Flight Delay & Cancellation Data
Buy and sell flight delay & cancellation data data. On-time performance, delay causes, and cancellation patterns — the airline reliability data travelers want.
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Find Me This Data →Overview
What Is Flight Delay & Cancellation Data?
Flight delay and cancellation data captures operational performance metrics for domestic airlines, including on-time arrival rates, delay causes, and cancellation patterns. This dataset tracks arriving flights, delays exceeding 15 minutes, cancellations, and diversions across U.S. airports by carrier, with breakdowns of delay attribution to carriers, weather, the National Airspace System (NAS), security, and late aircraft arrivals. The data serves researchers, data scientists, and aviation professionals seeking to understand operational challenges, identify performance trends, and analyze factors contributing to aviation industry reliability. Datasets typically span multiple years of historical records, enabling time-series analysis and comparative benchmarking across carriers and airports.
Market Data
August 2013 – August 2023 (10 years)
Historical Coverage
Source: Kaggle
78.1%
2024 Industry On-Time Rate
Source: U.S. Department of Transportation
0.7% of scheduled flights
December 2024 Cancellation Rate
Source: U.S. Department of Transportation
$33 billion
Annual Delay Cost (2019 estimate)
Source: Airlines For America
$100.76 per minute
Aircraft Block Time Cost (2024)
Source: Airlines For America
Who Uses This Data
What AI models do with it.do with it.
Airline Operations & Planning
Airlines analyze delay causes and on-time performance by carrier, airport, and time period to optimize scheduling, allocate resources, and benchmark against competitors.
Route & Network Analysis
Operations teams identify high-delay corridors and airports to prioritize infrastructure improvements, crew scheduling, and aircraft positioning strategies.
Regulatory & Policy Research
Government agencies and transportation researchers use delay data to assess system capacity, justify infrastructure investments, and evaluate ATC modernization impacts.
Travel & Consumer Applications
Travel platforms and consumer-facing apps leverage reliability metrics to show passengers carrier on-time performance, delay risk, and cancellation likelihood for informed booking decisions.
Pricing depends on the proposed terms
We do not have a verified, comparable price for your dataset. Consider the permitted uses, license term, exclusivity, provenance, coverage and quality. A seller asking price is a proposal, not an appraisal or guaranteed sale. Compare prices only when the source, date, currency, unit and license scope are known.
What Buyers Expect
What makes it valuable.valuable.
Comprehensive Delay Attribution
Granular breakdown of delays by cause: carrier, weather, NAS, security, and late aircraft arrival. Buyers need to isolate controllable factors from external variables.
Carrier & Airport Coverage
Data must include carrier codes, names, and airport identifiers with consistent naming conventions to enable multi-dimensional analysis and benchmarking.
Flight-Level & Aggregate Metrics
Combination of individual flight records and summarized metrics (arrival counts, delay counts, cancellation counts, diversions) for flexibility in analysis scope and granularity.
Timeliness & Historical Depth
Regular updates to support current operational decision-making, with sufficient historical archive (minimum 2–3 years) for trend analysis and seasonal pattern detection.
Potential applications and organizations
Who's buying.buying.
Internal operations teams conduct delay analysis, cost attribution, and route performance reviews to optimize scheduling and customer experience.
Integrate on-time performance and cancellation rates into search results and customer-facing reliability indicators to influence booking decisions.
Monitor system-wide delay trends, assess infrastructure adequacy, and justify capacity and ATC modernization investments.
Layer delay data with cost models and operational benchmarks to deliver strategic insights to airlines, airports, and government clients.
FAQ
Common questions.questions.
What time period does typical flight delay data cover?
Public datasets commonly span 5–10 years. For example, available Kaggle datasets cover August 2013 through August 2023. More recent commercial feeds may offer rolling monthly or weekly updates to track current operational performance.
How is delay cause classified in this data?
Delays are attributed to five categories: carrier (controllable factors), weather, National Airspace System (NAS) congestion, security, and late aircraft arrival. This breakdown allows buyers to distinguish airline-controlled issues from external factors.
What is the difference between cancellations and diversions in airline data?
Cancellations occur when a flight does not operate as scheduled. Diversions occur when a flight lands at an airport other than its intended destination. Both metrics affect operational costs and customer experience but signal different disruption types.
How can buyers monetize flight delay and cancellation data?
Buyers license or sell the data directly to airlines, integrate it into consumer travel apps, bundle it with consulting services, or use it in predictive models. Public government data is free; proprietary enrichments (real-time feeds, predictive delay models, cost attribution) command premium pricing.
Sell yourflight delay & cancellationdata.
Describe your flight delay & cancellation data and the uses you are authorized to offer. Price, legal suitability, and buyer interest require separate evaluation. No match or sale is guaranteed.
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