Transit times / Venus Group Management Inc

Venus Group Management Inc

238 ocean import shipments. Delayed 21.3 points more often than the dataset average of 43.8%.

238
Shipments
65.1%
Arrived late
155 shipments
3.3 days
Average delay, when late
median 2 days
12 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.

11
4.6%
Early
72
30.3%
On time
112
47.1%
1–3 days
26
10.9%
4–7 days
17
7.1%
8–14 days
0
0%
15+ days

By carrier

All 10 carriers used.

% delayed avg days late, when laten = shipments
  1. CMA CGM
    85.5%
    2.8d
    7665 late
  2. OOCL
    71.4%
    4.9d
    4230 late
  3. Wan Hai Lines
    73%
    3.9d
    3727 late
  4. Evergreen
    40%
    1d
    2510 late
  5. Yang Ming
    33.3%
    4.1d
    217 late
  6. MSC
    50%
    3.7d
    189 late
  7. ONE
    9.1%
    1d
    111 late
  8. YJIF
    80%
    1.5d
    54 late
  9. PLKQ
    100%
    3d
    22 late
  10. ZTIL
    0%
    10 late

By route

Top 12 of 22 lanes; 12 shipments across the remaining 10 not shown.

% delayed avg days late, when laten = shipments
  1. Yantian > Los Angeles, Ca
    60.9%
    1.8d
    6439 late
  2. Yantian > Long Beach, Ca
    27.3%
    1.6d
    339 late
  3. Yantian > Newark, Nj
    87.5%
    4.1d
    3228 late
  4. Ning Bo > Long Beach, Ca
    92%
    2.8d
    2523 late
  5. Qingdao > Los Angeles, Ca
    17.6%
    2d
    173 late
  6. Shekou > Los Angeles, Ca
    100%
    2.3d
    1616 late
  7. Qingdao > Long Beach, Ca
    100%
    5d
    1010 late
  8. Ning Bo > Newark, Nj
    100%
    9.3d
    88 late
  9. Ning Bo > Los Angeles, Ca
    42.9%
    2d
    73 late
  10. Shekou > Houston, Texas
    50%
    1d
    63 late
  11. Yantian > Savannah, Ga.
    20%
    11d
    51 late
  12. Qingdao > Newark, Nj
    100%
    7d
    33 late

By supplier

Top 12 of 117 suppliers; 148 shipments across the remaining 105 not shown.

% delayed avg days late, when laten = shipments
  1. Foshan Aoyinghui Trade Co Ltd
    12.5%
    2d
    162 late
  2. Dongguan Ruihao Smart Home Co Ltd
    100%
    2d
    1111 late
  3. Guangzhou Elov Cosmetics Co Ltd
    88.9%
    3.4d
    98 late
  4. Yiwu Hongjin E Commerce Co Ltd
    75%
    2d
    86 late
  5. Shenzhen Bjt Technology Co Ltd
    62.5%
    5.2d
    85 late
  6. Hong Kong Ztotop Industrial Co Ltd
    42.9%
    1.7d
    73 late
  7. Luoyang Makeace Import&Export Co
    33.3%
    12d
    62 late
  8. Hozio Service Co Ltd
    100%
    7.3d
    66 late
  9. Luoyang Makeace Import & Export
    33.3%
    5d
    62 late
  10. Ubrand Tianjin Technology
    100%
    1.4d
    55 late
  11. Yiwu Gehongshang Trade Co Ltd
    50%
    3.5d
    42 late
  12. Shenzhen Youqing Technology Co Ltd
    75%
    6.7d
    43 late

By vessel

Vessel names are in the most recent data only — 238 of 238 shipments (100%) name one, across 56 ships. This chart covers that subset, not the whole.

% delayed avg days late, when laten = shipments
  1. Cma Cgm Syracuse
    88.9%
    2d
    2724 late
  2. Esl Nhava Sheva
    100%
    1d
    1212 late
  3. One Singapore
    100%
    2d
    1111 late
  4. Cscl Summer
    100%
    2d
    1010 late
  5. Cscl Bohai Sea
    100%
    5d
    1010 late
  6. Msc Branka
    0%
    80 late
  7. Cma Cgm Amazon
    0%
    70 late
  8. Oocl Tulip
    71.4%
    6d
    75 late
  9. Mol Experience
    0%
    60 late
  10. Cosco Shipping Orchid
    100%
    7.5d
    66 late
  11. Conti Conquest
    50%
    2d
    63 late
  12. Oocl Magnolia
    100%
    7d
    66 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.

62.5%
n=32
2026-07-27
66%
n=47
2026-07-28
100%
n=7
2026-07-29
100%
n=19
2026-07-30
0%
n=1
2026-07-31
100%
n=14
2026-08-01
0%
n=10
2026-08-02
66.7%
n=9
2026-08-03
52.2%
n=23
2026-08-04
91.7%
n=12
2026-08-05
83.3%
n=12
2026-08-06
100%
n=6
2026-08-07
76.5%
n=17
2026-08-08
5.3%
n=19
2026-08-09
28.6%
n=7
2026-08-10
100%
n=3
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
    59%
    1.9d
    10562 late
  2. Long Beach, Ca
    62.3%
    3d
    6943 late
  3. Newark, Nj
    91.1%
    5.6d
    4541 late
  4. Houston, Texas
    60%
    2.7d
    106 late
  5. Savannah, Ga.
    42.9%
    7.3d
    73 late
  6. Oakland, Ca
    0%
    10 late
  7. Miami, Florida
    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
    68.2%
    3.3d
    220150 late
  2. Grenada
    23.5%
    3.5d
    174 late
  3. Norway
    100%
    8d
    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 →