UK FLIGHT DELAY INDEX

derived from CAA punctuality statistics for UK reporting airports

How often are these flights late or cancelled?

LHR ↔ TOKYO HANEDA

In the twelve months from July 2025 to June 2026, 21.2% of 1,730 movements arriving into LHR were disrupted — that is, they landed more than fifteen minutes late or were cancelled at short notice.

Put the other way round, 78.8% of 1,730 movements arrived on time by the industry's fifteen-minute standard. Severe delays were rarer: about one arrival in every 173 crossed the three-hour mark. Lower is better on every figure on this page. These numbers describe what happened on the route; they are not a prediction for any individual flight.

Definitions, denominators and limits
  • “Disrupted” means an arrival more than fifteen minutes late or a short-notice cancellation. The denominator is operated movements plus short-notice cancellations.
  • Arrivals into the UK airport only; all published carriers.
  • Crossing three hours is one condition for compensation, but monthly data cannot establish any individual passenger’s rights.
  • Delay cause is not published in the open data.
  • Source: CAA punctuality statistics · snapshot 17/08/2026 10:24 · method route-record-v2.1.

0 operations (0.00%) excluded because their published percentages could not be reconciled to whole numbers. Excluded operations enter neither the numerator nor the denominator. Outcome figures and comparisons are unavailable when the excluded share exceeds fifteen percent.

The four numbers at a glance

In the twelve months from July 2025 to June 2026, 21.2% of 1,730 movements were disrupted and 0.7% of 1,730 movements were cancelled at short notice.

When a flight was late, it was typically late by the range shown below. The delay is given as a range, not a single number, because the regulator rounds its published percentages and never says how many flights landed exactly on time.

Disruption shareShort-notice cancellationsAverage delay among delayed flights only — boundsOperations
21.2% of 1,730 movements0.7% of 1,730 movements30.1–74.0 min; N of delayed flights=355–8171,730
Definitions, denominators and limits

The bounds account for CAA rounding and the unknown number of zero delays. A point average across all operated movements, including punctual ones, would answer a different question and is not used here.

When it is late, how late is it?

Most delays here are short. The ladder below shows how many arrivals crossed each threshold, from a quarter of an hour up to six hours; each rung can only be smaller than the one above it.

Cancellations are counted separately: 0.7% of 1,730 movements. “One in N” means how many arrivals you would typically see between events at that level.

Delay threshold ladder; count and share of known operations15 min20.5%30 min10.9%60 min5.3%120 min2.4%180 min0.6%360 min0.2%
Delay ladder table: share, movements and one-in-N
DelayShare and nMovementsOne delay in every N operations
>15 min20.5% of 1,730 movements3554.9
>30 min10.9% of 1,730 movements1899.2
>60 min5.3% of 1,730 movements9119.0
>120 min2.4% of 1,730 movements4142.2
>180 min0.6% of 1,730 movements10173.0
>360 min0.2% of 1,730 movements4432.5
Definitions, denominators and limits

CAA counts delays strictly greater than each threshold, so exactly three hours is inseparable from the previous bucket. The ladder describes the archive, not a forecast.

Slightly late, or occasionally a disaster?

This route runs late less often than most, but when it does go wrong it tends to go badly wrong: its long delays are heavier than on the typical UK route.

The histogram below counts every recorded arrival, from more than fifteen minutes early through to more than six hours late. A tall bar near the middle and a thin right-hand tail is the healthy shape.

Nine delay buckets, minutes; share of all recorded operations>15 early42824.7%15–1 early47327.3%0–15 late46226.7%16–301669.6%31–60985.7%61…120502.9%121…180311.8%181…36060.3%>36040.2%D=1,730
Definitions, denominators and limits

Ratio of the long tail to sixteen-to-sixty-minute delays: 0.0379; corpus median 0.0217; 2056 routes in the corpus. The shape is compared conditionally among delays; the class name does not measure absolute frequency. Histogram counts and shares cover all recorded operations including unmatched records; reconstructed uniquely.

Has this route got better or worse since 2018?

Best month: Dec 2020, no events in 54 movements. Worst month: Aug 2023, 41.0% of 144 movements.

The line traces every month in the archive; lower is better. Gaps are months with no published data, never zeros. The 2020 and 2021 readings reflect the pandemic, not normal service.

