WorldACD Air Cargo Market Data

It answers what official statistics cannot: what did the airfreight market actually carry and price last week? WorldACD Market Data B.V., an Amsterdam-based intelligence provider with two decades of operating history, pools confidential submissions from more than 100 airlines and forwarders under stated principles of confidentiality, neutrality and independence - verifying and classifying cargo data, then publishing aggregates only.

The weekly layer carries chargeable weight, yields and rates, capacity and load factors, joined by a worldwide rate index, FTK and ATK trends on actual flights and history back ten-plus years. The deeper tier goes where public statistics never do: agent-level data across 15,000+ freight forwarders in 14 product and priority categories, plus GSA reporting.

Government tables count tonnes at airports after the fact; this record reads demand and pricing from the carriers and forwarders moving the freight, week by week. It sits inside our air freight logistics data hub of 24 pooled datasets. Get a sample cut to the markets you name.

One measure, one market cut, one period - that is the skeleton of every observation:

measure        : chargeable weight     period : week 34, 2026     grain : market-level aggregate
measure        : yield / rate          period : week 34, 2026     grain : market-level average
measure        : load factor           period : week 34, 2026     grain : market-level utilization

# monthly flight-based trends keep their own rhythm
measure        : FTK                   period : monthly series    basis : actual flights
measure        : ATK                   period : monthly series    basis : actual flights

# the competitive cut swaps market totals for named agents
forwarder      : <agent>               scope  : 15,000+ forwarders
product        : <category>            split  : 14 product & priority categories

Read the anatomy rather than the placeholders. Weight, rate and utilization share the same weekly coordinates, so one market-week resolves volume, price and how full the capacity flew without joining three sources. The monthly FTK and ATK lines keep their own rhythm on actual flights rather than schedules; the forwarder dimension swaps the market total for a named agent when the question turns competitive.

Six fields anchor the dictionary, each a market measure rather than a filler identifier: two volume measures, one price-and-yield measure, one utilization ratio, the two flight-based traffic measures, and the agent dimension that turns market totals into a competitive map.

They divide cleanly: Chargeable weight and Forwarder agent fix what moved and who moved it, Yield / rate prices it, Load factor says how full the lift was, and FTK plus ATK turn both sides of that ratio into distance-weighted traffic work. Because the yield series feeds a worldwide rate index, one dictionary serves both level questions and trend questions.

Additional fields on request: the agent-level table across more than 15,000 forwarders, the 14 product and priority category splits, worldwide rate index values, GSA performance reporting cuts, and origin-destination lane detail are documented against delivered extracts rather than promised blind - state which cuts you need when you request the sample.

Geography - worldwide air cargo markets with regional breakdowns, compiled from Amsterdam. Contributions come from airlines and forwarders rather than airport operators, so coverage follows the market's actual traffic instead of stopping at airports that file statistics.

Temporal - weekly weight and rate figures form the core cadence, with monthly publications summarizing the same market and historic growth data back more than ten years: enough runway to span fuel spikes, capacity crunches and the pandemic collapse-and-recovery inside one methodology.

Granularity - three levels deep. Market-level weekly and monthly aggregates are the shared layer; the deeper tier resolves to 15,000+ individual forwarders and 14 product and priority categories; GSA reporting recuts performance by sales agent. Most datasets in this slice own exactly one of those levels.

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

Pick the markets, cadence and landing zone - the same aggregate rows arrive either way, with the six-field dictionary above unchanged. The sample comes first, so market list, history depth and deeper-tier cuts are settled facts before any commitment.

• Rate negotiation and procurement - Walk into contract talks holding the trailing weekly market move, not one lane's last quote.
• Carrier and forwarder benchmarking - Set your own volumes, yields and load factors against the pooled market aggregate; competitor direction rides on the same series.
• Cargo-demand signals - Weekly contributor-fed demand and pricing gives quants an airfreight signal official releases publish too late to act on.
• Market sizing and diligence - A decade-plus of aggregates sizes the airfreight market and its cycles for entry studies and diligence.
• GSA performance management - Customized reporting recuts the same contributor base into sales-agent accountability by market.

Worked flows continue on demand forecasting for pipeline patterns and on citation-grade research for attribution discipline with a neutral aggregator as source.

Investors and quant researchers (relevance 3 of 3) get the cargo-demand signal official statistics deliver too late - weekly, contributor-fed and priced. Market researchers (3 of 3) get the market-level aggregate sizing work needs with a decade of history behind it; see market researchers in air freight. Competitive-intel and product teams (2 of 3) read rate direction before it hardens into a rival's pricing move; see competitive intel teams in air freight. Journalists and academics (2 of 3) cite a neutral aggregator over a carrier press release. Data scientists (1 of 3) pair these aggregates with flight-level feeds.

This record owns the contributor-fed weekly market view and concedes granularity elsewhere. TAC Index Air Freight Rate Index prices individual trade lanes through 100+ timestamped indices - sharper when one lane is the question. BTS T-100 Air Carrier Statistics digs deeper per flight - monthly US carrier traffic back to 1990, 14,083,343 segment records - but stops at US carriers and carries no rates. Eurostat's AVIA_GOOA main-airports table holds 17,791,958 airport-level observations from 1993 onward, all volume and no price. IATA WATS benchmarks 250+ airlines annually but cannot show a week's movement.

None replicates one neutral aggregator pooling weekly weight, rate, capacity and load-factor series from 100+ contributors with an agent-level cut beneath. Teams stack them: this record sets the weekly baseline, lane indices price routes, government tables verify volumes. Ranked slate: best air freight logistics datasets.

Three honest caveats.

First, aggregation is the product: contributor confidentiality means no booking-level truth exists here - raw submissions are never published, so a single carrier's own book stays outside its reach.

Second, depth is tiered: market-level weekly aggregates form the shared layer, while the agent cut, product categories and lane detail belong to the deeper tier - name which cuts you need and they get confirmed against delivery rather than assumed.

Third, some structure is undocumented publicly: chargeable-weight methodology and normalization choices get pinned down against live records during sample preparation. That defines where the record is strongest - breadth and neutrality over per-flight depth.