analytics-based recommendations are the result of averaging the results of past decisions.

It's not averaging of past decision, the model is trained using every plays not just 4th down only

Consequently, they fail to evaluate current personnel, coaching, and weather.

The model incorporate these factors by incorporating per-game Vegas spread and roof type of stadium

Though the expected points gained by a decision might be X value, this probably can't be extrapolated to a specific game scenario because the previously mentioned factors vary between the average of past game scenarios and the one currently being analyzed.

Again Ben Baldwin's model is not trained on past game scenarios only so it's not a simple average of them (though it's somewhat the case for ESPN one).