Monthly disruption share; gaps mean no published dataJan 2018: 22.4%; sample: 1162018Feb 2018: 3.6%; sample: 112Mar 2018: 8.9%; sample: 124Apr 2018: 14.2%; sample: 120May 2018: 7.3%; sample: 124Jun 2018: 3.3%; sample: 120Jul 2018: 7.3%; sample: 124Aug 2018: 12.9%; sample: 124Sep 2018: 13.3%; sample: 120Oct 2018: 18.5%; sample: 124Nov 2018: 13.3%; sample: 120Dec 2018: 10.8%; sample: 120Jan 2019: 4.8%; sample: 1242019Feb 2019: 17.0%; sample: 112Mar 2019: 12.1%; sample: 124Apr 2019: 12.5%; sample: 120May 2019: 8.1%; sample: 124Jun 2019: 8.3%; sample: 120Jul 2019: 10.5%; sample: 124Aug 2019: 8.9%; sample: 124Sep 2019: 15.8%; sample: 120Oct 2019: 29.8%; sample: 124Nov 2019: 17.5%; sample: 120Dec 2019: 31.7%; sample: 123Jan 2020: 24.2%; sample: 1202020Feb 2020: 28.7%; sample: 115Mar 2020: 11.0%; sample: 118Apr 2020: 6.0%; sample: 50May 2020: 0.0%; sample: 27Jun 2020: 0.0%; sample: 24Jul 2020: 2.8%; sample: 36Aug 2020: 3.7%; sample: 27Sep 2020: 6.7%; sample: 30Oct 2020: 2.1%; sample: 48Nov 2020: 2.3%; sample: 44Dec 2020: 0.0%; sample: 54Jan 2021: 0.0%; sample: 552021Feb 2021: 2.2%; sample: 46Mar 2021: 6.5%; sample: 62Apr 2021: 1.4%; sample: 73May 2021: 5.7%; sample: 70Jun 2021: 3.6%; sample: 56Jul 2021: 8.1%; sample: 86Aug 2021: 5.6%; sample: 89Sep 2021: 11.7%; sample: 77Oct 2021: 8.8%; sample: 80Nov 2021: 1.6%; sample: 64Dec 2021: 1.5%; sample: 65Jan 2022: 1.8%; sample: 552022Feb 2022: 2.1%; sample: 48Mar 2022: 39.4%; sample: 66Apr 2022: 13.3%; sample: 45May 2022: 12.2%; sample: 41Jun 2022: 7.1%; sample: 56Jul 2022: 11.8%; sample: 76Aug 2022: 1.3%; sample: 79Sep 2022: 5.1%; sample: 78Oct 2022: 1.2%; sample: 80Nov 2022: 26.6%; sample: 94Dec 2022: 26.1%; sample: 111Jan 2023: 29.1%; sample: 1172023Feb 2023: 15.5%; sample: 110Mar 2023: 15.0%; sample: 127Apr 2023: 34.3%; sample: 137May 2023: 16.3%; sample: 141Jun 2023: 36.5%; sample: 137Jul 2023: 24.6%; sample: 142Aug 2023: 41.0%; sample: 144Sep 2023: 32.4%; sample: 136Oct 2023: 19.4%; sample: 139Nov 2023: 23.3%; sample: 133Dec 2023: 8.2%; sample: 122Jan 2024: 36.0%; sample: 1252024Feb 2024: 14.2%; sample: 127Mar 2024: 14.5%; sample: 138Apr 2024: 16.0%; sample: 150May 2024: 13.5%; sample: 155Jun 2024: 23.3%; sample: 150Jul 2024: 25.2%; sample: 155Aug 2024: 23.2%; sample: 155Sep 2024: 26.8%; sample: 149Oct 2024: 17.1%; sample: 152Nov 2024: 15.0%; sample: 133Dec 2024: 12.5%; sample: 136Jan 2025: 11.6%; sample: 1292025Feb 2025: 28.7%; sample: 115Mar 2025: 9.8%; sample: 133Apr 2025: 16.0%; sample: 150May 2025: 17.4%; sample: 155Jun 2025: 27.3%; sample: 150Jul 2025: 35.3%; sample: 156Aug 2025: 35.0%; sample: 157Sep 2025: 20.7%; sample: 150Oct 2025: 8.6%; sample: 152Nov 2025: 4.5%; sample: 133Dec 2025: 21.9%; sample: 137Jan 2026: 16.1%; sample: 1242026Feb 2026: 15.6%; sample: 122Mar 2026: 38.2%; sample: 144Apr 2026: 15.2%; sample: 151May 2026: 12.9%; sample: 155Jun 2026: 26.8%; sample: 149Pandemic regime Jun 2020Summer 2022 breakdown Jul 2022NATS system failure Aug 2023Heathrow fire closure Mar 2025100%0%
Every month since 2018, including gaps and suppressed cells
MonthDisruption on arrivals
Jan 201822.4% of 116 movements
Feb 20183.6% of 112 movements
Mar 20188.9% of 124 movements
Apr 201814.2% of 120 movements
May 20187.3% of 124 movements
