OffsideFence - Real-time offside feedback for football forwards

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OffsideFence is a satirical sports-tech prototype that imagines real-time offside feedback for football forwards. It uses a plausible computer-vision pipeline—player detection, pitch mapping, tracking, defensive-line estimation, and haptic alerts—to ask where football should draw the line between analysis, assistance, and rule-breaking.

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OffsideFence started from a simple absurd question: what if football players received real-time feedback before drifting offside? At first, it was just a joke about how far sports technology could go. But the more I looked into it, the more interesting the technical boundary became. Player detection, pitch mapping, tracking, and defensive-line estimation are all real computer-vision problems. The strange part is sending that signal directly back to the player through a wearable. So I built OffsideFence as a satirical sports-tech prototype. The goal is not to “fix” football, but to use an exaggerated product idea to ask a serious question: where should the game draw the line between analysis, assistance, and rule-breaking? The launch process also evolved along the way. It began as a funny concept, then turned into a product-style website, then a more complete prototype with pricing, modes, technical architecture, GitHub docs, and a short launch film. The final version tries to balance two things: it should look plausible enough to be taken seriously for a few seconds, then become absurd enough to make people question the direction of AI in sports.

How does the haptic alert actually work during play, since forwards can’t glance at a screen mid-sprint?

Maker

 The alert is intentionally screenless. The idea is that the player should not have to look anywhere mid-sprint.

In the prototype framing, the wearable uses short haptic patterns rather than visual instructions: a light pulse means the forward is approaching the offside line, a stronger double pulse means they have crossed into a high-risk position. The player does not need to read data; they only feel a simple “hold / check your run” signal.

It is closer to a GPS watch vibration or a coaching cue than a dashboard. The important design constraint is that the feedback has to be binary, low-latency, and physically noticeable without becoming distracting.

Of course, that is also where the satire lives: once AI analysis becomes real-time physical feedback, the boundary between coaching, assistance, and rule-breaking gets much harder to define.