Transit times / Great Luck Inc

Great Luck Inc

229 ocean import shipments. Delayed 0.7 points more often than the dataset average of 43.8%.

229
Shipments
44.5%
Arrived late
102 shipments
3.8 days
Average delay, when late
median 2 days
17 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.

12
5.2%
Early
115
50.2%
On time
84
36.7%
1–3 days
5
2.2%
4–7 days
4
1.7%
8–14 days
9
3.9%
15+ days

By carrier

Top 12 of 15 carriers; 3 shipments across the remaining 3 not shown.

% delayed avg days late, when laten = shipments
  1. ONE
    11.7%
    2d
    607 late
  2. HMM
    68.5%
    5.8d
    5437 late
  3. CMA CGM
    55.9%
    2d
    3419 late
  4. MSC
    60%
    2.3d
    159 late
  5. Yang Ming
    71.4%
    2.2d
    1410 late
  6. Hapag Lloyd
    14.3%
    2d
    142 late
  7. COSCO
    66.7%
    5.1d
    128 late
  8. Evergreen
    42.9%
    1.3d
    73 late
  9. Maersk
    33.3%
    2d
    62 late
  10. SSBF
    0%
    60 late
  11. Zim
    100%
    1.5d
    22 late
  12. OOCL
    50%
    2d
    21 late

By route

Top 12 of 47 lanes; 58 shipments across the remaining 35 not shown.

% delayed avg days late, when laten = shipments
  1. Kobe > Los Angeles, Ca
    34.9%
    2.3d
    4315 late
  2. Tokyo > Los Angeles, Ca
    31%
    2d
    299 late
  3. Nagoya Ko > Los Angeles, Ca
    25%
    2.5d
    246 late
  4. Pusan > Newark, Nj
    81.3%
    12.8d
    1613 late
  5. Yokohama > Los Angeles, Ca
    41.7%
    1d
    125 late
  6. Kobe > Oakland, Ca
    40%
    2d
    104 late
  7. Pusan > Baltimore, Md.
    70%
    2.3d
    107 late
  8. Yangshan > Newark, Nj
    100%
    5.7d
    66 late
  9. Pusan > Houston, Texas
    83.3%
    1d
    65 late
  10. Kaohsiung > Newark, Nj
    40%
    1d
    52 late
  11. Ning Bo > Newark, Nj
    0%
    50 late
  12. Shanghai > Norfolk, Va.
    0%
    50 late

By supplier

All 8 suppliers.

% delayed avg days late, when laten = shipments
  1. Japan Trust Co Ltd
    44%
    3.9d
    21695 late
  2. Mac Nels Shipping Thailand Ltd
    25%
    2d
    41 late
  3. Japan Logistics Corp
    50%
    1d
    21 late
  4. Japan Trust Company Ltd
    50%
    2d
    21 late
  5. Pinnacle World Transport Pte Ltd
    100%
    1.5d
    22 late
  6. Safround Logistics Co Ltd
    0%
    10 late
  7. Pt Honour Lane Shipping
    100%
    2d
    11 late
  8. Otsuka Warehouse Co Ltd
    100%
    3d
    11 late

By vessel

Vessel names are in the most recent data only — 229 of 229 shipments (100%) name one, across 52 ships. This chart covers that subset, not the whole.

% delayed avg days late, when laten = shipments
  1. Navios Cyan
    0%
    480 late
  2. Mol Proficiency
    53.5%
    2d
    4323 late
  3. President Jq Adams
    13.3%
    1d
    152 late
  4. Hmm Aquamarine
    90%
    17d
    109 late
  5. President Grant
    100%
    3d
    77 late
  6. Msc Mumbai Viii
    16.7%
    1d
    61 late
  7. One Modern
    100%
    2d
    66 late
  8. Esl Nhava Sheva
    100%
    1d
    55 late
  9. Charlotte Schulte
    40%
    1d
    52 late
  10. Gjertrud Maersk
    0%
    50 late
  11. Grete Maersk
    0%
    50 late
  12. Msc Rikku
    100%
    2.3d
    44 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.

58.3%
n=12
2026-07-27
83.3%
n=6
2026-07-28
4.8%
n=42
2026-07-29
36%
n=25
2026-07-30
16.7%
n=6
2026-07-31
100%
n=1
2026-08-01
33.3%
n=6
2026-08-02
50%
n=10
2026-08-03
54.5%
n=22
2026-08-04
33.3%
n=6
2026-08-05
50%
n=8
2026-08-06
64.4%
n=59
2026-08-07
0%
n=3
2026-08-08
55.6%
n=18
2026-08-09
100%
n=1
2026-08-10
75%
n=4
2026-08-11

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. Los Angeles, Ca
    32.4%
    2.1d
    11136 late
  2. Newark, Nj
    63.9%
    9.2d
    3623 late
  3. Oakland, Ca
    47.1%
    1.8d
    178 late
  4. Baltimore, Md.
    71.4%
    2.2d
    1410 late
  5. Tacoma, Wa
    60%
    1.5d
    106 late
  6. Norfolk, Va.
    33.3%
    1.3d
    93 late
  7. Houston, Texas
    85.7%
    1.8d
    76 late
  8. Charleston, S.C.
    80%
    4.5d
    54 late
  9. Seattle, Wa
    0%
    50 late
  10. Miami, Florida
    25%
    1d
    41 late
  11. Long Beach, Ca
    0%
    40 late
  12. Savannah, Ga.
    100%
    3.3d
    33 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. Japan
    44.1%
    3.8d
    22097 late
  2. Thailand
    25%
    2d
    41 late
  3. Singapore
    100%
    1.5d
    22 late
  4. Cyprus
    100%
    5d
    11 late
  5. China
    0%
    10 late
  6. Indonesia
    100%
    2d
    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 →