The rarest role in sports analytics (per Billy Beane) is the translator — someone who deeply understands both quantitative analysis and football coaching, and can convert model outputs into actionable coaching instructions. Raw model outputs (xG, pressure compliance rates, similarity scores) are meaningless to most coaches until they're translated into decisions: "press this player," "take the free kick from here," "this player's value is in receiving under pressure, not space-finding." Without translators, analytical investment doesn't reach the pitch.
The translator function involves: (1) understanding the model well enough to know what it can and can't say; (2) knowing the coach's language and decision framework well enough to present findings in terms they act on; (3) understanding the game well enough to know which findings matter tactically; (4) building the feedback loop so the coach's reactions improve the models. The translator is not a data scientist or a coach — they're a bridge, and the bridge is the bottleneck.
The linguistics of metric naming directly determines adoption. "Expected Goals" and "Walks + Hits per Innings Pitched" tell you what they measure — they succeed. Corsi, Fenwick, PDO (hockey metrics named after people or meaningless acronyms) block adoption regardless of quality because nobody knows what they mean. Proprietary "roll-up grades" (single-number player grades) are the "bane of the professional analyst's existence" — they undermine trust and prevent deeper engagement. The name IS the adoption strategy.