Data science
Providing insights across all business areas
CricViz has a market-leading, data-science function which allows us to add significant value to the data collection by our data-collection service. This analysis forms the basis of all the work CricViz does in delivering ‘best-in-class’ products and services to a wide range of partners.
Our data-science team produces a wide range of models including WinViz which helps aid fan engagement for broadcasters to detailed player projection models which form the basis of our work in performance analysis.
The CricViz data science team also work on bespoke proprietary models for various clients across the sports data landscape.
Data science
CLIENTS
Data science is used by partners covering the full breadth of the game.
Three key models
WinViz
- Sophisticated algorithm that projects the expected outcome based on any match situation, informed by the results of every major T20 game ever played
- Based on two identical teams playing on a neutral ground or calibrated on the strength of both sides’ teams and the history of the ground in question
- Translated into a simple win predictor, displayed on digital platforms and on stadium big screens to support fan engagement
Match impact
- White ball model that looks past 'average' and 'strike rate' and evaluates a players performance in the context of the game
- Takes into account the ground conditions as well as game state
- Key evaluation metric used by a wide variety of clients to determine who the key players in a match were
Player ratings
- Model that looks at historical player performance and generates overall player ratings
- Takes into account the quality of opposition as well as accounting for how long ago each performance was
- Powers a significant amount of the player recruitment work done by CricViz
CASE STUDY
Headline to go here
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