Love Data, Crazy About Cricket? Introduced by: Alan Herron Presented by: Swathi Yellajosyula & Suddhasheel Bhattacharya

Love Analytics, Crazy About Cricket?

Love Analytics, Crazy About Cricket?

Let Analytics do the Betting for you! One of the most widely viewed sporting events across the world, the World Cup is scheduled to be hosted between 30 May to 14 July 2019 10 Teams 11 Venues 48 Matches 6 Weeks Let Analytics do the Betting for you! A tool that uses historical performance analysis of all the ten participating teams to offer exploratory predictions about the outcome of each of the ODI matches

Capability Overview Batting Statistics Player Statistics Playoff Prediction Bowling Statistics Scoring Model The world cup predictor can evolve with addition of more contextual data as the tournament progresses Result prediction- Playoff

Batting Statistics Strike Rate Prediction Batting Index Forecast Batsman 360 This feature lets users explore the batting performance of a selected team Users can create custom graphs to read into the data easily by using axis selectors The tool takes into account batting statistics of each player in a selected team to predict the average strike rate & performance score for the team A batting index of the team can also be generated that ranks teams on their batting performance over a specified period of time in the past four years

Wicket Strike Rate Trend Bowling Statistics Performance Trends Wicket Strike Rate Trend Bowler 360 The tool takes into account, the bowling statistics of each individual player in a selected team to gain a view over individual & average strike rate performance of the team. Key metrics such as Wicket strike rate trend & The projected performance trend of the selected team can be compared with the opposition team’s projected performance through custom visualizations by using axis selectors

Batting & Bowling Economy Player Statistics Impact Analysis Player Impact Index Batting & Bowling Economy This feature lets users calculate a performance score for each player of the team based on their past performances Users can create custom graphs to read into the data easily by using axis selectors The tool takes into account batting & bowling statistics of each player to predict the average strike rate at which a particular player can be predicted to perform in the upcoming matches: Batting averages per wicket Batting strike rates Bowling average & wicket strike rate

Scoring Model Top Performer Listing Individual Score Match by Match Prediction Individual Score Index Batting/Bowler Form This model is developed based on the historical data collected for the 10 participating teams over the last four years (Afghanistan, Australia, Bangladesh, England, India, New Zealand, Pakistan, South Africa, Sri Lanka, and West Indies) To train our model, we utilize the data collected from all the individual players portfolios in the ten teams to compare & adjust performance ratings based on the quality of the opposition players

Match by Match Prediction Winning Probability Prediction Prediction during Warm Up Matches India England New Zealand South Africa 64% Precision in Predicting Outcomes For a given match, the model sums up the total score of the top eleven players in each team, and the resulting win probability of a team is proportional to its total score Top batsman, top bowler The team with the higher win probability is the predicted winner of that match As the tournament proceeds, the win probability of each team remaining in the competition is adjusted according to the performance

Top Contributor Prediction Top Contributors from Team A Top Contributors from Team B 3 out of 5 accurate top contributor predictions For a given match, the model sums up the total score of the top eleven players in each team, and the resulting win probability of a team is proportional to its total score Top batsman, top bowler The team with the higher win probability is the predicted winner of that match As the tournament proceeds, the win probability of each team remaining in the competition is adjusted according to the performance