CRICKET

TVConal uses a completely different approach for match analysis and player comparison based on the individualized, situation-based prognosis. Using TVConal, 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 TVConal are developed to assess how well a player (batsman 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.

We provide ball-by-ball live match score and win predictions based on team squads, match situation, historical performance in similar conditions, venue stats and other metrics. For each partnership in a match, we compute who are the top three bowlers most likely to dismiss the batsmen and break the partnership. We also provide analysis of individual players; Batsman and Bowler Analysis, their expected vs. actual performance in the match.

Provides deep data analytics and graphical visualizations. We have a large variety of stats based on players, teams, venues, match formats, innings, innings section, overs etc,. You can create templates to get answers from specific queries. You can create and organize dashboards for easy access of premade templates. If you do not like raw data, no problem! Mithra has nice graphics for easy understanding of complicated stats. You can have visualizations in the form of bar graph, worm graph, waterfall model, scatter plots etc,.
We are in the process of developing Ask Mithra using which you can get answers to deep stats related questions about cricket.

Allows coaches to store and analyze videos of their players. Coaches can upload training videos of their players, add comments and audio recordings at specific intervals, use drawing canvas to highlight anything in the video and take screenshots.

AutoMeta has video analysis and extraction of data based on several Biomechanical Key Performance Indicators (KPIs). For Bowlers, we have wrist height detection, runup speed and ball speed detection, back foot contact, front foot contact, angle of bowling arm etc,. Among our Batsman KPIs are ball contact height detection, shot type detection, measuring the distance from the stumps, check whether the batsman is balanced or not.