How are AI and Data Analytics revolutionizing Cricket?

“In India, cricket isn’t just a sport, it is a religion” - Steve Waugh, celebrated Australian cricketer.

 

To call cricket the nation’s favorite pastime might be doing a disservice to the sport. When the IPL season rolls over the DNA of entire cities is transformed overnight as a loyal fanbase, both young and old, gear up for another cricketing extravaganza. 

But, behind the glitz and glamor and the phenomenal performances of cricketers, lied the underrated efforts of an army of data analysts and scientists, These professionals crunch large volumes of data to derive valuable insights that can give their team the competitive advantage in winning the trophy. 

 

 

Data Analytics in Cricket

 

The inclusion of technology in cricket has revolutionized the way sport is played professionally. Data analytics has permeated every facet of decision-making in cricket, and for good reason. When the Chennai Super Kings (CSK) squad for the 2021 season was announced, it was met with ridicule. Dubbed the ‘daddy’s army’, the average age of a CSK player was 30. 

 

Analyzing the data of the players tells us that CSK is supported by the strong opening partnership of Raydu and Shane Watson, utilizing the experience of Harbhajan and Ashwin, and the individual brilliance of captain cool himself. Everything except the last is due to Dhoni, the coaching staff, and the ownership team being presented with actionable intelligence derived from the analysis of prior match performances. 

It is telling that CSK has won more matches in the death-overs (19-20th over) winning 28 of their 49 games. A play that requires a squad with experience in dealing with high-pressure chases. 

 

Implementation of data analytics in cricket also had a hand in the victory of Kolkata Knight Riders (KKR) in 2014. The team had partnered with SAP HANA-based analytical platforms to gain a competitive edge over the other teams in the IPL. 

 

How have advances in technology affected the game of cricket? 

 

Data is the fuel that runs cricket analytics. And with years of compiled statistics easily accessible, data analysts can generate reports that can help quantitatively and qualitatively change the performance of an athlete. 

 

A cricket analyst runs the pertinent data through machine learning algorithms gleaning match-winning advantages against the competition. Below are some responsibilities of a cricket analyst:

1. Understand the success rate of a team chasing a score depending on the stadium. Reference
2. Help franchisees develop a strong title-contending team by ranking the best performing players.

 

Observations:
Cris Gayle is the player who won the most player of the match awards and hence is the most valuable player.
Six Indian players have figured in the top ten IPL players list.

Reference credits

 

1. Understand the relation between winning the toss and victory in this match. 
2. Use data visualization to convert their data-driven insights for the better decision-making of other stakeholders like team owners, management, coaches, etc

For example, IPL teams running on a shoe-string budget will want to have the most bang for their buck. This was the case with the title-winning Rajasthan Royals in 2008 who had an investment of just US$ 65 Million from their parent company, emerging media-led consortium. The champions only had one A-list player in the form of Shane Warne and a seasoned player like Mohammed Kaif who was contracted for US$ 675,000. 

Compared to the star-studded line-ups from Chennai Super Kings who had M.S.Dhoni at the helm and Mumbai Indians who were being led by Sachin Tendulkar, Rajasthan Royals did not seem like a team that could win matches let alone the entire championship.

However, on the 1st of June 2008, this Rajasthan Royal’s team etched their place in history. Becoming the first winners of the IPL trophy. 

 

Predictive analysis and better statistics 

Every ball bowled in cricket comes with countless variables; some that can be measured, and others that are not directly observable. A few among many measurable variables in cricket matches include the speed of the ball, the swing, the angle of attack of the batsman, and the pitch conditions, to name a few. Websites like EspnCricinfo and Cricviz clean this data and present it in a visually appealing format to the viewer. 

In the 2015 cricket world cup, ICC partnered with SAP Hana-based predictive analytics tools to provide fans with engaging statistics that kept them more invested in the game. In the 2019 cricket world cup, a predictive analysis model that was trained with data from 1987 came to the conclusion that the 2019 world cup will be won by England which indeed became a reality.  

 

Creating the perfect cricket team

Fantasy leagues are online games where users create their perfect roster of players. A common fixture in the international football scene, fantasy cricket leagues are gaining traction among cricket fans in India. Utilizing the raw processing power of machine learning algorithms and data from across competition, data analysts have conceived winning teams from scratch. For instance, deploying artificial intelligence in cricket has enabled data analysts to understand that KL Rahul is effective in creating partnerships, or that he performs consistently better at the IS Bindra stadium with an average of 49.78. 

 

Can data analysis predict the outcome of matches?

Ishan Kishan had the highest bid in the IPL 2022 with Mumbai Indians contracting him for 15.25 crores. His price was based on his average performance over the last two years where he had a strike rate of 155.50 in just 13 innings. But the most valuable player last season was Jos Buttler of Rajasthan Royals who had a strike rate of 149.05. He also has the second-highest IPL total of all time at 863.

Data analysis in cricket can only provide probable scenarios that might work out in ideal conditions, it takes experience and the player's intuition on-field to convert these numbers into victory.

For instance, during M.S.Dhoni’s captaincy of CSK during the 2021 season, although served with data visualizations of players who could help him win the IPL, his intuition made him play spinners in the death overs. 

It was the same intuition that led to Harbhajan not bowling a single ball even though he was in the playing XI during CSK’s 2018 playoffs against Sunrisers Hyderabad.

 

Cricket analysis and you

 

Every aspiring data scientist needs to work on multiple data sets to improve their understanding of the code and to generate engaging visualizations. Cleaning and transforming data is a tedious task that yields gratifying results in the end.  Those who are keen on pursuing a career in data analysis and science should have an eye for detail and lots of patience. 

 

Cricket is one of the few sports with mountains of data available for mining and extraction. For example, you can write a program that is completely out of left-field, like calculating the inherent factors behind India’s wins whenever Dada was explicit in his celebration.

 

Starting a career as a sports analyst will allow you to work with top IPL teams like Rajasthan Royals or the Chennai Super Kings as well as upcoming teams like the Gujarat Titans. You could crawl through datasheets of matches from 2008-to-2022 to find a strategy that hasn’t been tried before or you could find a rare gem of a player Deepak Hooda. 

 

When you start your career as a data analyst in cricket you will have to present your visualizations to the owners of franchises. An underrated skill that every data analyst should have is the ability to communicate ideas with clarity and conviction. Your insight should inspire stakeholders like the CEOs and team management to make informed decisions when it comes to signing a new player or changing the rotation of the current players in the team.

 

Skill-Lync’s programs in Data Science have been designed to train you in skills that will help you start your career as a sports analyst in cricket. Our 24-week PG program will train you in cutting-edge tools like Power BI, SQL, Tableau, Python, and MS Excel. Students should know their way around MS Excel, which remains the gold standard in data visualization and data analysis. This is the reason why we have dedicated an entire module for you to train in this versatile program. Moreover, our 10 projects will give you hands-on experience in real-life problems you would need to tackle as a data analyst.

 

The start of T20 transformed the identity of cricket and brought data to the forefront. Data helps decide everything from team composition to shot selection and there is an ever-increasing demand for data scientists and data analysts. 

 

Working with your favorite sports team is not just a dream come true, but is a lucrative career option as well. Data scientists and data analysts in cricket earn an average of INR 10 lakhs per annum. This will increase based on the experience under your belt and the unique solutions that you can present to the stakeholders. 

 

A career in sports analytics, with adequate experience in simulated real-life projects, will be rewarding and help you chart new courses in your personal and professional life.