← Risk register SOC 27-2023 · reviewed 2026-08-11

Umpires, Referees, and Other Sports Officials

15,780 US workers · median $40,710/yr · Media

EXPOSED

The modal official works youth, high school, and rec leagues part-time — running the field, positioning for sightlines, enforcing rules in real time, and managing angry coaches and parents, none of which a camera rig does. But the single most visible task, judging ball position and boundary calls, is already automated where money exists: Hawk-Eye retired professional tennis line judges, and automated ball-strike systems are entering baseball. Sensors erode the calling function from the top of the sport downward; crowd control, safety decisions, foul intent, and game management stay human because someone physically present must own the call.

10-year outlook: By the mid-2030s, sensor systems will handle most objective calls at professional and top collegiate levels, while human officials remain essential everywhere below that for game control, safety, and enforcing conduct — pay stays modest and the work stays largely part-time.

US employment, 2019–2025-21.6%
20,12015,780 workers

Nearly all of this fall was the 2020 shock. It has been climbing back since.

Median pay $28,550 → $40,710 +14.1% in real terms (nominal +42.6%, less ~25% US inflation over the period)

The job count is not the verdict

This line is counted by the Bureau of Labor Statistics — the one figure on this page that isn't a judgement of ours. Headcount moves on demand, offshoring, demographics and the business cycle, and automation is one term among several, often not the loudest.

So a falling line is not evidence that AI did it, and a rising one is not evidence that it won't. Both happen in this register: some occupations resist automation and shrink anyway, others are highly automatable and keep growing. The marked year is 2020.

BLS projection, 2024–2034

+5.7%

Percentage only. The projection counts a different population from the 15,780 above — it includes self-employed workers, which for this occupation is most of them, so the two headcounts are not comparable.

Growing, and only partly exposed

The BLS expects +5.7% more of these jobs by 2034, and at 54/100 the work is only partly exposed — some tasks are automatable, the core of the job is not. Nothing here is in tension.

Different clocks. The score is what current AI could do to this work today. The projection is how many of these jobs will exist in 2034. Everything between the two — how fast employers actually adopt, whether demand grows in the meantime — is why they can point opposite ways without either being wrong.

~4,600 openings a year on average, including replacing people who leave.

One email if this score changes. Watch as many occupations as you like from the same address — no account, and nothing is sent on a schedule, only when a verdict actually moves.

Also known as — 24 job titles this covers

Titles reported by people doing this work, from the US Department of Labor's O*NET survey. If your job title is here, this page is about your work even though the name doesn't match.

ScorerUmpireClockerMarshalRefereeStarterStewardessTimekeeperHandicapperPit StewardScorekeeperTest ScorerDance CriticDiving JudgePatrol JudgeRace StarterPaddock JudgePlacing JudgeState RefereeBaseball CoachDressage JudgeSoccer RefereeBaseball UmpireClerk of Scales

Score — 54/100 resistance

Holding it up: embodiment (17/20). Weakest point: liability shield (4/20).

Five dimensions, 0–20 each, summed. Higher means more protected. The arithmetic is shown so you can check it: 11 + 17 + 4 + 8 + 14 = 54. · Scored 2026-08-11, and re-examined when evidence accumulates rather than on a schedule.

Task resistance 11/20

Mixed — a routine tier and a judgment tier Ball-tracking and boundary calls — the tasks sensors have already taken in ATP tennis and Triple-A baseball — are a real slice of the job, but the rest of a Friday night game is spotting a horse-collar tackle, deciding whether contact was incidental, restarting play, and ejecting a coach, which is why this lands at 11 rather than 5.

Embodiment 17/20

Hands-on in uncontrolled environments You are on the field for the whole contest, in whatever weather the district scheduled, backpedaling to keep the play in front of you, taking foul balls off the mask, and physically separating players — that is uncontrolled-environment work, and 17 rather than 20 only because the venue is a marked, bounded playing surface with known dimensions.

