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| CricViz | |
|---|---|
| Name | CricViz |
| Type | Private |
| Industry | Sports analytics |
| Founded | 2014 |
| Headquarters | London, United Kingdom |
| Products | Analytical models, match projections, databases, broadcast graphics |
| Services | Data feeds, consultancy, live match insights, media production |
CricViz is a sports analytics company focused on professional cricket statistics, predictive models, and broadcast analytics. Founded in the mid-2010s, it supplies real-time data, probability models, and editorial commentary used by broadcasters, franchises, and national boards. Its outputs inform match commentary, strategic decision-making for teams, and fan-facing visualisations across domestic leagues and international tournaments.
CricViz was established amid a growing market for sports analytics alongside firms such as Opta Sports, Stats Perform, ESPNcricinfo, FiveThirtyEight, and IBM's sports initiatives. Early collaborators included media outlets like Sky Sports, BT Sport, and Channel 4 which sought enhanced match graphics similar to innovations by BBC Sport and Sky News. As Twenty20 competitions like the Indian Premier League and the Big Bash League expanded, demand from franchises such as Mumbai Indians, Chennai Super Kings, and Sydney Sixers increased. Partnerships with cricket boards including the England and Wales Cricket Board, Cricket Australia, and Board of Control for Cricket in India reflected a wider trend following major events such as the ICC Cricket World Cup and the ICC T20 World Cup. Growth paralleled developments in data science driven by institutions like University of Cambridge, Imperial College London, and companies such as Google and Microsoft exploring machine learning for sport.
CricViz offers live probability models used on broadcasts by Sky Sports Cricket, BT Sport Cricket, and streaming platforms linked to organisations like Willow TV and Hotstar. It provides editorial products for publications including The Guardian, The Telegraph, The Times, ESPN and BBC Sport. Franchises in leagues such as the IPL, Big Bash League, Caribbean Premier League, and Pakistan Super League use its consultancy alongside performance tools used by national teams from England cricket team, Australia national cricket team, India national cricket team, and West Indies cricket team. Its product suite is comparable to analytics offerings from Hawk-Eye Innovations, SportVU, and Catapult Sports, with specialised outputs for tournaments like the County Championship and Ranji Trophy.
The company employs probabilistic forecasting, ball-by-ball modelling, and expected value metrics similar in ambition to work by Nate Silver's projects and analysts at FiveThirtyEight. Data sources include official scoring feeds from competitions managed by organisations such as the International Cricket Council, broadcast tracking systems like Hawk-Eye, and scorers accredited by bodies like the Marylebone Cricket Club and national associations. Techniques draw on machine learning methods common in research from Stanford University, Massachusetts Institute of Technology, and industry practice at Amazon Web Services and Google Cloud Platform for feature engineering, time-series analysis, and ensemble modelling. Metrics produced parallel constructs used in sabermetrics-style research originating with the Baseball Prospectus and apply Bayesian updating akin to methods used by Alan Turing's statistical approaches—historically reflected in work at University of Oxford and University College London.
CricViz analytics have influenced commentary formats on outlets including Sky Sports, Channel 4, and BBC Radio 5 Live while informing tactical choices by captains such as those leading England cricket team and New Zealand national cricket team. Broadcast enhancements echo innovations pioneered by NFL and NBA coverage from networks like ESPN and Sky Sports in using real-time win probability charts and wagon wheels. Teams use projections during match strategy sessions in the manner of decision-making frameworks seen in Moneyball-era Oakland Athletics approaches, and coaching staffs with origins in institutions like National Cricket Academy and High Performance Centres integrate these outputs into selection and planning. The influence extends to fantasy sport operators and betting markets regulated by authorities such as the Gambling Commission and platforms comparable to DraftKings.
Public-facing collaborations include media partners like Sky Sports, The Guardian, ESPNcricinfo, and streaming platforms associated with Star Sports and Disney+ Hotstar. Commercial and sporting clients have included franchises from the Indian Premier League, national boards such as the England and Wales Cricket Board and Cricket South Africa, and tournament organisers for the ICC Cricket World Cup and The Hundred. Technology and data integrations have involved vendors and partners like Hawk-Eye Innovations, AWS, Microsoft Azure, and production houses engaged with broadcasters such as Endemol Shine and IMG.
Analytics pipelines leverage cloud computing platforms such as Amazon Web Services and Microsoft Azure for scalable storage and processing, with containerisation practices informed by tools from Docker and orchestration via Kubernetes. Data visualisation and broadcast graphics align with workflows used by Chyron and real-time systems employed by Hawk-Eye for ball-tracking. Model development uses libraries and tooling popularised by contributors at Google Research, OpenAI, and academic groups at Carnegie Mellon University for machine learning, while deployment and CI/CD follow patterns in engineering organisations such as Atlassian and GitHub.
Reception from journalists at outlets like The Telegraph and analysts at ESPNcricinfo has been largely positive for enhancing fan engagement and editorial depth, with commentators referencing parallels to analytics revolutions chronicled in works about Bill James and Michael Lewis's Moneyball. Criticisms echo debates in sport analytics communities, with sceptics at organisations such as Marylebone Cricket Club and commentators on BBC Sport asking about model transparency, data ownership, and ethical use similar to controversies involving Facebook and Cambridge Analytica over data practices. Academic critiques from faculties at University of Melbourne and University of Cape Town raise methodological concerns familiar from statistical discourse in journals associated with Royal Statistical Society and debates in conferences like NeurIPS.
Category:Sports analytics companies