SAFE
The product is a human body competing in real time in front of people who care specifically that it is a human body — there is no screen-work core for AI to eat. Physical performance, in-game reads, and audience connection are the entire job; the only AI-touched pieces are film study, scouting reports, and training-load analytics, which are support functions handled by staff. The real career risks here are injury, roster math, and a national median that hides a brutal pay pyramid — not automation.
Dipped in 2020, then grew past where it started.
Median pay $51,370 → $66,710 +3.9% in real terms
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
+5.5%
Percentage only. The projection counts a different population from the 15,070 above — it includes self-employed workers, which for this occupation is most of them, so the two headcounts are not comparable.
Hard to automate, and growing
The work resists current AI and the BLS projects +5.5% more of these jobs by 2034. Note that safe does not mean well paid — several of the fastest-growing resistant occupations are among the lowest paid on the register.
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.
~2,100 openings a year on average, including replacing people who leave.
BoxerDiverGamerRowerSkierArcherBowlerGolferJockeyPlayerSkaterSurferAthleteCyclistOarsmanPitcherSwimmerHorsemanPugilistSkydiverWrestlerBicyclistCar RacerCricketer
Holding it up: embodiment . Weakest point: liability shield .
Tasks largely resist digitisation Sprinting a 4.4 forty, absorbing contact, and executing a play call under a shot clock cannot be tokenized — the 19 rather than 20 reflects that opponent-tendency film review and periodized training plans, which used to be your own homework, now arrive pre-chewed from an analytics department.
Hands-on in uncontrolled environments The job is performed in stadiums, on ice, in mud, in heat, against opponents actively trying to physically stop you — there is no version of this executed remotely, and injury risk is an occupational condition rather than an exception.
No licence, no signature requirement There is no licence to compete; league eligibility, a contract, and a drug-testing consent form are the gate, and a team can waive you Tuesday morning with no credential to fall back on.
Meaningful discretion You own live reads — when to shoot, when to concede the bunt, when to say the hamstring is done — but coaching staffs set the game plan, playbooks constrain the option set, and consequences of a bad call are a loss rather than someone's ruin, which caps this well below the licensed-professional tier.
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.
Your task mix speaks to task resistance (19/20 here) — how much of the day's work current AI already does. That is the dimension the boxes above are about.
It cannot move the other three. Liability shield (2/20) is whether the law requires a licensed human to sign. Trust premium (18/20) is whether buyers specifically pay for a person. Judgment and accountability (12/20) is whether the role exists to own consequential calls. Those are facts about the occupation's standing, not about which tasks are in your week — a paralegal who does only trial exhibits still holds no licence. Together they are 32 of this occupation's 71 points (45%).
Embodiment (20/20) is also a property of the work rather than the worker, but we don't tag individual tasks as physical or not, so the picker can't tell you anything about it. That's a limit of this tool, not a claim.
Did we get the list right? Tell us what's missing — the tasks are written from the outside, and you're reading this from the inside.
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 79/100, still SAFE.
Expanded on-field decision authority as officiating and coaching are partly automated: if automated ball-strike systems and AI play-call suggestion tools shift the remaining discretionary calls to players (e.g. MLB's ABS challenge system giving batters/catchers the challenge right, 2025 spring training and planned 2026 rollout), the athlete personally owns consequential ambiguous calls rather than the bench.
League/union rules that formally bar synthetic or AI-generated athlete likenesses from substituting for live competition or broadcast content — e.g. NIL and digital-replica clauses of the type SAG-AFTRA won in 2023 being written into NFLPA/NBPA/MLBPA CBAs, plus state digital-replica statutes (Tennessee ELVIS Act, California AB 1836) applied to athlete likeness. This locks the paying audience to the physical human and monetizes it.
Anti-doping and integrity regimes that place personal, non-delegable liability on the competitor — WADA strict liability already does this, and any expansion of sports-betting integrity rules imposing personal licensure on athletes (as several state gaming commissions license participants) would make the individual a legally named, sanctionable signer.
The limit. Already 71/100 with task_resistance and embodiment near max; there is almost no headroom on the capability side and liability_shield will never behave like a professional license — the binding career risk is the pay pyramid and injury, which no dimension here scores.
| Phoenix-Mesa-Chandler, AZ | 870 | $50,070 -25% |
| Dallas-Fort Worth-Arlington, TX | 740 | — |
| New York-Newark-Jersey City, NY-NJ | 560 | $100,130 +50% |
| Houston-Pasadena-The Woodlands, TX | 510 | $75,550 +13% |
| Tampa-St. Petersburg-Clearwater, FL | 350 | $76,860 +15% |
| Kansas City, MO-KS | 330 | $78,790 +18% |
| St. Louis, MO-IL | 320 | $203,390 +205% |
| Chicago-Naperville-Elgin, IL-IN | 290 | — |
| St. Louis, MO-IL | 320 | $203,390 +205% |
| Las Vegas-Henderson-North Las Vegas, NV | 140 | $124,130 +86% |
| Salt Lake City-Murray, UT | 240 | $123,140 +85% |
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 71. 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.
Has AI actually changed your work? One tap, anonymous, and the running tally is public. Nothing else is asked of you.
Rather than check back: get the digest and we'll tell you what changed — or watch a single occupation from its own page.