Liability shield 4/20

No licence, no signature requirement State association registration and a rules-test certification get you assigned to games, but nothing about it is a practice licence: no statute makes you personally liable for a blown call, and a mis-called ejection ends in an association review or a non-renewal, not a suit against you.

Trust premium 8/20

Some relationship component Assigners rehire officials they know will show up and hold a game together, and varsity crews build reputations that get them playoff assignments — but the teams do not choose you, the fans do not want a relationship with you, and an unfamiliar official in the right uniform is accepted, which caps it at 8.

Judgment & accountability 14/20

Exists to be accountable for ambiguous calls Intent on a flagrant foul, whether a pitcher's arm is a safety risk, whether to suspend play for lightning or a head injury, and whether a coach's conduct has crossed into ejection are calls made in seconds with no replay, no consultation, and consequences for a player's health and a team's season — the rulebook frames them but does not decide them.

Confidence: medium · reviewed 2026-08-11 · how scoring works

What this job involves — and which parts are yours

The verdict above describes this occupation as a whole. Almost nobody does the typical version of a job — tick what's actually in your week and see how your own mix sits.

AI already does these at usable quality

These still need a person

Active moats on the surviving side: embodiment, judgment, physical-presence

How to future-proof this job

Where to go deeper on what this job runs on: Toastmasters — public speaking practice at local clubs worldwide low · Coursera — critical thinking and logic, audit free free to audit · Coursera — active listening and communication skills free to audit · Coursera — decision making under uncertainty free to audit · edX — performance measurement and evaluation free to audit · Khan Academy — reading and vocabulary, all levels, free free

All 35 skills ranked by how many jobs they open →

Where this experience transfers — nothing clears the bar

No occupation passed every test: close enough to umpires, referees, and other sports officials on skills and subject matter, at least 10 points more resistant, no big jump in training, no new licence, no pay cut, and not shrinking on its own. That happens for 223 of the 654 occupations here that aren't SAFE, and it is worth stating plainly rather than leaving the section off.

The usual reason is that exposure travels with the skill profile. The jobs most similar to yours tend to be exposed for the same reasons yours is, so the near neighbours don't clear the gap — and the ones that do are a different kind of work, not a transfer of what you already know. Read that as a limit of this method, not a verdict that you're stuck: it only compares whole occupations, and it cannot see specialisation, industry, or anything you'd bring that isn't in a federal skill survey.

Here is that claim on your own job rather than in the abstract. These are the three occupations closest to this one by skill and subject matter — the places the work would most naturally transfer — with what the register scores them:

Models COOKED 31/100 (-23) · 76% overlap
Locker Room, Coatroom, and Dressing Room Attendants EXPOSED 40/100 (-14) · 72% overlap
Substitute Teachers, Short-Term EXPOSED 53/100 (-1) · 71% overlap

That is the whole problem in three lines. The nearest work is not meaningfully safer, so there is no move here that trades a similar skill set for a better verdict. This is not us running out of ideas — it is what the neighbourhood looks like.

What would move this occupation up is the other direction, and on this page it's the more useful one.

What would move this back up — beyond any one person

The moves above are yours to make. This is the other half: what would have to change in the world for the occupation itself to score higher. None of it is in any one person's gift, but it is where the floor actually comes from. Scores here are not a one-way ratchet. Only two of the five dimensions — task resistance and embodiment — track what machines can do. The other three track law, what buyers will pay for, and who is answerable, and those move in both directions, often in response to the same pressure AI creates. If every lever below landed, this occupation would score around 70/100 — SAFE.

5 specific changes that would raise this score
  • already happening task resistance +3

    Task-mix shift is genuinely two-tier: if ball/strike, line, and offside calls are fully sensor-handled (ABS in MLB, Hawk-Eye in tennis/soccer semi-automated offside), the residual job is foul intent, unsportsmanlike conduct, advantage rulings, and game management — none of which have a sensor analogue. Watch for high school associations adopting cheap phone-based line tech while retaining a human for everything else.

