Transit times / Walong Marketing Inc

Walong Marketing Inc

138 ocean import shipments. Delayed 12 points more often than the dataset average of 43.8%.

138
Shipments
55.8%
Arrived late
77 shipments
3.9 days
Average delay, when late
median 2 days
13 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.

6
4.3%
Early
55
39.9%
On time
49
35.5%
1–3 days
17
12.3%
4–7 days
11
8%
8–14 days
0
0%
15+ days

By carrier

All 10 carriers used.

% delayed avg days late, when laten = shipments
  1. Evergreen
    23.6%
    1d
    5513 late
  2. OOCL
    92.6%
    4.8d
    5450 late
  3. Yang Ming
    33.3%
    1.6d
    155 late
  4. CMA CGM
    80%
    1.5d
    54 late
  5. Wan Hai Lines
    100%
    4.5d
    22 late
  6. Orient Express Container
    0%
    20 late
  7. AMEH
    100%
    5.5d
    22 late
  8. RSLC
    100%
    10d
    11 late
  9. OOCO
    0%
    10 late
  10. KFUN
    0%
    10 late

By route

Top 12 of 38 lanes; 48 shipments across the remaining 26 not shown.

% delayed avg days late, when laten = shipments
  1. Kaohsiung > Newark, Nj
    63.2%
    1.5d
    1912 late
  2. Kaohsiung > Los Angeles, Ca
    0%
    150 late
  3. Laem Chabang > Newark, Nj
    100%
    7.3d
    99 late
  4. Yantian > Oakland, Ca
    14.3%
    1d
    71 late
  5. Laem Chabang > Long Beach, Ca
    100%
    2.4d
    77 late
  6. Yangshan > Newark, Nj
    100%
    6.6d
    77 late
  7. Yantian > Long Beach, Ca
    50%
    4d
    63 late
  8. Kaohsiung > Oakland, Ca
    40%
    2.5d
    52 late
  9. Yantian > Newark, Nj
    100%
    5d
    44 late
  10. Hong Kong > Newark, Nj
    100%
    6.3d
    44 late
  11. Kaohsiung > Long Beach, Ca
    100%
    1.8d
    44 late
  12. Taipei > Los Angeles, Ca
    0%
    30 late

By supplier

Top 12 of 67 suppliers; 79 shipments across the remaining 55 not shown.

% delayed avg days late, when laten = shipments
  1. Taiwan Wachine Co Ltd
    22.2%
    4.5d
    92 late
  2. Shanghai Wachine Trade Company Li
    83.3%
    6.6d
    65 late
  3. Universal Rice Co Ltd
    83.3%
    5.4d
    65 late
  4. Nutri Asia Inc
    20%
    1d
    51 late
  5. Sing Lin Foods Corp
    60%
    3d
    53 late
  6. I Mei Foods Co Ltd
    25%
    1d
    41 late
  7. Feng Shou Hong Limited
    25%
    3d
    41 late
  8. Ksf Beverage Holding Co Ltd
    50%
    5.5d
    42 late
  9. Shanghai Wachine Trade Co Ltd
    0%
    40 late
  10. Firm Honor Corp
    100%
    1.8d
    44 late
  11. Fuzhou Aurora Import & Export
    75%
    1d
    43 late
  12. Shanghai Zhoushi Foodstuffs Co Lt
    100%
    9.3d
    44 late

By vessel

Vessel names are in the most recent data only — 138 of 138 shipments (100%) name one, across 43 ships. This chart covers that subset, not the whole.

% delayed avg days late, when laten = shipments
  1. Ever Mild
    0%
    170 late
  2. Oocl Tulip
    100%
    6d
    1010 late
  3. Taurus
    0%
    90 late
  4. Taipei Triumph
    100%
    2.1d
    99 late
  5. Ever Muse
    100%
    1d
    88 late
  6. Ever Memo
    16.7%
    3d
    61 late
  7. Ever Loyal
    0%
    50 late
  8. Ever Favor
    40%
    1d
    52 late
  9. Xin Fei Zhou
    0%
    50 late
  10. Oocl Magnolia
    100%
    10d
    55 late
  11. Cma Cgm J. Madison
    100%
    2.3d
    44 late
  12. Zeal Lumos
    33.3%
    10d
    31 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=28
2026-07-27
50%
n=4
2026-07-28
100%
n=6
2026-07-29
54.5%
n=11
2026-07-30
37.5%
n=8
2026-07-31
92.3%
n=13
2026-08-01
0%
n=3
2026-08-02
25%
n=4
2026-08-03
21.7%
n=23
2026-08-04
16.7%
n=6
2026-08-05
33.3%
n=3
2026-08-06
83.3%
n=6
2026-08-07
25%
n=12
2026-08-08
33.3%
n=3
2026-08-09
33.3%
n=6
2026-08-10
50%
n=2
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. Newark, Nj
    81.5%
    4.5d
    5444 late
  2. Los Angeles, Ca
    13.8%
    4.3d
    294 late
  3. Long Beach, Ca
    69.2%
    3.6d
    2618 late
  4. Oakland, Ca
    38.1%
    1.8d
    218 late
  5. Baltimore, Md.
    0%
    40 late
  6. Norfolk, Va.
    100%
    1.7d
    33 late
  7. Honolulu, Hawaii
    0%
    10 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. China
    66.7%
    4.5d
    5134 late
  2. Taiwan
    47.4%
    2.1d
    3818 late
  3. Thailand
    76%
    4.7d
    2519 late
  4. Vietnam
    33.3%
    2d
    62 late
  5. Philippines
    0%
    50 late
  6. Hong Kong S.A.R.
    25%
    10d
    41 late
  7. South Korea
    0%
    30 late
  8. Malaysia
    33.3%
    1d
    31 late
  9. Panama
    0%
    10 late
  10. Grenada
    100%
    1d
    11 late
  11. Japan
    100%
    1d
    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 →