Who can win 2019 cricket world cup?

Before getting to the serious bit of the answer, here’s a slightly different analogy. Every Indian

captain who has led the Indian cricket team after marriage has enjoyed great success. After

marrying, Kapil Dev-led team brought World Cup to India for the first time in 1983. After his

marriage in 2010, MS Dhoni brought the world cup again back to India in 2011. Now Virat Kohli is

married. Do you see where I am going?

Call it superstitious. But the theory is quite interesting, hopeful and fitting.

However, away from this foolery analogy, India is still a favorite to win 2019 cricket world cup. Under

Virat Kohli, the team has been performing exceptionally well in all format. The team is highly

balanced with the right mix of every kind of player. So we can hope Indian team to bring the

prestigious title back home for the third time.

But there are few other teams who stand just as much of the chance to win the tournament. South

Africa and England, too, are playing great. They have a great line-up of new and experienced players.

Other than these, teams like Australia, West Indies, and Sri Lanka can put up a great challenge. But

they wouldn’t win the world cup. Period.

We’re still 16 months away from the tournament. Anything can happen over the course. It’s all the

in the build-up. The better a team is performing in the runner-up to the World Cup, the better would

they perform on the big stage. So, as disappointing as that is, no amount of analysis can predict who

will win 2019 world cup.

India will win.

Cause indian cricketer are playing well.

This is a statistical AI-driven prediction by sportskeeda.com

Classification Methods

In this research, we present two different approaches for our predictive analysis. At first, we present a classifier approach and later we present a neural network approach with hidden layers. Classifier approach would help us identify the pattern whereas neural network would help us identify the weights allocated after training for each feature.

A. Ensemble Classification Approach

The framework of ensemble classifier systems is established by combining numerous basic classifiers together to reduce the variance caused by a single training set and more expressive concept in classification than a single classifier. We utilize the 8 basic classifiers for this study. The number of basic classifiers are selected based on the leave one out fold validation of the training data. Ensemble classifier has proven to be effective for predictive analysis, hence we adopted the same for this research.

B. Neural Network Approach

In this neural network approach, we utilize 12 hidden layers for this study. The number of hidden layers was chosen based on leave one out validation of the training data. Gradient descent back propagation method is utilized.

2015 Cricket World Cup

At first, we validate our approach by estimating the probabilities of winning the World Cup of these 10 teams for the 2015 world cup and match with the actual 2015 world cup results. We estimate the probabilities based on the data collected from 1975-2011 world cups. Despite the 2015 world cup being played among 14 different countries, we focus on the results of these 10 teams. Table 2 lists the probabilities for the 2015 world cup based on both classifier and neural network approaches along with the actual result.
2015 World Cup Results
2015 World Cup Results

2019 Men’s Cricket World Cup

Now, we predict the 2019 world cup results based on the data collected from 1975-2015 world cups. Table 3 presents the probabilities based on the classification approaches based on the data collected until 18th July 2018.
2019 Cricket World Cup Prediction
2019 Cricket World Cup Prediction

Notes

Defending champions Australia gets a relatively lower probability due to their poor performance at England recently. Top 2 contenders for the world cup according to the classifier are England and India. Classifier approach predicts that the England cricket team has the highest probability of winning. This could be because the previous world cups were won by host nations and due to excellent record by their team in last few years at their home ground (world cup location). Meanwhile, the Neural Network approach predicts India and Pakistan as the top two contenders, this could be due to their excellent performance in the ICC champions trophy 2017. Also, India won the champions trophy 2013 and reached the finals in 2017 which happened in England, hence India gets a relatively higher probability by both Neural Network and Classifier approaches. However, their middle order performance is considerably low when compared to England, hence Classifier predicts England as the winner whereas the Neural Network still believes India has higher chances.

Some of the other interesting notes about this research: If Team India plays without Virat Kohli and Rohit Sharma in this upcoming world cup, India's chances of winning the world cup reduces to 2% whereas if South Africa plays with AB de Villiers, their chances go up to 18%.