What we did, step by step
From dvw file to match report
Anyone who scouts volleyball works with DataVolley or VolleyMetrics. Every match is scouted into a dvw file: every serve, reception, attack and dig, with player, zone and outcome. DataVolley used to turn that into a readable match report. Many clubs in Belgium and Europe now work with VolleyMetrics, which mostly uses American terminology and does not always show the figures in a friendly way.
That is where Volley Analytics began, a product of Ace's own: a tool that turns a dvw file into a match report and a set report, so that after the match we can look at our figures per player and as a team, visually, the way DataVolley used to show them. That first step is still publicly online at dvwtomatchreport.com: any volleyball team working with VolleyMetrics generates a match or set report from its dvw file there in a few clicks.
Visual analytics: seeing what the figures say
A table full of percentages tells a coach little. Volley Analytics turns it into visual analytics. The set report shows the score progression per set: where the team pulled away and where it let the set slip. The setter's distribution per rotation sits on six courts side by side. And for serve, reception, attack and defence the tool draws the hitting directions on the court, per player or for the whole team, percentages included.
So a coach reads at a glance what a VolleyMetrics analysis hides in numbers: which rotation struggles, where the attack always goes, who carries reception under pressure.
Volleyball scouting: the opponent's patterns and weaknesses
It did not stop there. Volley Analytics now also processes the data from the dvw files to recognise patterns and weaknesses in opponents. The coach uploads the next opponent's scouted matches and filters: per player, per rotation, per set, on serve or on attack. Where does their opposite hit in rotation four? Who gets the ball in reception when it gets tight?
Volleyball scouting remains human work; watching the video is part of it. But laying the figures beside it, with all the filters, makes match preparation a good deal shorter and sharper.
A product of our own, built in Django
Volley Analytics is a web application of our own: Django with PostgreSQL and htmx, hosted on Railway, with its own parser that reads dvw files from DataVolley and VolleyMetrics. Each team sees only its own matches, with separate roles for coach and players, and everything works on a phone too, on the bus to the match.
Because it is our own product, it grows with what the coaches ask for: every feedback round brings new filters and new reports.
In use at Darta Bevo Roeselare and Rembert Torhout Heren
Volley Analytics is used internally today by Darta Bevo Roeselare and Rembert Torhout Heren, for their own matches and for scouting opponents. Wouter Verhelst of Rembert Torhout Heren contributed to several feedback rounds; a few of the most interesting features are in it thanks to him.
Is your club looking for a faster way from the dvw file to match preparation, from match report to scouting? Then let's talk.
