Umpires, Referees, and Other Sports Officials
In short: today's best AI models could do about 15% of this job's working time (projected from METR's April 2026 measurement and Epoch's November 2026 index) if the work were set up for them, and about the same by the end of 2028 if progress keeps its long-run pace. The people and hands-on work, about 85% of the time, stays with people.
Officiate at competitive athletic or sporting events. Detect infractions of rules and decide penalties according to established regulations. Includes all sporting officials, referees, and competition judges.
15,780 people do this job in the US. $40,710 a year.
A typical 40-hour week
Not yet reviewed task by task- AI could take on6 h
- A person checks AI's work0 h
- Desk work AI can't do yet0 h
- Stays with people34 h
Umpires, Referees, and Other Sports Officials, now: of a 40-hour week, AI could take on 6 hours, 0 hours become checking its work, 0 hours are desk work it can't do yet, and 34 hours stay with people.
The largest pieces: Research and study players and teams to anticipate issues that might arise in future engagements (about 4 h); Verify scoring calculations before competition winners are announced (under an hour); Compile scores and other athletic records (under an hour).
Estimates for a typical week of this job, if progress keeps its long-run pace, counting work the best models finish four times in five. Every task is below.
of the working time. Now is projected from METR's April 2026 measurement and Epoch's November 2026 index.
- 15%
- 7%
- 77%
of the work: Anthropic's measure of what people already bring to Claude at work (2025). It counts help with part of a task, so it can be higher than the share within reach.
On the chosen pace and reliability. Estimate.
Share of the working time within reach, now to 2030
Change assumptionsHide assumptionsLong-run pace, four in five
What each choice means: , , , , . Every pace starts from .
At this date and pace, models finish tasks up to 2.4 work days long four times in five.
How far this has come
With GPT-4, measured in March 2023, 0% of this job's working time was within reach at . With Claude 3.7 Sonnet, measured in February 2025, 0%. With Claude Mythos Preview (early), measured in April 2026, 12%. Today's estimate: 15%.
A backcast: today's task data with the best model METR had measured by each date. It shows how fast the models have moved, not what anyone forecast at the time.
Measured use over time
Of the Claude.ai conversations Anthropic sampled and tied to a work task, no reportable share went to this job's tasks in May 2026; 0 of its 16 tasks showed up. Within each of Anthropic's methods, never across a change: none to 0.0019% (released February and March 2025); none to 0.0063% (August 2025 to February 2026).
Each release
| Conversations | Share | Rank | Tasks seen |
|---|---|---|---|
| Released February 2025 | none | n/a | 0 of 16 |
| Released March 2025 | 0.0019% | 675 of 703 | 1 of 16 |
| The week of Aug 4, 2025 (released September 2025) | none | n/a | 0 of 16 |
| The week of Nov 13, 2025 (released January 2026) | 0.0047% | 578 of 672 | 1 of 16 |
| The week of Feb 5, 2026 (released March 2026) | 0.0063% | 552 of 677 | 1 of 16 |
| April 2026 (released June 2026) | none | n/a | 0 of 16 |
| May 2026 (released June 2026) | none | n/a | 0 of 16 |
Measured, not estimated: Anthropic's samples of Claude.ai conversations, each tied by a model to an O*NET task, from the Anthropic Economic Index. It says where Claude's use goes, not how much of this job's working time it covers, so it is not on the same scale as the reach above. The releases differ in their sample, their classifier and the smallest share they report (the June 2026 file rounds each task to a hundredth of a percent, so a smaller task reads as none), which is why a change of method starts a new line. At least 96% of each older release's task-tied use matched this site's tasks, and all of the newest. Claude.ai only, so use through other tools and other companies' models is not in it. Every job ranked.
Robots and the physical work
Anthropic rates 46% of this job's working time as physical work. For 6% of the working time, a robot has been shown doing most of the task somewhere: 6% in a purpose-built cell. 0.06 of 3, the 566th highest of the 923 jobs.
- Not physical 54%
- No robot shown 40%
- In a purpose-built cell 6%
Anthropic's rating, not this site's estimate: Claude Opus 5, searching the web, rated each physical O*NET task by the kind of setting in which a robot it could cite (deployed, sold or demonstrated) does most of the task, weighted by its own estimate of each task's share of the time (What work can robots do?, September 30, 2026, data CC BY 4.0; every job ranked). A robot shown somewhere is not a robot in your building: cost, setup and safety decide that. The share within reach on this page still counts no body work. The robot behind each rated task is under the task below.