Jun 20183.3% of 120 movements
Jul 20187.3% of 124 movements
Aug 201812.9% of 124 movements
Sep 201813.3% of 120 movements
Oct 201818.5% of 124 movements
Nov 201813.3% of 120 movements
Dec 201810.8% of 120 movements
Jan 20194.8% of 124 movements
Feb 201917.0% of 112 movements
Mar 201912.1% of 124 movements
Apr 201912.5% of 120 movements
May 20198.1% of 124 movements
Jun 20198.3% of 120 movements
Jul 201910.5% of 124 movements
Aug 20198.9% of 124 movements
Sep 201915.8% of 120 movements
Oct 201929.8% of 124 movements
Nov 201917.5% of 120 movements
Dec 201931.7% of 123 movements
Jan 202024.2% of 120 movements
Feb 202028.7% of 115 movements
Mar 202011.0% of 118 movements
Apr 20206.0% of 50 movements
May 2020no events in 27 movements — small sample, not ranked
Jun 2020no events in 24 movements — small sample, not ranked
Jul 20202.8% of 36 movements — small sample, not ranked
Aug 20203.7% of 27 movements — small sample, not ranked
Sep 20206.7% of 30 movements — small sample, not ranked
Oct 20202.1% of 48 movements — small sample, not ranked
Nov 20202.3% of 44 movements — small sample, not ranked
Dec 2020no events in 54 movements
Jan 2021no events in 55 movements
Feb 20212.2% of 46 movements — small sample, not ranked
Mar 20216.5% of 62 movements
Apr 20211.4% of 73 movements
May 20215.7% of 70 movements
Jun 20213.6% of 56 movements
Jul 20218.1% of 86 movements
Aug 20215.6% of 89 movements
Sep 202111.7% of 77 movements
Oct 20218.8% of 80 movements
Nov 20211.6% of 64 movements
Dec 20211.5% of 65 movements
Jan 20221.8% of 55 movements
Feb 20222.1% of 48 movements — small sample, not ranked
Mar 202239.4% of 66 movements
Apr 202213.3% of 45 movements — small sample, not ranked
May 202212.2% of 41 movements — small sample, not ranked
Jun 20227.1% of 56 movements
Jul 202211.8% of 76 movements
Aug 20221.3% of 79 movements
Sep 20225.1% of 78 movements
Oct 20221.2% of 80 movements
Nov 202226.6% of 94 movements
Dec 202226.1% of 111 movements
Jan 202329.1% of 117 movements
Feb 202315.5% of 110 movements
Mar 202315.0% of 127 movements
Apr 202334.3% of 137 movements
May 202316.3% of 141 movements
Jun 202336.5% of 137 movements
Jul 202324.6% of 142 movements
Aug 202341.0% of 144 movements
Sep 202332.4% of 136 movements
Oct 202319.4% of 139 movements
Nov 202323.3% of 133 movements
Dec 20238.2% of 122 movements
Jan 202436.0% of 125 movements
Feb 202414.2% of 127 movements
Mar 202414.5% of 138 movements
Apr 202416.0% of 150 movements
May 202413.5% of 155 movements
Jun 202423.3% of 150 movements
Jul 202425.2% of 155 movements
Aug 202423.2% of 155 movements
Sep 202426.8% of 149 movements
Oct 202417.1% of 152 movements
Nov 202415.0% of 133 movements
Dec 202412.5% of 136 movements
Jan 202511.6% of 129 movements
Feb 202528.7% of 115 movements
Mar 20259.8% of 133 movements
Apr 202516.0% of 150 movements
May 202517.4% of 155 movements
Jun 202527.3% of 150 movements
Jul 202535.3% of 156 movements
Aug 202535.0% of 157 movements
Sep 202520.7% of 150 movements
Oct 20258.6% of 152 movements
Nov 20254.5% of 133 movements
Dec 202521.9% of 137 movements
Jan 202616.1% of 124 movements
Feb 202615.6% of 122 movements
Mar 202638.2% of 144 movements
Apr 202615.2% of 151 movements
May 202612.9% of 155 movements
Jun 202626.8% of 149 movements