  • already happening judgment accountability +3

    Formal assignment of ejection, forfeit, and suspend-the-contest authority to the on-site official under weather/lightning and crowd-violence protocols (NFHS lightning policy already does this in most states), with the association explicitly barring remote or automated override.

  • plausible liability shield +5

    State youth-sports concussion statutes (all 50 states have Lystedt-style laws) being amended to name the game official — not just the coach or trainer — as the person who must remove a player from play and document it, with the official's certification revocable. Some state associations already require officials to stop play for suspected head injury; making it a statutory duty attached to a registered credential is the specific step.

  • plausible liability shield +3

    State athletic association rules requiring a registered, background-checked official of record to sign the game report for any contest whose result affects postseason eligibility or state records — making the human signature the thing that validates the result, regardless of who made the calls.

  • unlikely trust premium +2

    Narrow route only: leagues marketing 'human-judged' divisions is not a real market. The plausible version is parent/athlete pressure after a high-profile automated-call failure leading a state association to keep human final say on subjective calls as a stated policy — a trust premium held by the institution, not paid by the buyer per game.

The limit. Pay and headcount are the binding constraint, not capability: this is a part-time, per-game market where the sensor cost curve determines adoption, and the modal official is already unreplaced at youth level for economic reasons. Liability and accountability gains would raise the score without raising the wage.

These are conditions, not forecasts — what would have to happen, not what will. Specific rules, cases and bills are named so you can go and check whether they exist and where they stand; verify before relying on any of them. Nothing here is legal or financial advice.

Where this work is, and what it pays there

BLS metro figures for 66 areas. The verdict above does not change by city — the rubric judges what the work involves, not where it happens — but pay and headcount do, and the national median hides a very wide range.

Most of these jobs

New York-Newark-Jersey City, NY-NJ 860 —
Los Angeles-Long Beach-Anaheim, CA 550 $51,230 +26%
Chicago-Naperville-Elgin, IL-IN 540 $51,600 +27%
St. Louis, MO-IL 520 $34,360 -16%
Denver-Aurora-Centennial, CO 490 $42,350 +4%
Kansas City, MO-KS 490 $37,650 -8%
Salt Lake City-Murray, UT 450 $31,430 -23%
Provo-Orem-Lehi, UT 420 $29,790 -27%

Best paid

Green Bay, WI 40 $77,670 +91%
Baton Rouge, LA 120 $65,230 +60%
Bismarck, ND 70 $63,920 +57%

Percentages are against this occupation's national median of $40,710. Counts are jobs in that metro, not vacancies. Metros where the BLS suppressed the cell are absent rather than shown as zero.

Who is actually doing this — nobody, on the record

We have no reported case of a named organisation automating this occupation. Not one deployment, not one announcement.

That is worth saying out loud next to a score of 54. The verdict above is about what the work exposes — what current AI could do to these tasks. It is not a claim that anyone has done it. For this occupation those two things have come apart completely: the capability argument is on this page, and the evidence column is empty.

Read that as a gap in the reporting we can see, not proof of absence — the dispatch runs on English-language feeds and misses plenty. If you know of a case, tell us, or add a field report from inside the job.

Quick take — do you do this job?

Has AI actually changed your work? One tap, anonymous, and the running tally is public. Nothing else is asked of you.

Self-reported and unverified — a sentiment signal, not a survey. One response per person per occupation; you can change your answer.

Field reports — what people say has changed

No field reports yet. A written account takes a paragraph rather than a tap, goes to an editor before it appears, and is the one thing on this page the rubric cannot produce on its own.

File a field report

Concrete beats general: a tool that arrived, a task that moved, a headcount decision you watched happen. Don't include anything that identifies you or your employer if that would put you at risk.

Watch this verdict
Kept current

Rather than check back: get the digest and we'll tell you what changed — or watch a single occupation from its own page.