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The POST /get_future_transfer_value endpoint predicts what a player will be worth at transfer time after a 3-year simulation period. SquadAssist finds comparable historical players — matched on attributes such as rating, potential, position, and club reputation — and projects the player’s future value based on how those peers evolved. This endpoint covers the future transfer fee component of the full ROI analysis; you can use it in isolation or as part of your own valuation pipeline. For the complete ROI picture including on-field impact, use POST /get_roi_analysis instead.
The simulation always uses the 2025/2026 season as the starting point and projects 3 years forward. Season and simulation length are not yet request parameters. Reach out in case this is of importance.

Request

The request body must be a JSON object.
string
required
The SquadAssist player ID. Use POST /query_player to look up the ID from a Transfermarkt or Wyscout ID.
string
required
The SquadAssist club ID for the club the player would be joining. The club’s reputation and league context influence the prediction. Use POST /query_club to look up the ID.
number
The current transfer fee in the currency specified by currency_code. This serves as the baseline value for the prediction. If omitted, SquadAssist calculates an expected fee automatically.
string
An ISO 4217 currency code (e.g. EUR, GBP, USD). The expected_transfer_value input is interpreted in this currency, and all monetary output values are returned in this currency alongside their EUR equivalents. Defaults to EUR.

Response

string
The ISO 4217 currency code for all non-EUR monetary values in the response.
integer
The predicted market transfer value at the end of the 3-year simulation, in the requested currency.
integer
The predicted market transfer value at the end of the 3-year simulation, in EUR.
string
A category summarising the predicted value trajectory. One of: "Elite Prospect", "Excellent Opportunity", "Steady Grower", "Stable Value", "Decline", or "Major decline".
object
A probability distribution across all six outcome categories, based on how comparable historical players performed.
object
Explanatory data about the prediction.

Example

Errors