What did the big disruptions actually do here?

Each named event below is shown against this route’s own baseline for the twelve months before it, and against how long the route took to get back to that baseline.

A month worse than baseline is not proof the named event caused it: the open data carry no delay-cause field at all. Some events sit near the edge of the archive, which limits how long a recovery can be traced.

EventDirectionDisruption that monthBaseline beforeReturn to baseline
Pandemic regime · Jun 2020Arrivalsno events in 24 movements — small sample, not ranked16.0% across 1,285 flightsreturned the next month
Pandemic regime · Jun 2020Departuresno events in 25 movements — small sample, not ranked12.0% across 1,279 flightsreturned the next month
Summer 2022 breakdown · Jul 2022Arrivals11.8% of 76 movements9.4% across 772 flightsreturned the next month
Summer 2022 breakdown · Jul 2022Departures74.7% of 75 movements20.5% across 759 flightsreturned after 4 months
NATS system failure · Aug 2023Arrivals41.0% of 144 movements19.3% across 1,353 flightsreturned after 4 months
NATS system failure · Aug 2023Departures33.3% of 141 movements30.6% across 1,354 flightsreturned after 2 months
Heathrow fire closure · Mar 2025Arrivals9.8% of 133 movements19.0% across 1,717 flightsreturned the next month
Heathrow fire closure · Mar 2025Departures17.8% of 135 movements24.5% across 1,713 flightsreturned the next month
Definitions, denominators and limits

The baseline is the unweighted mean share over the twelve preceding calendar months. The return window is the following eight months, up to the end of the archive. Return means the first observed value at or below the baseline; it is not the duration of the disruption itself. If the event month is already below the baseline, counting still starts the month after. Gaps and suppressed cells are not treated as zeros or as recovery.

Which time of year has historically been hardest?

June has historically been the hardest month on this route: in a typical June, 23.3% of arrivals were disrupted, measured across 7 Junes in the archive. May has been the calmest, at 12.9% across 7 Mays.

Even June has ranged from 3.3% to 36.5% in different years, so this is a record of what happened, not a forecast of what will. Lower is better throughout.

Each cell is one calendar month of one year; the number is the share of that month’s arrivals that were disrupted. Darker means worse. A blank cell means no published data, not zero.

Seasonality: calendar month by year; share and nJanFebMarAprMayJunJulAugSepOctNovDec20194.8% of 124 movements17.0% of 112 movements12.1% of 124 movements12.5% of 120 movements8.1% of 124 movements8.3% of 120 movements10.5% of 124 movements8.9% of 124 movements15.8% of 120 movements29.8% of 124 movements17.5% of 120 movements31.7% of 123 movements202024.2% of 120 movements28.7% of 115 movements11.0% of 118 movements6.0% of 50 movementsno events in 27 movements †no events in 24 movements †2.8% of 36 movements †3.7% of 27 movements †6.7% of 30 movements †2.1% of 48 movements †2.3% of 44 movements †no events in 54 movements2021no events in 55 movements2.2% of 46 movements †6.5% of 62 movements1.4% of 73 movements5.7% of 70 movements3.6% of 56 movements8.1% of 86 movements5.6% of 89 movements11.7% of 77 movements8.8% of 80 movements1.6% of 64 movements1.5% of 65 movements20221.8% of 55 movements2.1% of 48 movements †39.4% of 66 movements13.3% of 45 movements †12.2% of 41 movements †7.1% of 56 movements11.8% of 76 movements1.3% of 79 movements5.1% of 78 movements1.2% of 80 movements26.6% of 94 movements26.1% of 111 movements202329.1% of 117 movements15.5% of 110 movements15.0% of 127 movements34.3% of 137 movements16.3% of 141 movements36.5% of 137 movements24.6% of 142 movements41.0% of 144 movements32.4% of 136 movements19.4% of 139 movements23.3% of 133 movements8.2% of 122 movements202436.0% of 125 movements14.2% of 127 movements14.5% of 138 movements16.0% of 150 movements13.5% of 155 movements23.3% of 150 movements25.2% of 155 movements23.2% of 155 movements26.8% of 149 movements17.1% of 152 movements15.0% of 133 movements12.5% of 136 movements202511.6% of 129 movements28.7% of 115 movements9.8% of 133 movements16.0% of 150 movements17.4% of 155 movements27.3% of 150 movements35.3% of 156 movements35.0% of 157 movements20.7% of 150 movements8.6% of 152 movements4.5% of 133 movements21.9% of 137 movements202616.1% of 124 movements15.6% of 122 movements38.2% of 144 movements15.2% of 151 movements12.9% of 155 movements26.8% of 149 movementsno datano datano datano datano datano data
Month-by-month table: median, observed range and sample
MonthMedianObserved rangeSample
Jan16.1%1.8–36.0%7 months, 790 flights
Feb15.5%2.1–28.7%7 months, 746 flights
Mar14.5%8.9–39.4%7 months, 856 flights
Apr15.2%12.5–34.3%7 months, 873 flights
May12.9%7.3–17.4%7 months, 895 flights
Jun23.3%3.3–36.5%7 months, 882 flights
Jul18.2%7.3–35.3%6 months, 777 flights
Aug18.1%1.3–41.0%6 months, 783 flights
Sep18.2%5.1–32.4%6 months, 753 flights
Oct17.8%1.2–29.8%6 months, 771 flights
Nov16.3%4.5–26.6%6 months, 733 flights
Dec17.2%8.2–31.7%6 months, 749 flights
Definitions, denominators and limits

