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Science Untangled is a suite of online data analysis applications focused on volleyball, built for local clubs, professional teams, national teams, scouts, and competition organizers. It is not a general-purpose SEO or marketing tool, but a sports analytics product whose core value lies in turning volleyball scouting files into statistical reports, heatmaps, video analysis, and tactical insights.
Its feature set is fairly comprehensive: DataVolley/VBStats file validation, interactive data exploration, attack charts, blocking analysis, setter choices, passing distribution, defensive analysis, team matchups, PDF reports for indoor and beach volleyball teams, match simulations, live predictions, match planning, league leaderboards, and more. Data mainly comes from users’ own files, with support for .dvw and .vsm files and partial support for VBStats .psvb files. The documentation clearly notes that analysis results can be affected by errors in the input files and differences in scouting habits, so it is better suited to teams that already have a standardized data collection workflow.
Most applications allow free upload and use of a single file. To perform more valuable analysis across a collection of multiple matches, a subscription is required. The single-user plan costs AUD 12/month and does not include video storage. AUD 24/month provides one main user plus three read-only sub-accounts and 25GB of video storage. AUD 40/month provides 15 sub-accounts and 100GB of storage. A 21-day free trial is available on request. Payment is monthly by credit card and can be canceled; annual payment or other arrangements may also be negotiated.
The strengths are its deep focus on a vertical use case, covering the full workflow from data validation, analysis, and video to reporting and developer APIs. Pricing is relatively friendly compared with professional sports software. It also provides the openvolley R package, pydatavolley, and APIs, making it easier for technical teams to extend. The downsides are that the platform does not provide ready-made data, so users must bring their own match files; multi-file analysis requires a paid plan; the single-user plan has no video storage; and accessing sensitive video via links carries some risk.
It is suitable for volleyball analysts, coaching staff, clubs, league organizers, and developers who want to build custom analysis with R/Python. The text does not state how well it works from China. Payment appears to be mainly by credit card, and it is unclear whether domestic Chinese cards or localized invoices are supported. Alternative or complementary tools include DataVolley, VolleyStation, VBStats, and the openvolley ecosystem.
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