Sports Data Analysts
Computer & MathematicalAI exposure
- Data source: BLSPublished: 2026-08
Very high· relative
LowFour relative bandsVery highGroup-level value
Scale, basis and source
Four relative bands (Low / Moderate / High / Very high)
831 detailed occupations in the BLS Employment Projections table. Assigned per National Employment Matrix (NEM) code, so occupations sharing a NEM code carry the same band
- Data source: AnthropicPublished: 2026-03
0.211
0.000Range of values carried here0.745Scale, basis and source
- Data source: ILOPublished: 2025
0.56
0.09Range of values carried here0.70Group-level value
Scale, basis and source
Generative AI exposure index, 0–1 as published
ISCO-08 unit group — every occupation sharing the code gets this value
Computed by this site, not published by the ILO: of the 1,012 occupations this site links to the ILO dataset, 8% score at or above this value.
What kind of figure this source publishes
The BLS category is a relative rank, not an absolute level, and it is not a first-hand measurement: it groups an occupation's percentile ranks across several published studies into four bands. It is not an employment or wage forecast, not a probability of adoption, and it does not separate automation from augmentation.
Task-level exposure
Show 26 hidden tasks| Task | Claude.aiRaw / share % |
|---|---|
Draw conclusions or make predictions based on data summaries or statistical analyses.15-2041 | 0.169513.1 |
Evaluate sources of information to determine any limitations in terms of reliability or usability.15-2041 | 0.162512.6 |
Prepare appropriate formatting to data sets as requested.15-2041 | 0.12389.6 |
Identify relationships and trends in data, as well as any factors that could affect the results of research.15-2041 | 0.09897.7 |
Report results of statistical analyses, including information in the form of graphs, charts, and tables.15-2041 | 0.07575.9 |
Process large amounts of data for statistical modeling and graphic analysis, using computers.15-2041 | 0.07325.7 |
Examine theories, such as those of probability and inference, to discover mathematical bases for new or improved methods of obtaining and evaluating numerical data.15-2041 | 0.06795.3 |
Write detailed analysis plans and descriptions of analyses and findings for research protocols or reports.15-2041 | 0.05904.6 |
Develop an understanding of fields to which statistical methods are to be applied to determine whether methods and results are appropriate.15-2041 | 0.05884.6 |
Read technical literature and participate in continuing education or professional associations to maintain awareness of current database technology and best practices.15-2041 | 0.05864.5 |
Values in this tab are predicted labels, not observations. Eloundou et al. (2023) published two rating regimes — human raters and GPT-4 — and the β shown here is derived from the GPT-4 rater basis alone; the same task can take a different value under the other regime. The unit and the meaning differ from the observed shares (%) in the other tabs, so do not place them on the same axis.
| Task | βE1 + 0.5 × E2 |
|---|---|
Process large amounts of data for statistical modeling and graphic analysis, using computers.O*NET Task ID 8954 | 1.0 |
Prepare data for processing by organizing information, checking for inaccuracies, and adjusting and weighting the raw data.O*NET Task ID 8957 | 1.0 |
Evaluate the statistical methods and procedures used to obtain data to ensure validity, applicability, efficiency, and accuracy.O*NET Task ID 8958 | 1.0 |
Supervise and provide instructions for workers collecting and tabulating data.O*NET Task ID 8963 | 1.0 |
Adapt statistical methods to solve specific problems in many fields, such as economics, biology, and engineering.O*NET Task ID 8965 | 1.0 |
Develop and test experimental designs, sampling techniques, and analytical methods.O*NET Task ID 8966 | 1.0 |
Examine theories, such as those of probability and inference, to discover mathematical bases for new or improved methods of obtaining and evaluating numerical data.O*NET Task ID 8967 | 1.0 |
Develop software applications or programming for statistical modeling and graphic analysis.O*NET Task ID 20193 | 1.0 |
Present statistical and nonstatistical results, using charts, bullets, and graphs, in meetings or conferences to audiences such as clients, peers, and students.O*NET Task ID 20194 | 1.0 |
Determine whether statistical methods are appropriate, based on user needs or research questions of interest.O*NET Task ID 21100 | 1.0 |
β = E1 + 0.5 × E2 · E1 = tasks where direct LLM access alone cuts time by at least 50%, E2 = tasks where software built on top of an LLM cuts time by at least 50%. Values take only 0 / 0.5 / 1.0.
Data sources & licenses — O*NET®, Anthropic Economic Index, Eloundou et al. (2023): see full notices on the Credits page