ANS Performance (ANSperf) — ATC Performance Data

Datadory delivers ans performance ansperf atc performance data data covering the Performance Review Commission's measurement view of Europe's air traffic network: en-route ATFM delay by area and FIR split on IATA cause codes, airport arrival delay, ASMA additional time, taxi times, slot adherence, flight efficiency, IFR movements, gate-to-gate CO2/NOx/SOx and ANSP cost-effectiveness. Delivered daily, weekly, or hourly - your call.

What is ANS Performance (ANSperf) — ATC Performance Data?

It is the measurement view of the European air traffic network - the indicator tables the EUROCONTROL Performance Review Unit maintains for the independent Performance Review Commission, delivered by Datadory as analysis-ready rows under the Aerospace & Defense banner. Where dashboards show yesterday's network picture, these are the regulated benchmarks: the delay, efficiency, capacity, cost and emissions series that appear in European air navigation service performance reporting.

Five dataset families make up the record. Operations en-route covers en-route IFR flights, ATFM delay computed at both area-control-unit (AUA) and flight information region (FIR) level with full splits by IATA-style delay reason codes, and horizontal flight efficiency measured on the KEP/KEA definitions. Operations at airports covers airport traffic, arrival ATFM delay, ASMA additional terminal airspace time, additional taxi-out and taxi-in time, ATC and all-cause pre-departure delays, ATFM slot adherence and continuous climb/descent operations. Traffic adds complexity scores by provider. Economics carries ACE cost-effectiveness operational data plus provider financial data. Emissions provides gate-to-gate CO2, NOx and SOx including CO2 by state.

Scale check before you read further: the Airport Traffic table alone holds roughly 975,000 rows spanning 2014-2026, and the en-route ATFM delay table about 274,000. Every definition below was verified against the publisher's own field documentation during the August 2026 research pass - part of why this record scores 9/10 against a cross-catalog mean of 7.81. Get a sample of this dataset cut to your providers and years, or read the rows first.

What do sample rows look like?

Captured verbatim during the August 2026 research pass - two en-route delay rows, two airport traffic rows and one emissions bucket:

# en-route ATFM delay: one row per entity x month x methodology (AUA level)
YEAR 2011   MONTH_NUM 1   MONTH_MON JAN
ENTITY_NAME AirNav Ireland          ENTITY_TYPE ANSP (AUA)
FLT_ERT_1   1077                    DLY_ERT_1   106

YEAR 2011   MONTH_NUM 1   MONTH_MON JAN
ENTITY_NAME Albcontrol              ENTITY_TYPE ANSP (AUA)
FLT_ERT_1   362                     DLY_ERT_1   106

# airport traffic: one row per airport x month (Network Manager movements)
YEAR 2018   MONTH_MON JAN   FLT_DATE 2018-01-01
APT_ICAO EBBR   APT_NAME Brussels   STATE_NAME Belgium
FLT_DEP_1 211    FLT_ARR_1 204       FLT_TOT_1 415

YEAR 2018   MONTH_MON JAN
APT_ICAO EBCI   APT_NAME Brussels - Charleroi   STATE_NAME Belgium
FLT_DEP_1 51    FLT_ARR_1 53       FLT_TOT_1 104

# gate-to-gate emissions: one row per level x segment x phase x month
LEVEL NETWORK   AREA ECAC   YEAR 2019   MONTH 1
MARKET_SEGMENT business   FLIGHT_TYPE I   FLIGHT_PHASE cruise
NB_FLIGHTS 35561   CO2_TONS 75402.8

Read the anatomy rather than the digits. ENTITY_TYPE is what makes the en-route table additive across levels - the same DLY_ERT_1 column carries minutes for an ANSP, a functional airspace block or the whole area, and only that column tells you which denominator you are looking at. The airport rows keep operator-sourced and Network Manager movement counts apart (FLT_TOT_IFR_2 versus FLT_TOT_1) instead of blending them into one number nobody can audit. And the emissions row shows the qualifier discipline: segment, flight type and phase ride along with every tonne, so cruise burn never contaminates a taxi comparison.

Which fields does the dictionary define?

Twenty-six fields anchor the schema below, every definition verified against the source's own embedded data dictionary during the August 2026 review. They divide into four jobs:

Where does coverage run across geography, time and grain?

  • Geography: EUROCONTROL member states and the wider ECAC area, aggregated on one hierarchy from continental network down to individual state, functional airspace block, air navigation service provider and airport. One scheme spans continent-wide totals and single-provider cuts.
  • Temporal: staggered starts by design, not one arbitrary cutoff - en-route ATFM delay and IFR flights run from January 2011, horizontal flight efficiency from January 2014, airport operations from 2014, ACE operational data from January 2019, provider financial data across 2017-2024 and the gate-to-gate emissions window covering January 2019 through December 2024.
  • Granularity: daily buckets for airport operations and dashboards; monthly aggregations for en-route delays, traffic and emissions; yearly lines for the economics families - always keyed by entity so cuts stay comparable across periods.

