Confused? You might be wondering what Criclytics means! Don’t Worry, I will explain what this means and how this is playing a central role in cricket. Cricket is one of the most followed sport in the world and with the 2015 World cup around the corner, the craze is reaching fever pitch. So in this blog I would like to talk about “Criclytics” – Analytics in Cricket.
A single cricket match generates loads of data – in the form of bowling figures and batting figures. If you take the data related to batsmen, it would be number of runs scored, number of balls faced, strike rate, number of four’s and sixes scored, number of runs scored against a particular bowler, strike rate against a particular bowler and so on. If you take the case of a bowler, the data would be number of wickets taken, number of overs bowled, number of runs given, bowling average and so on. Apart from this statistical data there is video data showing how the ball has swung during the initial stages of the game, how the player has responded to a particular delivery etc. This presents a huge opportunity to analyse this data and make meaningful insights which helps in taking correct decisions both on and off the field.
Let’s look at some examples where Criclytics is playing a central role in taking correct decisions. Recently, KKR, an Indian Premier League Franchisee employed Analytics tools during auction process to select the players that fit into the team’s strategy. Every year large sums of money is spent during bidding process to select the players. While lucrative nature of the premier league means that the teams have more money to spend, the competitive nature of the bidding process often push the teams to make the unrealistic and impulsive bids. Analytics tools play an important role in taking guesswork and impulse out of the equation. Teams can now select players by looking their past IPL Performance and analyzing many other dimensions.
This particular analytics tool has helped the KKR team during two phases. During the pre-auction phase it has helped to analyse the individual players along multiple dimensions and during the auction phase, it has acted as a dash board streaming information and visibility of players available for bidding and how the other franchisees fared. KKR previously used multiple sources of cricket data to get the information about these players and that is quite a cumbersome process. With this tool in place, KKR has saved a lot of analysis time and the predictive capabilities of this tool has helped the team choose the best players.
The other application that is gaining significance is WASP, (Win and Score Predictor). WASP predicts the score in the first innings and chasing team’s winning probability in the second innings. By considering various factors such as history of games at that particular venue, weather & pitch conditions, scoring rates, and dismissal probabilities etc, WASP will predict the first innings total and the chasing team’s winning probability. WASP also depends on the match situation. For example, in the T20 cricket matches where New Zealand was playing, it was floundering with winning prediction of 5%. Suddenly, New Zealand cricketer Luke Ronchi scoring a quick 51 runs off 28 balls. With this, the winning probability has risen to 70-80%.
For the last example, I’d like to bring up the case of a cricket team that has employed analytics and has risen to from the bottom to number one ranking in test matches. Any guesses? It’s none other than England. When Andrew Strauss became the England captain, he setup a vision of the team rising to number one in test rankings. Data played a key role in achieving their vision. They analysed the teams they were competing with and analysed opposition team’s strengths and weaknesses through rigorous analysis of their scoring patterns, how they scored their runs, when they were vulnerable during innings. They identified players who had the skills to counter those opponents in different conditions. They made sure that they had a clear plan for each day, each session. Like Ravi Shastri would say, teams played, but data analytics was the winner.
Analytics can be applied only to a certain extent; it can’t be used for all situations. For example, in the champion’s trophy final match between India and England, Dhoni’s decision to bowl Ishant Sharma in the 18th over of the innings has proved to be decisive moment in India’s victory. According to the analysis, he should have gone with either Bhuvaneshwar Kumar or Umesh Yadav. But Dhoni trusted his instinct and gave the ball to Ishant Sharma, the rest as they say is history.
So it is obvious that Analytics can play a decisive role in cricket, but let’s agree that nothing can replace a seasoned player’s instinct. It is just a questions of finding the delicate balance between use of analytics and experience on the field. If used properly, it could be a gold mine, if not it could quickly turn into a land mine.
This blog is authored by Venkat Prasad, Analytics Consultant at BRIDGEi2i
About BRIDGEi2i: BRIDGEi2i provides Business Analytics Solutions to enterprises globally, enabling them to achieve accelerated business impact harnessing the power of data. Our analytics services and technology solutions enable business managers to consume more meaningful information from big data, generate actionable insights from complex business problems and make data driven decisions across pan-enterprise processes to create sustainable business impact. To know more visit www.bridgei2i.com
The views and opinions expressed in this article are those of the author and do not necessarily reflect the official position or viewpoint of BRIDGEi2i.