The matrix shows the last eight calendar years, including an incomplete final year; the start of the archive is kept in the history above. Seasonal summaries use the whole available archive, excluding the pandemic regime 2020–2021; this is an observed range, not a forecast. Zero events, missing data and suppressed cells are marked separately. † marks a small sample, described but not ranked. For ranges the colour follows the upper bound.

Which airline has the better record here?

On the published record there is no clear winner: All Nippon Airways 15.9% of 365 movements, Japan Airlines 22.1% of 728 movements, British Airways 23.2% of 637 movements. Observed shares differ; the mix of operations is not matched, so no causal conclusion follows.

Figures cover arrivals, July 2025 to June 2026; lower is better in every column. Carriers with fewer than twenty published flights are suppressed rather than shown as zero. The page makes no ranking: the operations behind these shares are not matched for aircraft, time of day or season.

Observed disruption share by optionAll Nippon Airways15.9% of 365 flightsBritish Airways23.2% of 637 flightsJapan Airlines22.1% of 728 flights
Airline comparison table: operations, cancellations, three-hour delays and data quality
AirlineOperationsDisruptionCancellations>180 minData quality
Air Francesuppressed: fewer than twenty movementssuppressed: fewer than twenty movementssuppressed: fewer than twenty movementssuppressed: fewer than twenty movementssuppressed
All Nippon Airways36515.9% of 365 movements0.3% of 365 movements0.8% of 365 movementsdescriptive comparison
British Airways63723.2% of 637 movements1.4% of 637 movements0.8% of 637 movementsdescriptive comparison
Japan Airlines72822.1% of 728 movements0.3% of 728 movements0.3% of 728 movementsdescriptive comparison

The noise check is a descriptive approximation assuming independent operations. Delay correlation and mix differences are not estimated; no ranking is derived.

Would another UK airport have been better?

No other UK airport published enough flights to this city in this window.

Each figure is arrivals into that UK airport, all carriers combined, over the same twelve months. It is a historical record, not a recommendation about where to fly from, and it says nothing about getting to or from each airport on the ground.

Airport comparison table: operations, cancellations, three-hour delays and data quality
Other UK airport to the same cityOperationsDisruptionCancellations>180 minData quality
Ltn ↔ Tokyo-Hanedasuppressed: fewer than twenty movementssuppressed: fewer than twenty movementssuppressed: fewer than twenty movementssuppressed: fewer than twenty movementssuppressed
Man ↔ Tokyo-Hanedasuppressed: fewer than twenty movementssuppressed: fewer than twenty movementssuppressed: fewer than twenty movementssuppressed: fewer than twenty movementssuppressed

Does the direction you are flying change anything?

Barely: arrivals into LHR ran 21.2% of 1,730 movements disrupted, departures 22.3% of 1,732 movements.

It matters legally as well as practically: a departure from the UK and an arrival into the UK on a UK or EU carrier fall under different conditions, and a departure delay does not establish a late arrival at your final destination.

Arrivals and departures side by side
DirectionDisruptionCancellationsOver three hours
Arrivals into LHR21.2% of 1,730 movements0.7% of 1,730 movements0.6% of 1,730 movements
Departures from LHR22.3% of 1,732 movements0.8% of 1,732 movements0.5% of 1,732 movements
Definitions, denominators and limits

CAA conditions on delays and cancellations.

How many flights here crossed the three-hour mark?

