Game Analytics: Making a play in Cricket

Data and analytics, which might have been unheard off in cricket a few decades ago is now becoming a big back room component amidst all teams. Performance analysts’ have become a regular in-house support staff for international teams and the domestic circuit too is catching up.

No longer are teams satisfied with just a wagon wheel or a colourful graph, they want to gain a head start by analyzing everything there is to know about not just their own players but also scout opponents. Strike rates and averages are not the only parameters anymore, a player’s performance against a particular specialization, his favorite batting position, his performance on a particular pitch/venue are a few microscopic details that are taken into consideration.

Pre-tournament, pre-game, live and post-game data points are all dissected, processed, studied and are modeled into a single entity to get as much as information as possible. Key factors like momentum swings, batting impact and bowling impact of a player are studied in detail to analyze the best combination.

Real time predictive analytical models are constantly built which helps franchises/ teams to derive insights and prepare better. For example, The Win/Loss probability at a particular time of the game, score potential at a particular run rate can all provide key insights.

The toss decision trends are studied to gain a head start before a ball has been bowled. Each ball can provide numerous data points with respect to a team’s momentum and chances of victory. Par score identification can assist teams in picking the right combination- whether to go batsman packed or include more bowlers. Player efficiency across different over slabs can give insights into the batting order or the bowling line-up, and provide teams alternatives for a specific position.

For example, details such as dot ball percentage, time of acceleration, death over strike rate, runs and boundaries conceded, wickets lost, are factors that are studied in depth to assess a team’s momentum, and thereby a player’s impact on the game.

 Off-field factors such as pressure, workload, and dietary habits might have an impact on a player, but with the right statistical backing, a player’s performance efficiency, team composition, and strategies can be extracted.

Data analytics is also playing a key role in engaging with fans in the digital era. Key statistics about a player, or player comparison with engaging insights through a visual medium in the form of video scorecards or infographics will keep the fans hooked on the go.

With 580 players, including 361 Indians registered for the IPL auction taking place on 27th and 28th January and big money on the table, teams are turning to big data to optimize their squad structure and it will be an interesting watch to see who will be the biggest winners in Bengaluru.