Data visualization has become an important tool of finding an insight of any activities. The main objective of our project is to visualize the cricket data, not a prediction modeling system. Cricket is one of the most popular sports and analytics is imperative.
Many steps are involved in the process of implementing our project: Scribbling ideas, designing architecture, mockups, wire framing, brainstorming about analytics, frontend, backend database, parsing data, and, mostly, connection with testing rigorously. As, we focused on three domains of cricket- match, player, and team, our project will provide the following information-
• List of all the cricketing nations, highlighted in a world map.
• For each team in a particular year:
o Runs scored in every 10 overs.
o Runs scored in each partnership.
o A table reflecting the run scored by the batsmen.
o Bowling performance- how many boundaries, dot balls, extras, 1s or 2s are conceded successively.
• Suppose, team A and B are two cricketing nation who have played a lot of matches since their debut. For each team, the analytics will be:
o Over an interval of 10 overs, the runs of each batsman corresponding to the span of overs they played.
o For each partnership (1-10), runs scored by the couple individually.
o Rate of the increase in runs throughout the match of team A and B.
o Over an interval of 10 overs, the runs conceded by each bowler corresponding to the span of overs they bowled.
o Number of spells, boundaries conceded, wickets taken, extras, dot balls of every bowler.
• For every player:
o Runs scored against number of balls played.
o Number of times played in each position with batting average.
o Run concede, no of spells, wickets taken.
Our project is developed in MEAN stack, using a full stack approach, with the usage of a collection of tools required for web application development such as git, bower etc. Most of them are explained in our report. Hopefully, you will be able to comprehend from it.