Understanding fpl price changes: live data and predictions
Introduction: Why fpl price changes matter
Price movements in Fantasy Premier League (fpl price changes) influence transfer decisions, team value and captaincy planning for managers. Small movements of £0.1 can compound across a squad, so tracking likely rises and falls helps managers plan transfers, wildcards and chip use.
Main body: How changes are predicted and recent data
How price changes work
In principle, FPL price changes are driven by net transfers in or out of players. Price falls happen in £0.1 steps when net transfers are below a certain ownership-derived threshold. The precise counting method used in the official algorithm is not fully public, so third‑party predictors must estimate the probability that each published transfer will count toward a move.
Recent snapshots from LiveFPL and FPLedits
Third‑party services publish live predictions to help managers. LiveFPL’s Price Change Predictor shows player-level indicators: for example, Rogers (MID, £7.7, Aston Villa) is listed with values including -45.62% and -37.03% (>2 days), a short-term change of +0.44% and an associated figure of 47. Wirtz (MID, £8.3, Liverpool) is shown with -21.2% and -31.46% (>2 days), a short-term change of -0.53% and an associated 382. LiveFPL also presents price ladders for clubs — a Newcastle set of entries shows repeated £6.6–£7.3 bands changing incrementally across dates.
Daily reported movements and examples
FPLedits publishes daily price‑change summaries. For 30 January 2026 they recorded entries such as 2.0% • £4.6m • FWD, 38.8% • £7.0m • DEF and 35.9% • £7.3m • FWD, alongside many other percentage indicators across positions. Earlier entries (29–31 January 2026 and 28 January highlights) similarly list varying probabilities and price points, illustrating volatility day to day.
Notable inconsistencies
Predictors note anomalies: for instance, Solanke experienced heavy transfers out yet avoided a price fall for several days — a behaviour that appears inconsistent with algorithm‑driven expectations and underlines the uncertainty around exact counting methods.
Conclusion: What this means for managers
Given algorithmic opacity and short‑term volatility, managers should use multiple predictors (LiveFPL, FPLedits and others), monitor ownership levels and transfer trends, and treat price forecasts as probabilities rather than certainties. Keeping an eye on daily summaries and unusual cases like Solanke can help inform transfer timing and protect team value over a season.
