Two-day reach by warehouse location: the modeled US coverage study
Two warehouses on opposite coasts reach 51-81% of the contiguous-US population in two modeled ground days. Adding a Texas warehouse raises that to 66-98%. These are modeled ranges, not carrier quotes. If you're deciding where to hold stock, you can use the Cost Audit to compare the assumptions with your own shipment history.
The headline numbers
Our model puts New Jersey plus the West Coast node at 51-81% two-day reach today. With the Texas node added from November 1, the modeled reach is 66-98%. The conservative band is the lower number and the optimistic band is the upper number.
The network's modeled average zone is 4.19 today and 3.74 with Texas. The model reaches 100% of the contiguous-US population in five ground days for both networks. You'll see MODELED beside every figure because it uses distance and population, not a live carrier lookup.
A single warehouse origin compared with our network
| Seller origin | Modeled 2-day share alone | Average zone alone |
|---|---|---|
| Los Angeles | 16-24% | 6.57 |
| Dallas | 19-53% | 5.28 |
| Chicago | 37-73% | 4.93 |
| Atlanta | 39-75% | 5.07 |
| Salt Lake City | 18-32% | 6.23 |
| Knoxville | 46-75% | 4.97 |
| Memphis | 38-74% | 5.00 |
| Seattle | 5-18% | 7.01 |
| Miami | 10-33% | 5.98 |
| Columbus, Ohio | 50-72% | 4.94 |
MODELED. The range is conservative to optimistic. The average zone uses the nearest warehouse and the same contiguous-US population base as the study.
What one, two, and three warehouses change
| Warehouse count | Warehouse set | Modeled 2-day share | Modeled 5-day share | Average zone |
|---|---|---|---|---|
| 1 | East | 35-57% | 85-100% | 5.23 |
| 2 | East + West | 51-81% | 100-100% | 4.19 |
| 3 | East + West + Texas | 66-98% | 100-100% | 3.74 |
MODELED. East is New Jersey alone. The two-warehouse row is today's New Jersey plus Ontario network. The three-warehouse row is the network from November 1. Each range is conservative to optimistic.
What this means for Amazon SFP Extra Large
| Extra Large test | Threshold | East | East + West | East + West + Texas |
|---|---|---|---|---|
| Two-day page-view proxy | At least 25% | 35-57% | 51-81% | 66-98% |
| Five-day page-view proxy | At least 60% | 85-100% | 100-100% | 100-100% |
MODELED. Amazon's page-view metric is not the same as the Census population proxy used here, and the table does not promise a carrier delivery date.
How we built the model
We placed each warehouse and each ZIP area at its Census ZCTA centroid, measured the straight-line distance to the nearest node, and counted population inside conservative and optimistic ground-distance bands. We didn't model roads or carrier hubs. For two days those bands are 600 miles and 1,000 miles. We weighted every result by 2020 Census ZCTA population across the contiguous US, which means 48 states plus DC.
Average zone uses the study's standard ground bands: zone 2 through 150 miles, zone 3 through 300, zone 4 through 600, zone 5 through 1,000, zone 6 through 1,400, zone 7 through 1,800, and zone 8 beyond that. We assume every SKU is available at every node and each order leaves from the nearest node.
The study was checked October 13, 2026. It is MODELED from straight-line distance and Census population, not checked against a live UPS or FedEx lookup.
Limits you should keep beside the table
Real routes follow roads and carrier hubs. A ZIP near a band edge can land in a different carrier zone than the straight-line estimate, and the transit bands were tuned against published UPS maps rather than a live quote.
The model uses population as a page-view proxy. Prime page views can have a different geography, cut-off time, weekend behavior, holiday calendar, and product mix. A Friday order can also move differently from the same-day business-day assumption here.
Parcels of 50 lb or more can have Additional Handling or Large Package status, where UPS time guarantees do not apply. Rural centroids, delivery-area exceptions, remote ZIPs, and peak-season delays can move the real result. Inventory splits, stockouts, and cost-based routing can send an order farther than the nearest-node assumption.
Alaska, Hawaii, Puerto Rico, and other territories are outside the contiguous-US denominator and are not modeled in these ground figures. You can't read a zone drop as a statement about your shipping charges or savings. It's a distance result.
How to cite this data
How to cite this data: Two-day reach by warehouse location: the modeled US coverage study, https://www.shippingcow.com/guides/two-day-reach-by-warehouse-location, October 13, 2026, ShippingCow. If you're quoting a range, keep the MODELED label.
Use the model with your own shipment history
The model gives you a starting range. If you want to compare it with real lanes, send 30 recent shipments through the Cost Audit. We'll put the modeled warehouse question beside your actual origin and destination mix.
Questions
What is the modeled two-day reach with two warehouses? +
New Jersey plus the West Coast node reaches 51-81% of the contiguous-US population in two modeled ground days. The lower figure is the conservative band and the higher figure is the optimistic band.
How much does the Texas warehouse add in this model? +
Adding Texas to East plus West raises modeled two-day reach from 51-81% to 66-98%. It also lowers modeled average zone from 4.19 to 3.74.
Can one West Coast warehouse clear the SFP Extra Large two-day threshold? +
It can miss it. The West-only row is 16-24% in two modeled ground days, below the 25% Extra Large screen. East alone is 35-57% in this model and clears that screen.
Are these carrier delivery promises? +
No. They are modeled ranges from straight-line distance, published ground-distance bands, and Census population. They are not a live UPS or FedEx zone or time-in-transit lookup.
Why is population standing in for Prime page views? +
The source study needed a consistent national denominator, so it used 2020 Census ZCTA population across the contiguous US. Prime page views can have a different mix, and the model does not include those account-level patterns.
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