The tasks
Sorted by . 16 tasks from .
| Task | Kind | |||
|---|---|---|---|---|
| Officiate at sporting events, games, or competitions, to maintain standards of play and to ensure that game rules are observed.Done more than weekly by most who do it. Robots: no robot shown. Anthropic's rating. | 34% | 2.5 h1.7 h to 3.3 h | Stays with people | |
| Judge performances in sporting competitions to award points, impose scoring penalties, and determine results.Done more than weekly by most who do it. | 17% | 1.7 h50 min to 3.3 h | Stays with people | |
| Keep track of event times, including race times and elapsed time during game segments, starting or stopping play when necessary.Done more than weekly by most who do it. | 14% | 1.3 h25 min to 2.5 h | Stays with people | |
| Research and study players and teams to anticipate issues that might arise in future engagements.Done more than weekly by most who do it. | 10% | 1.7 h50 min to 3.3 h | 100%Half by now | |
| Confer with other sporting officials, coaches, players, and facility managers to provide information, coordinate activities, and discuss problems.Done more than weekly by most who do it. | 6% | 25 min13 min to 50 min | Stays with people | |
| Inspect game sites for compliance with regulations or safety requirements.Done more than weekly by most who do it. Robots: in a purpose-built cell, Spot (AI-powered inspection / Autowalk missions) (Boston Dynamics / Cargill) (deployed). Anthropic's rating. | 3% | 25 min13 min to 50 min | Stays with people | |
| Resolve claims of rule infractions or complaints by participants and assess any necessary penalties, according to regulations.Done several times a day by most who do it. | 3% | 17 min8 min to 38 min | Stays with people | |
| Inspect sporting equipment or examine participants to ensure compliance with event and safety regulations.Done more than weekly by most who do it. Robots: no robot shown. Anthropic's rating. | 3% | 17 min8 min to 38 min | Stays with people | |
| Signal participants or other officials to make them aware of infractions or to otherwise regulate play or competition.Done more than weekly by most who do it. | 2% | 8 min4 min to 17 min | Stays with people | |
| Direct participants to assigned areas, such as starting blocks or penalty areas.Done more than weekly by most who do it. | 2% | 8 min4 min to 17 min | Stays with people | |
| Teach and explain the rules and regulations governing a specific sport.Done more than yearly by most who do it. | 1% | 50 min25 min to 2.5 h | Stays with people | |
| Verify scoring calculations before competition winners are announced.Done more than weekly by most who do it. | 1% | 17 min8 min to 25 min | 100%Half by now |
Within reach, per task: the share of the task's time whose instances are short enough for a model to finish at the chosen date, pace and reliability. Half by: the date half of that time comes within reach.
Jobs that share skills with this one
From O*NET's related occupations. Within reach now and by the end of 2028, long-run pace, four in five.
- Coaches and Scouts33% now, 34% by 2028
- Athletes and Sports Competitors12% now, 12% by 2028
- Amusement and Recreation Attendants16% now, 16% by 2028
- First-Line Supervisors of Entertainment and Recreation Workers, Except Gambling Services27% now, 28% by 2028
- Exercise Trainers and Group Fitness Instructors48% now, 48% by 2028
- First-Line Supervisors of Police and Detectives44% now, 53% by 2028
Where this job works
The industry groups that employ the most of it (BLS, May 2025).
Where the most of these jobs are
The metro areas with the most people in it (BLS, May 2025).
Questions about this job
- How much of the work of Umpires, Referees, and Other Sports Officials is within reach of AI now?
- An estimated 15% of the working time is within reach of AI models now and 15% by the end of 2028, on METR's long-run pace at four in five. Within reach means a model could finish work that long at that reliability. It is not a forecast of jobs lost or of savings.
- Which tasks of Umpires, Referees, and Other Sports Officials come within reach first?
- Weighted by the time each takes, the tasks with the most within reach now (projected from METR's April 2026 measurement and Epoch's November 2026 index) are: Research and study players and teams to anticipate issues that might arise in future engagements (100% of the task's time now); Verify scoring calculations before competition winners are announced (100% of the task's time now); and Compile scores and other athletic records (100% of the task's time now).
- Which tasks of Umpires, Referees, and Other Sports Officials stay with people?
- Tasks that are people work or body work are not counted as within reach at any date. The largest: Officiate at sporting events, games, or competitions, to maintain standards of play and to ensure that game rules are observed; Judge performances in sporting competitions to award points, impose scoring penalties, and determine results; and Keep track of event times, including race times and elapsed time during game segments, starting or stopping play when necessary. Together such tasks are about 85% of the working time.
- Do people already use AI for the work of Umpires, Referees, and Other Sports Officials?
- In the Claude.ai conversations Anthropic sampled for May 2026, no reportable share went to this job's tasks. Anthropic's labor market measure puts the share of the job's tasks seen in real Claude use at work at 0%. These are measures of use, not of how much of the work AI could finish, and they cover Claude only.
- Can robots do the physical work of Umpires, Referees, and Other Sports Officials?
- Anthropic's robot exposure rating (September 2026) finds 46% of the working time is physical work, and that a robot has been shown doing most of the task, somewhere, for 6% of the working time. Its index is 0.06 of 3. One example: Spot (AI-powered inspection / Autowalk missions) for "inspect game sites for compliance with regulations or safety requirements". A robot shown somewhere is not one in every workplace; this site's own estimates still count no physical work as within reach.
- How is this estimated?
- From the 16 tasks O*NET lists for the occupation, each with an estimated length checked against GDPval and a share of the working time, each classed as desk, people or body work, and METR's measurements of how long a task the best AI models can finish, carried forward to the date from the latest, Claude Mythos Preview (early) in April 2026. Data checked November 10, 2026.
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