How does Data Science Help Predict Cricket Match Outcomes?
By Meghna Kar
Big data and analytics are no longer a stranger to the world of sports. Sports is another field which relies on data science. It is not just the sportspersons sweating it on the field anymore, data science works equally hard. Its goal is to predict match outcomes and it also helps improve game strategies. The German football team and
famous NBA teams are some of the big names, which rely on analytics to improve their game.
Now, the game of cricket not only generates immense thrill, but also a lot of data. Take into account the figures that come from just batting and bowling. Now think about the data that is related to both, the batsman and the bowler. The insights that are derived from big data, provide the players, fans and the broadcasters with enough background information and predictions to make the correct decisions about the team’s performance.
Let us look at how data science predicts cricket matches today.
1. Readily available information
Data science goes a long way in suggesting optimal strategies for a team to win a match. It also provides sufficient information for a franchise to bid on players. Today, there is an influx of cricket statistics-oriented websites and organizations that provide detailed information on cricket.
International Cricket Council (ICC), for example, uses big data to analyse player data and match tournament data. The Board of Control for Cricket in India (BCCI) acquires this service from Sports Mechanics, a strategic consulting, technology and analytics partner for the global sports ecosystem.
2. Keeps cricket fans engaged
The statistical data related to a single batsman and bowler highlights the wickets left, the way the ball was swung, runs scored per deliveries faced, the way each player responded to the delivery, and so on. This data allows fans to understand the game in depth rather than just looking at the match proceedings.
3. Help captains make the right decisions
Data analytics can help solve the uncertainty attached to a bowler or a batsman’s average performance. What’s critical is to know how they will perform in a given circumstance. Collectively, all of this data has the potential to create vast opportunities to analyse and draw meaningful insights, which then help predict or classify future events. This, in turn, helps captains make the right decisions, on and off the field.
4. Machine learning technique WASP predicts final score
A machine learning technique called Winning and Scoring Prediction (WASP) predicts the final score in the first innings and estimates the chasing team’s probability of winning in the second innings. And it works as a scoring predictor in the first innings of a match. For example, WASP may predict based on its calculations that the team will score 278 at the end of the innings.
In the second innings, it works as a winning predictor. For example, if WASP says 67% during a match's second innings, it means that the chasing team has a 67% chance of winning the match.
5. Deeper analysis of match predictions, performances, and patterns
Researchers have used Google trends to refer to data science for a deeper cricket match analysis. Certain Indian analytics companies like Cricket-21, play a huge role
in data analysis for most global teams.
Opportunities in big data and sports analytics are now even greater than usual. The future of machine learning is bright in the world of cricket. Big data has a vital role to play in decision-making for cricket, based on the available data. People don’t chase cricket anymore. In fact, it is the sport that is running behind fans with data.