The table below counts arrivals and departures that ran more than three hours late — the threshold that is one of the conditions for compensation — across the whole archive and within the last six years.

The pound figure beside each count is arithmetic, not money anyone received: it is the count multiplied by the maximum statutory amount for this distance band. Whether any of those flights actually qualified is not knowable from this data.

DirectionWindowFlights over three hoursArithmetic statutory ceiling
ArrivalsWhole archive · Jan 2018–Jun 202674 flights out of 11,12474 × £520 = £38,480
ArrivalsLast 72 months · Jul 2020–Jun 202641 flights out of 7,76341 × £520 = £21,320
DeparturesWhole archive · Jan 2018–Jun 202662 flights out of 11,06462 × £520 = £32,240
DeparturesLast 72 months · Jul 2020–Jun 202631 flights out of 7,70831 × £520 = £16,120
Definitions, denominators and limits

Full formula: the count is the sum of the two tail buckets across months, carriers and service types in one direction; the ceiling is that count multiplied by the maximum statutory amount for the distance band. The condition is: if every such delay had been the carrier's fault and a claim had been filed on every one of them.

This is conditional arithmetic over operations: passenger numbers, legal applicability and the number of claims are all unknown. For departures it is an arithmetic scenario only, because arrival at the final point is not observed. For long routes the maximum ceiling is used; any reduction in the payable amount is not calculated.

The archive window is counted from the last month of data, not from today: this is not a limitation check for an individual case. The CAA states six years for England and Wales and five for Scotland. CAA: time limits and how to complain. Information, not a legal service.

The facts about this route

Route reference table: codes, distance, frequency, archive span
FieldValue
UK airportHEATHROW · LHR
Final point / countryTOKYO (HANEDA) / JAPAN
Final point codesHND / RJTT
Great-circle distance9,592 km
Maximum statutory amount for the band£520
Average operated arrivals per day4.71
Presence in the latest twelve-month windowoperations present in every month of the latest twelve-month window
First and last active monthJan 2018–Jun 2026
Months with operations in the archive102

origin_destination is the final point of the CAA service, not evidence of a nonstop connection. The distance joins the coordinates of the named airports; the actual track is unknown. Frequency describes published operations.

What this data cannot tell you

Delay cause is not published in the regulator's open data. Monthly aggregates describe a population, not a specific flight. Cells below twenty operations are suppressed; twenty to forty-nine are descriptive only and not ranked. Arrivals and departures do not add up. Cancellations are short-notice only, by the CAA definition. A movement is not the same as a scheduled flight.

0 operations (0.00%) excluded because their published percentages could not be reconciled to whole numbers. Excluded operations enter neither the numerator nor the denominator. Outcome figures and comparisons are unavailable when the excluded share exceeds fifteen percent.

Data-quality counters for this route

Zero observed events does not mean zero risk. Operator coverage against the Summary file is not established in this record; comparisons are limited to the published population.

Unmatched records: 0; all recorded operations: 1,730; excluded by quarantine: 0.

Quick answers

How often is this route disrupted?

21.2% of 1,730 movements over July 2025 to June 2026. Arrivals into the UK airport; all published carriers.

How many flights are cancelled at short notice?

0.7% of 1,730 movements in the same window.

How many delays crossed three hours?

0.6% of 1,730 movements in the same window; these are observed movements, not a count of claims.

What does the delay distribution look like?

rare but severe. The class compares the tail with short delays across routes in the corpus.

What distance is used?

9,592 km, great-circle.

Can compensation entitlement be established here?

No. The cause and the circumstances of an individual flight are unknown. Official CAA conditions.

Why do some cells say "no data"?

That month is absent from the published series. Small cells carry a separate "suppressed" marker; a gap is never replaced by a zero.

How this was calculated

Dataset version, input hashes and reconstruction rules

Dataset version: 396da8dde2874f14; method route-record-v2.1.

Versioned register of every number and the entity map · Input hashes · Correction log · Reconstruction and formulas.

Reconstruction: integer counts inside the rounding bounds of shares of D, summing to M. Ambiguity is preserved as a range of feasible counts; non-convergence stays in quarantine. The map of codes and coordinates is pinned by hash alongside the data. Raw CSV files are not included in the published output.

Your trip has already gone wrong — what now?

The official route to complain

Contact the airline first, then the relevant ADR body or the CAA. The right to care is assessed separately from compensation; time limits and circumstances are checked case by case. CAA: how to complain.

Reconstruction and formulas

Open the versioned claim register

Was your flight delayed 3h+? Check what you may be owed

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