That ladder is the point: the same entity keys answer "which provider booked the most capacity delay last year" and "which airport added the most taxi-in time since 2014" without any reconciliation between families. Set against the wider catalog - where the average quality score across all 1,744 datasets Datadory tracks is 7.81 - this record's 9/10 reflects verified field documentation and a publisher whose own regulatory role generates the numbers.

How is the data delivered?

API, files, or your warehouse. Daily, weekly, or hourly.

Name the providers, airports, families and period range when you request the sample and it lands shaped to that scope with the field dictionary unchanged - typed numerics, parsed periods, cause codes arriving as their own columns rather than buried in a total. Most teams take the historical depth once and keep recent periods rotating on whatever cadence matches their planning cycle; the key structure stays identical either way, so each pull appends cleanly to the last. Two honesty notes travel with every delivery: the emissions window is fixed through December 2024 while delay and traffic series run to current reference months, and the ACE operational line was flagged incomplete at research time. Datadory marks which series carry which caveat, so nobody builds a trend on a gap without knowing it.

Who uses this data, and for what?

Six jobs the record settles outright:

  1. Regulatory-grade benchmarking - state-, ANSP- and FAB-level delay, efficiency and cost figures issued by the body that polices them, which is why consultancies use them as the citation layer; see citation-grade research.
  2. Demand forecasting on European lanes - monthly IFR movements by airport back to 2014 give capacity models real seasonality to learn from; see demand forecasting.
  3. Aviation emissions baselining - gate-to-gate CO2, NOx and SOx by market segment and flight phase supply denominators for footprint claims; see ESG emissions analysis.
  4. Punctuality and cost signals between earnings - delay-minutes trends by cause code feed airline and airport narratives ahead of results; see quant backtesting.
  5. Hub competitiveness tracking - airport traffic plus ASMA and taxi measures rank how much approach and ground time each hub costs its carriers; see market sizing.
  6. Air-freight transit buffering - ATFM delay patterns by lane inform how much slack shippers should build into European road-and-air legs.

Which personas get the most value?

Journalists, academics and students get fifteen-plus years of citable European ATC performance history straight from the regulatory record - ideal raw material for punctuality, capacity and emissions reporting; see journalists academics aerospace & defense. Market researchers and consultants benchmark providers, states and airports on one consistent grid instead of stitching national statistics offices together. Data scientists and ML engineers train delay and traffic models on monthly series whose keys stay stable across fifteen years; see data scientists aerospace & defense. Investors and quant researchers read delay-cause trends as demand and cost indicators for carrier positions; see investors quants aerospace & defense. Competitive intelligence and product teams track hub-level throughput shifts; see competitive intelligence aerospace & defense.

Persona fit has edges, and it is worth naming them: sales-growth teams will find no purchasing budgets here beyond the provider cost lines themselves, and e-commerce operators get lane-risk context rather than customer data. The record measures the network's performance - not anyone's spending.

Which notes and neighboring datasets pair with it?

Scope note - this record is the Performance Review Commission's indicator view, deliberately distinct from the presentation-layer dashboards and trajectory repository the same organisation also publishes. Extracts are cut family-first by default; widen them deliberately if you want the full five-family bundle.

Completeness note - all twenty-six definitions above were verified against the publisher's own field documentation during the August 2026 research pass, and newest reference periods are confirmed against live records when your sample is prepared rather than claimed here. Known caveats we label rather than bury: the ACE operational line was flagged unavailable at research time, and complexity-score series split across BADA versions cannot be joined.

Where to go next - the rail below collects the sibling records that complete the picture: the dashboard view of the same network, US-side equivalents for transatlantic comparisons, and the glossary entries that decode the delay vocabulary.

Field dictionary

Every field below is documented against real records. The full dictionary ships with the sample.

