TVConal is driven by passion for solving the most challenging problems in television industry on viewer engagement. The progressing digitization of television viewing activities has revolutionized television industry. At TVConal we provide a foundation for building automation in deeper and more compelling content generation by gaining insights into viewers’ behavior and preferences. Machine learning and big data technologies assist us in unlocking the value from the data already existed and rapidly accumulated over time from heterogeneous sources including second screens and social media.

Our Solutions

TVConal supplies the technological resources and solutions that enables broadcasters, media, and entertainment companies to deliver more engaging content and better identify and seize new opportunities. We assist our clients in evaluating the way a program or a show is received or providing insights about interests for a new one. Our services include consulting, analyzing, and data visualization.

Sports Analytics

Our sports analytics solutions span a wide array of applications in modeling players’ behaviors, real-time predictions, game strategies and in-depth game understanding, and detection of important in-game events. We use right intelligence to obtain non-intuitive insights from the massive volume of statistics and raw information that are generated through cutting edge technologies in sports from ball tracking and player tracking to wearable sensors in players’ shoes and helmets. We develop data-driven prognostics using pattern recognition and machine learning to detect the most interesting and the most engaging content in a sport match.



Our mission is to let sports viewers enjoy watching a game in the depth they desire.

CASE STUDY

CRICKET PROGNOSTIC SYSTEM

CPS uses a completely different approach for match analysis and player comparison based on the individualized, situation-based prognosis. Using CPS one can predict more than the probability of victory for a team in a match. Prognoses can be made about several nested layers of parameters. Predictive models in CPS are developed to assess how well a player (batter or bowler) is likely to perform in a given situation with respect to an opponent team, an opponent player, in a specific partnership, and at a particular ground and time.

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1 Changi North Street 1,
Lobby 1, #02-02
Singapore 498789
+(65) 83596478
+(65) 6542 9108
 
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