focused and ready to charge. Before you can even register what has happened, the sounds of cheering engulf you and you’re being carried away on the shoulders of your overjoyed mates. You see that you’ve uprooted the stumps and your rival has his head down as he makes his way across the pitch. Exciting, right?
Let’s take a few steps back and look at the crucial moments that lead up to this point. Having already played five matches, you have a fair idea of how your opponent has been performing in the series. You know that he is a big-hitter who lacks foot movement, and any ball pitched farther away from his legs, will only end up reaching the farthest corners of the field. So, with this knowledge in hand, and with the help of various algorithms and statistics to guide you, you know that the best way to tackle the situation is to york him out. And voilà – you’ve used all the information collected on your opponent to strategically understand his strengths and weaknesses. In a nutshell, you have used analytics to beat your opponent.
Well, it isn’t that simple either. With a total of 56 matches and one team averaging 14-17 matches in a season, you can only imagine the sheer amount of data out there. Here are a few fun facts about this amazing franchise that can be derived from this data:
Fun Fact 1
In 2018, Star Sports won the broadcasting rights for IPL for a tenure of 5 years for an eye-watering sum of Rs. 16,347.5 crore. That is Rs. 3269.5 crore per year. This means that every delivery in the IPL will cost the network over Rs. 24 lakhs given every season 56 matches are played and every match is played with each side playing all their 20 overs. (courtesy: sportscounty.com)
Fun Fact 2
Harbhajan Singh has played a total of 160 matches and has bowled 1,249 dot balls. This is the most number of dot balls delivered by any player in the history of this tournament. Lasith Malinga comes second with 1,155 dot balls. (courtesy: sportscounty.com)
Fun Fact 3
Kings XI Punjab is the only team that has changed its captain 11 times in the course of IPL. On the contrary, Chennai Super Kings is the only team whose captain, Thala Mahendra Singh Dhoni has been constant since the first match. (courtesy: thesportsschool.com)
Fun Fact 4
Chris Gayle has the most number of sixes to his name. The West Indian has scored 355 sixes in IPL. He has a whopping tally of 1001 sixes in all T20 competitions, which is 307 sixes more than any other batsman in T20 cricket. Shikhar Dhawan has scored the most number of fours in IPL. The Delhi Capitals Southpaw has dispatched 634 balls to the boundary (courtesy: Howstat)
With the availability of such a herculean amount of data, dedicated analysts can empower a team with the right statistical tools to come up with a perfect strategy. One such analyst I have been following for several years is Pdogg, or Prasanna Agoram, who has been with team South Africa for over a decade now and is even seen frequenting the IPL pitch.
Power of Data Analytics in Cricket
To a cricket lover, Pdogg is hardly a new name. In fact, his videos with all-rounder Ravichandran Ashwin give viewers an idea as to how different combinations of factors, such as a team’s strengths and weaknesses, past performance, and pitch conditions, can determine the outcome of a game.
Below are some examples from Pdogg’s videos that I found fascinating.
1. Taking on Sehwag:
Virender Sehwag is every bowlers’ nightmare. His love for hitting boundaries makes him a formidable opponent – remember the start of almost every match during the 2011 World Cup? He is no stranger to antics either. One time, he called the 12th man just when he was about to bat to ask for the lyrics to a song he had forgotten! That’s just how confident he is of his game. Many players and teams have had a tough time facing Sehwag, however, PDogg was able to work out a strategy for South Africa that proved to be a game-changer.
Normally, in the first few overs of any Test match, the bowler does not have a deep third man. Pdogg, after analyzing Sehwag’s batting patterns, suggested to captain Graeme Smith that he start the innings with a third man. The reasoning behind this was that Sehwag is known to nick a few boundaries to the third man, which gives him the momentum to only up his game from thereon. Though the South African players were unsure of this move, they did employ it, and to their surprise, Sehwag was dismissed at an early stage of the match. How, you ask? A catch to the deep third man, of course! (You can refer to this link for a better picture https://www.youtube.com/watch?v=ccr61kb9I_I)
2. Southpaw’s game goes south
Pdogg proved the benefits of data analysis during the 2011 World Cup too. India had a stellar start to the tournament thanks to Sehwag’s mighty batting, but other members of team India were also in full form back then. Zaheer Khan, the legendary southpaw, was on top of his game, and it was Pdogg who was able to realize that Khan was lethal during death overs. With this nugget of insight in hand, the Proteas were able to force India to bring Khan out much before the death overs, eventually bringing them victory. What’s important to note here is that Khan’s signature move is evaluated not based only on how he is performing today, but after studying long-term behavioral patterns backed by numbers and specifics. A similar analysis was done during the IPL to understand how to take on Sunrisers Hyderabad’s Bhuvaneshwar Kumar. (Check out this link https://www.youtube.com/watch?v=CFILyNPDWXM)
In this way, analysts like Pdogg, are able to not only improve game strategies but also predict match outcomes.
Pre-gaming for an Achilles heel
Pre-match shows are also a great way for enthusiasts to explore the power of data analytics in cricket. Shows like Game Plan, the IPL pre-match show anchored by former New Zealand cricketer and commentator Scott Styris, are especially useful when it comes to gauging what to expect from that day’s play. Game Plan specifically focuses on the players to watch out for in that day’s match, and how best to approach them – different from what Pdogg does, but also a treasure trove of data and knowledge. During one Kolkata Knight Riders match, Styris analyzed West Indies all-rounder Andre Russell’s game. Now, we all know that Russell’s game can be exciting and explosive, much like his teammates’. Styris was able to point out that Russell’s power move is placing his front leg wide, which gives him the right force and stance to generate a massive swing. Styris’ take on how to counter this was to opt for a body line short ball to restrict Russell’s movement, or fuller bowling outside the off-stump (fifth or sixth stump), which is outside his range.
Styris was able to predict that having a deep point will increase the chances of dismissing Russell. The ironic, and amazing, part is that Russell actually implemented Styris’ suggestions while he was bowling, and was able to bag a 5-fer!
No ballpark figures here
Looking at the examples above, whether it’s Pdogg’s real-time analysis or pre-match predictions with Styris, it is clear that the integration of technology into the world of cricket is moving fast, and has a bright future. Today, there are statistics at every level of the game — match outcomes, match type, teams, players, stadiums, toss, weather conditions, etc. The quantity and quality of data that is at our disposal are only growing, providing experts with all the right ingredients to employ data analytics in cricket with full force.
Cricket has always been statistically driven like baseball, but over the past 15 years we have moved beyond comparing averages and now use data to help in strategy and player selection.
– Rahul Dravid, 15th MIT Sloan Sports Analytics Conference
While there still remains some hesitation towards dependency on data in a game, because, let’s face it, cricket is a game that is high on emotions, we cannot undermine its role, nor the role of the analyst who crunches numbers faster than you can say ‘howzat!’.