Field dictionary - schema verified against the publisher's own data dictionary, August 2026
FieldTypeDefinitionExample
YEARintegerReference year of the record.2024
MONTH_NUMintegerMonth as a numeric value.7
MONTH_MONstringMonth as a three-letter code.JUL
FLT_DATEdateDate of flight, present in day-level airport operations rows.2024-07-15
ENTITY_NAMEstringName of the entity the row relates to: an ANSP, functional airspace block or area.Albcontrol
ENTITY_TYPEstringLevel the entity sits on: ANSP (at area-control-unit basis), FAB or AREA.ANSP (AUA)
FLT_ERT_1integerTotal number of flights within the respective airspace.1077
DLY_ERT_1numberMinutes of en-route ATFM delay.106
DLY_ERT_C_1numberMinutes of en-route ATFM delay attributed to code C - ATC capacity.
DLY_ERT_S_1numberMinutes of en-route ATFM delay attributed to code S - ATC staffing.
DLY_ERT_W_1numberMinutes of en-route ATFM delay attributed to code W - weather.
FLT_ERT_1_DLYintegerNumber of en-route ATFM delayed flights.
FLT_ERT_1_DLY_15integerNumber of en-route ATFM delayed flights exceeding 15 minutes.
ATFM_VERSIONstringMethodology used for the ATFM delay computation.
APT_ICAOstringICAO four-letter airport designator.EDDM
APT_NAMEstringAirport name.Munich
STATE_NAMEstringCountry in which the airport is located.Germany
FLT_DEP_1integerNumber of IFR departures, Network Manager source.211
FLT_ARR_1integerNumber of IFR arrivals, Network Manager source.204
FLT_TOT_1integerTotal IFR movements, arrivals plus departures, Network Manager source.415
FLT_TOT_IFR_2integerTotal IFR movements from the airport-operator source, kept separate from the Network Manager count.
LEVELstringAggregation level in the emissions dataset, e.g. NETWORK.NETWORK
MARKET_SEGMENTstringMarket segment in the emissions dataset, e.g. business aviation.business
FLIGHT_PHASEstringFlight phase in the emissions dataset, e.g. cruise or descent.cruise
CO2_TONSnumberCO2 emissions in tons in the gate-to-gate emissions dataset.
NOX_KGnumberNOx emissions in kilograms in the gate-to-gate emissions dataset.
SOX_KGnumberSOx emissions in kilograms in the gate-to-gate emissions dataset.

Coverage at a glance - geography, time, granularity

DimensionCoverage
GeographyEUROCONTROL member states and the wider ECAC area - network, state, functional airspace block (FAB), ANSP and airport levels under one scheme
TemporalEn-route ATFM delay and IFR flights from January 2011; flight efficiency from January 2014; airport operations from 2014; ACE operational data from January 2019; provider financial data 2017-2024; gate-to-gate emissions January 2019 - December 2024
GranularityDaily for airport operations and dashboards; monthly aggregations for en-route delays, traffic and emissions; yearly lines for the economics families - always keyed by entity

Product specification

AttributeValue
IndustryAerospace & Defense
PublisherEUROCONTROL Performance Review Unit, supporting the independent Performance Review Commission
Dataset familiesOperations en-route (delays, flights, KEP/KEA efficiency), Operations at airports (arrival delay, ASMA, taxi, pre-departure, slot adherence, CCO/CDO), Complexity, Economics (ACE + financials), Emissions
DimensionsEntity (ANSP / FAB / state / area), airport (ICAO), year-month, flight date, delay cause code, market segment, flight phase
Fields27 verified columns documented above; each family ships with its own embedded data-dictionary sheet defining names, sources and examples
StructureOne row per entity x period x measure family; flat, additive tables - no nested payloads, pivot-ready as delivered
SourceEUROCONTROL Aviation Intelligence Portal (ANS Performance portal)

Questions buyers ask

What does the ans performance ansperf atc performance data data contain?

Five families of European air navigation performance measures: en-route operations (IFR flights, ATFM delay at AUA and FIR level with IATA cause-code splits, KEP/KEA flight efficiency), airport operations (traffic, arrival delay, ASMA additional time, taxi times, pre-departure delays, slot adherence, continuous climb and descent), complexity scores, ACE cost-effectiveness and provider financials, and gate-to-gate CO2, NOx and SOx emissions.

How far back does the ATC performance history go?

En-route ATFM delay and IFR flight series run from January 2011, giving fifteen-plus years of monthly history per entity. Horizontal flight efficiency starts January 2014, airport operations 2014, ACE operational data January 2019, provider financial data covers 2017-2024, and the modelled gate-to-gate emissions window runs January 2019 through December 2024.

Which geographies can the series be cut on?

EUROCONTROL member states and the wider ECAC area, aggregated on one hierarchy: continental network, individual state, functional airspace block, air navigation service provider and airport. The ENTITY_NAME and ENTITY_TYPE columns name which level a row sits on, so a state rollup versus a provider-versus-provider comparison is a filter change rather than a new extract.

What separates delay minutes booked against capacity from those against weather?

The cause-code columns: DLY_ERT_C_1 carries capacity minutes, DLY_ERT_S_1 staffing and DLY_ERT_W_1 weather, each sitting beside DLY_ERT_1's total in the same row. Attribution studies never have to re-derive causes from narrative reporting - the regulator's own coding arrives pre-applied to every minute.

Is this different from the EUROCONTROL dashboard record?

Yes, and both matter. The dashboard record leads with presentation-layer analytics and a trajectory repository; this record is the Performance Review Commission's measurement view - the official indicator tables behind European air navigation performance regulation. Teams needing citable benchmark figures take this one; teams wanting daily network pictures pair it with the dashboard feed.

Can a sample be scoped to specific providers, airports and years?

Yes. Name the entities, families and period range when you request the sample and it lands shaped to that scope with the field dictionary unchanged - typed numerics, parsed periods, cause codes kept as their own columns. Anything validated against the sample survives delivery intact, because production draws from exactly the grain the sample showed.

See the rows before you pay anything.

Name this dataset and we send real records from it — scoped to the fields you asked for.

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