Late at night, after his footy games had finished, Kai Bloomfield would sit in a dark room replaying footage, one moment at a time. Every pass, every shot, every turnover had to be tracked manually, building up a picture of what had actually happened beyond the scoreboard. It was slow, repetitive work, the kind that required patience more than anything else, but it was the only way to get real insight into a game.
Most teams never even get that far. Not because it isn’t valuable, but because it takes too long and demands too much effort to maintain. So decisions are made another way, based on instinct, memory, and whatever fragments of the game people can hold onto afterwards.
The insight: most teams don’t have real data
At the professional level, sport looks very different. Every movement is tracked, every action recorded, and entire teams are built around analysing performance. That data shapes how players train, how teams prepare, and how decisions are made.
Outside of that environment, very little of it exists.
Community teams, junior programs, and even semi-professional clubs are largely operating without structured data. Coaches who want deeper insight have to create it themselves, often spending hours coding games manually, and even then ending up with something incomplete. Over time, that gap becomes normalised, even though it limits how much players and teams can actually improve.
Cordelia King, Kai Bloomfield, and Sam Hung had seen this pattern repeatedly through their previous company, Trainstop, where they worked closely with clubs and players navigating recruitment. Teams were asking for better ways to evaluate performance, but without reliable data, there was only so much they could do.
Turning footage into understanding
Superstat was built to make that process easier, but more importantly, to make it possible.
Instead of manually breaking down games, teams can upload their footage and receive a structured view of what actually happened. Player stats, timelines of key events, and patterns across games are all generated automatically, giving coaches something they can use immediately rather than something they have to assemble themselves.
Behind that is a system trained to recognise the elements of a game in motion. It identifies players, tracks the ball, and captures the actions that define how a game unfolds. What used to take hours of manual effort becomes something that runs in the background, allowing teams to focus on interpreting the game rather than recording it.
Built by people who have always looked deeper
For the founders, this wasn’t a new problem. It was something they had each been drawn to long before starting the company.
Kai had always been focused on data, whether that meant tracking his own performance as a kid or later analysing entire sports seasons to predict outcomes. Cordelia approached it through discipline and improvement, using whatever tools she could find to measure progress and refine her performance. Sam had been building products around sport from an early age, creating ways for players to connect and compare how they were performing.
Superstat sits at the intersection of those instincts. It reflects a shared belief that understanding a sports game more deeply leads to better decisions, but that most people haven’t had access to the tools needed to do that consistently.
When it started to click
The shift from idea to something real happened when coaches began using the product in their own workflows. What stood out wasn’t just that it worked, but how quickly it changed how they spent their time. Tasks that had taken entire weekends could now be done automatically, giving coaches the chance to focus on reviewing games rather than documenting them.
That change was small on the surface, but meaningful in practice. It meant the product wasn’t just producing data, it was changing how teams approached the game itself.
What this unlocks
With access to reliable data, the way teams operate begins to shift. Training becomes more focused because it’s based on actual patterns rather than assumptions. Player development becomes easier to track over time, and decisions around selection or strategy become more grounded.
Just as importantly, it changes who can access that level of insight. What was previously limited to elite environments starts to become available to a much broader group of teams and players, many of whom have never had access to structured performance data before.
A different future for team sports
In individual sports, data has already become part of how people train and improve. Runners track their pace, cyclists measure output, and swimmers analyse performance over time. It’s become normal to understand progress through numbers.
Team sports haven’t followed the same path, largely because the data has been too difficult to capture.
Superstat is built on the belief that this will change. Over time, players and coaches will expect to understand their performance in more detail, and that access to that information will become part of the standard experience of playing sport.
Looking ahead
The ambition behind Superstat is straightforward, even if the shift it represents is significant.
If you play a team sport, your games should exist in data. Not just the final score, but everything that led to it.
As that becomes possible, improvement stops being based on memory or guesswork and starts to come from something more consistent. The gap between amateur and professional environments begins to narrow, not because the level of play changes, but because the tools available to understand it do.
The ask
If you coach or play basketball, the team would love to hear from you. You can try it at superstat.com.au
Watch them pitch at Demo Day
When: Thursday, 30 April @ 7:00 PM (pre-party starting at 5 PM)
Where: Carriageworks (at the close of Blackbird's Sunrise Festival)
What: Pitch night (19 companies)
Tickets: Grab your ticket here
