Transit times / Fayman & Sorbello Food Group Llc

Fayman & Sorbello Food Group Llc

118 ocean import shipments. Delayed 13 points more often than the dataset average of 43.8%.

Includes shipments filed under: Fayman & Sorbello Food Group Llc · Fayman Sorbello Food Group Llc

118
Shipments
56.8%
Arrived late
67 shipments
2.3 days
Average delay, when late
median 2 days
7 days
Worst single delay

How late, when late

Every shipment placed in a band. Early and on-time are shown too, so the delayed share is read against the whole, not on its own.

0
0%
Early
51
43.2%
On time
63
53.4%
1–3 days
4
3.4%
4–7 days
0
0%
8–14 days
0
0%
15+ days

By carrier

All 4 carriers used.

% delayed avg days late, when laten = shipments
  1. Hapag Lloyd
    70.6%
    2d
    8560 late
  2. CMA CGM
    13.8%
    7d
    294 late
  3. Zim
    100%
    1d
    33 late
  4. ONE
    0%
    10 late

By route

All 4 lanes.

% delayed avg days late, when laten = shipments
  1. Sao Paulo > Houston, Texas
    42%
    2.5d
    6929 late
  2. Barao De Teffe > Houston, Texas
    75.6%
    2d
    4534 late
  3. Montevideo > Houston, Texas
    100%
    1d
    33 late
  4. Port Bustamante > Houston, Texas
    100%
    7d
    11 late

By supplier

All 8 suppliers.

% delayed avg days late, when laten = shipments
  1. Jbs S/A
    59.2%
    2d
    7645 late
  2. Barra Mansa Comercio De
    54.5%
    2.4d
    2212 late
  3. Prima Foods S A
    25%
    7d
    82 late
  4. Frigol S A
    66.7%
    2d
    32 late
  5. Frigorifico Better Beef Ltda
    66.7%
    2d
    32 late
  6. Vale Grande Industria E
    33.3%
    7d
    31 late
  7. Frigorifico Guarani S A C I
    100%
    1d
    22 late
  8. Cooperativa Colonizadora
    100%
    1d
    11 late

By vessel

Vessel names are in the most recent data only — 118 of 118 shipments (100%) name one, across 5 ships. This chart covers that subset, not the whole.

% delayed avg days late, when laten = shipments
  1. Dalian Express
    100%
    2d
    6060 late
  2. Le Havre Express
    0%
    260 late
  3. Cma Cgm Rabelais
    0%
    250 late
  4. Swansea
    100%
    7d
    44 late
  5. Zim Baltimore
    100%
    1d
    33 late

Delay rate by arrival date

Share of each day’s arrivals that came in late. A single late vessel puts the same delay on every container it carried, so a tall isolated bar is usually one sailing rather than a bad week — the count under each bar is the check on that.

100%
n=60
2026-07-30
100%
n=4
2026-08-02
0%
n=26
2026-08-04
0%
n=25
2026-08-09
100%
n=3
2026-08-10

By destination port

Where the delay actually lands — a congested discharge port shows up here rather than under the carrier.

% delayed avg days late, when laten = shipments
  1. Houston, Texas
    56.8%
    2.3d
    11867 late

By supplier country

Origin-side effects: a country whose shipments are consistently late points at booking or documentation, not at the ocean leg.

% delayed avg days late, when laten = shipments
  1. Brazil
    55.3%
    2.2d
    11463 late
  2. Paraguay
    100%
    1d
    33 late
  3. Germany
    100%
    7d
    11 late

Reading this

Delay is measured against each shipment’s own estimated arrival on the same manifest record, so it reflects what was promised for that shipment. Average days late is taken over delayed shipments only.

A delay is usually a property of one sailing: every container off a late ship arrives the same day. It is not only that — an estimated arrival is set per bill of lading at booking, so two containers on the same ship can carry different delays. Across the shipments that name a vessel, two thirds of same-ship, same-day groups share a single delay value and a third do not.

Watch the counts. A carrier or lane with a handful of shipments can show a dramatic rate off one or two late arrivals — the n beside every bar is there so a small sample is never mistaken for a pattern.

Track a shipment live →