New product launch
Projective Fuel Oil & Feedstock Flows
Forward-looking cargo intelligence for fuel oil and feedstocks, built from validated market intelligence.
15–30%
Additional informational edge reported by clients
~60 days
Forward discharge visibility
~94%
Counterparty / trader coverage
Trusted by the world's leading Oil Majors, Trading Houses, National Oil Companies and Financial Institutions
TotalEnergies
Chevron
Shell
BP
Glencore
Mercuria
Gunvor
Aramco
ADNOC
SK Energy
Petrobras
Pertamina
INEOS
Repsol
Citi
Macquarie
Why this matters
Most market datasets are reflective rather than projective. They tell you what has already happened, or what is happening now. This intelligence is different: it projects physical cargo movements, inventories and trader behaviour weeks before barrels arrive, giving forward visibility into the supply dynamics that shape regional balances and pricing.
Physical traders use it to read competitor activity, inventory builds and arbitrage opportunities before they become visible to the wider market.
Quantitative researchers, paper traders and financial institutions use the same intelligence to understand the physical drivers behind futures pricing, spreads, cracks, time structures and regional dislocations.
It provides forward visibility of actual cargo movements, inventories and trader behaviour up to around 60 days ahead, a forward-looking layer that complements conventional vessel tracking and market data rather than replacing it.
Built for
Commodity traders
Hedge funds
Research and analytics teams
Market intelligence functions
~98% of tracked flows are projective, with up to ~60 days forward visibility
~94% counterparty / trader coverage
Captures sanctioned, dark fleet, ship-to-ship and re-documented flows
Weekly structured delivery with continuous updates through the cargo lifecycle
INDEPENDENT RESEARCH
From physical intelligence to pricing signals
Maritime Data has independently reviewed the framework behind this research, the Physical Fuel Oil Inventory Pressure Research Framework, and verified a random sample of the results. It explores multiple approaches for turning projected physical inventory intelligence into quantitative pricing signals, and shows how forward-looking physical intelligence can support discretionary trading, systematic research and quantitative model development.
A methodological review, not an endorsement of the findings, which remain the work of the source data provider.
−0.6155
Strongest rank correlation
~2 weeks
Forward signal horizon
22,572
Configurations tested
COVERAGE
Products covered
HSFO
LSFO / VLSFO / ULSFO
SRFO / A.RES / LSSR
VGO
Heavy Sweet Crude
CBFS
DCO
MCB / Slurry
LSWR
LCO
GEOGRAPHIC FOCUS
Key arrival regions
Singapore
North Asia
Arabian Gulf
Red Sea
Northwest Europe (ARA)
US Gulf
Format / Source
Date Range
S3 Bucket
HTML Report
Singapore
Jan 2017 - Present
Jan 2022
Jan 2017
North Asia
Jan 2017 - Present
Jan 2022
Jan 2017
Arabian Gulf
Aug 2021 - Present
Jan 2022
Aug 2021
Red Sea
Aug 2021 - Present
Jan 2022
Aug 2021
USA
July 2022 - Present
July 2022
July 2022
NW Europe
Jan 2025 - Present
Jan 2025
Jan 2025
HISOTRICAL COVERAGE
Coverage by format, date range and region
Update frequency: Weekly
SIGNAL COMPLETENESS
Complete on first report
Share of stems delivered with complete, actionable data points on initial reporting — across the fields that drive a trade.
Load Location and Date
100% complete
Product Type
100% complete
Discharge Location
100% complete
Trader
94% complete
COMPARABLE SYSTEM ANALYSIS
More complete initial signals
51% of stems tracked by a leading AIS-based provider lacked complete, actionable data points upon initial reporting.
Load Location and Date
Our Data 100%Provider 89%
Product Type
Our Data 100%Provider 84%
Discharge Location
Our Data 100%Provider 63%
Trader
Our Data 94%Provider 21%
Misclassifications
76% of the disputed volume was incorrectly classified as standard crude oil by the AIS-based provider, obscuring true fuel oil and feedstock balances.
Same
High Sulphur Fuel Oil
Crude
Low Sulphur Fuel Oil
No Product
Blending Crude
Condensates
Cycle Oils
18.1%
22.3%
59.6%
LSFO
17.2%
6%
24.1%
52.7%
HSFO
82.2%
8.7%
9.1%
SRFO
HSWEET
100%
30.3%
24.5%
30.3%
9.7%
VGO
0%
20%
40%
60%
80%
100%
FEEDBACK
What users say
"Back-testing of data resulted in a 30% increase in results output from our global analytics database."
QUANT ANALYST, OIL MAJOR
"You even get all the Russian trades right and that is our system. There is no competition in your space; what you do is totally different."
HEAD FUEL AND FEEDS ANALYST, NATIONAL OIL COMPANY
"We tried to do what you do, and could not achieve it internally."
GLOBAL HEAD OF ANALYTICS AND INNOVATION, GULF-BASED NATIONAL OIL COMPANY