It's less about pure random chance, and more about our uncertainty. Compare it to a weather forecast that says there's a 10% chance of rain tomorrow. In the same way that weather forecasts get better over time (better atmospheric measurements, more sophisticated computer models), we could potentially do more to measure what the outcome of the election will be. And it might be theoretically possible (albeit highly unrealistic) to predict it with complete accuracy, given enough data. But we're not in that situation, hence uncertainty.

(There are a couple of caveats about election forecasting as opposed to weather forecasting. The first is the "October surprise," a sudden revelation that changes the election. This cycle, it was arguably Trump's covid diagnosis, although that tended if anything to push the results further in the direction they seemed to be going on their own, rather than upset any trend. The second is that, unlike with weather systems, measuring voter behavior (and widespread reporting on these measures) can change people's behavior. The effect of this is hotly contested, but one of the many explanations of Trump's victory in 2016 which hinged on turnout in a few key states is that those states were predicted wins for Clinton, so Clinton voters didn't bother voting. Despite occasional jokes to the contrary, it doesn't rain just to spite the weatherman.)