What is it?
The average of FreightWaves’ proprietary algorithm designed to predict and portray buy side (shipper/broker to carrier) van spot market linehaul rates of over 750,000 lanes in the U.S., excluding lanes under 250 miles in length The algorithm ingests multiple data points, including but not limited to tender data, operational costs, and demographic information and projects them 28 days into the future.
These rates are available for both van (FWS) and reefer (FWSR) modes and will have a historical predictive value available for 7 (FWS7/FWSR7) and 28 (FWS28/FWSR28) days out. This will enable the user to see the historical accuracy over time of the predictive algorithm based against the actual value.
In addition to the straight average, there is also a weighted average calculation for national van rates (FWSW), which weights each lane’s value based on volume derived from tender data.
FWS.USA – National scientific van rate with a 28-day prediction. (Note: Every value after the previous day’s date is predicted and subject to daily fluctuations until the day arrives.)
FWS7.USA, FWS28.USA – Historical predicted values for the 7- and 28-day van rates. These are static representations of the predicted rates that will not change, unlike the predicted values in FWS.USA
Take the above graphic for example:
- On February 4, the predicted national rate value for February 11 (7-days in the future) was $2.06/mile.
- The actual observed value ended up being $2.02/mile.
FWSR.USA – National scientific reefer rate with a 28-day prediction.
FWSR7.USA, FWSR28.USA – Historical predicted values for the 7- and 28-day reefer rates.
FWSW.USA – The weighted average of the scientific rates. This average is weighted based on volume derived from tender data. It values lanes with higher volumes more than lower volume lanes.
Who is interested?
Freight Brokers, Pricing Managers, Transportation Managers, Shippers, Financial Analysts, Company Executives, Industry Experts, Owner Operators
What does it tell me?
These rates provide a predictive outlook for national spot rate movement over a 28-day period as well as provide a historical view how market conditions have changed. Knowing if spot rates are expected to climb or decline can help users make more accurate decisions for either acquiring or pricing capacity in the near-term.
Variances in the predicted values can also help users identify and explain market anomalies when the market diverges rapidly from expectations formed from the market information available up to month ahead of execution.
Historical data provides insight into how the market has behaved over time, which can assist in either benchmarking or validating decisions related to securing or selling truckload capacity.