ETA accuracy benchmark · 🇺🇸 New Orleans / Lower Mississippi
How Port Flow's predicted ETA compares to each vessel's own broadcast ETA at New Orleans / Lower Mississippi, measured on closed voyages over the last 90 days. We publish the number — good or bad. Lower error is better.
Port Flow predicted ETA (RMSE)
23.97 h
MAE 13.74 h · 12 voyages
Broadcast ETA (RMSE)
Building…
only 3 comparable voyages so far (need 20)
Gap
—
benchmark builds as more voyages close
Closed voyages
error = predicted/broadcast minus actual arrival (hours)| MMSI | Cargo | Arrival | Our error | Broadcast error |
|---|---|---|---|---|
| 636013521 | container | 06/26, 05:48 AM UTC | -16.32 h | -762.82 h |
| 538012009 | product | 06/25, 07:03 AM UTC | -1.99 h | — |
| 259099000 | container | 06/25, 04:54 AM UTC | -2.83 h | — |
| 636021440 | general-cargo | 06/21, 04:12 AM UTC | -4.91 h | -10.20 h |
| 477050800 | dry-bulk | 06/14, 11:12 AM UTC | 24.19 h | -104.20 h |
| 249189000 | container | 06/14, 08:59 AM UTC | -74.64 h | 6399.00 h |
| 248430000 | container | 06/11, 08:25 AM UTC | -6.50 h | — |
| 241613000 | product | 05/31, 05:13 AM UTC | 0.13 h | — |
| 538010227 | product | 05/31, 03:13 AM UTC | 16.21 h | — |
| 367342960 | chemical | 05/30, 01:33 PM UTC | 10.30 h | -24.56 h |
| 538007209 | container | 05/18, 11:15 AM UTC | -3.08 h | — |
| 352003298 | product | 05/15, 10:23 AM UTC | 3.80 h | — |
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How it's measured
- Predicted ETA: distance-to-berth over speed-made-good, refreshed on every AIS position, with a seasonal correction from rolling medians.
- Broadcast ETA: the crew-entered ETA in the vessel's AIS message — the de-facto industry default.
- Both are compared to the actual arrival timestamp on the same closed voyages. We report RMSE (penalises large misses) and MAE (typical error).
- Broadcast ETAs more than 7 days off are dropped as AIS sentinel / placeholder values, and our model is scored on that same set — so the comparison is honest, not cherry-picked.
- Coverage is public AIS only; ports with weak coverage show fewer closed voyages. We'd rather show a small honest sample than a big misleading one.