How FPL price changes moved in January–February 2026

Introduction: why fpl price changes matter

Price changes in Fantasy Premier League (fpl) alter player values and can force managers to use funds or miss transfers. Understanding these moves helps with squad planning, captaincy decisions and chip timing. Recent data from LiveFPL and FPLedits highlights both predictable patterns and puzzling events, underlining the value of monitoring multiple predictors.

Main body: mechanisms, recent data and examples

How price changes are driven

In principle, FPL price changes result from net transfers in or out of a player across the game. Price falls typically happen in small steps (often -£0.1) when net transfers fall below a threshold relative to ownership. However, the exact algorithm is not fully public and predictors must estimate the probability that each published transfer will be counted towards a change. Wildcard use and transfer volumes complicate predictions.

LiveFPL and FPLedits snapshots

LiveFPL’s predictor pages show live ranks, ownership and several percentage indicators. Examples from the feed include Rogers (MID, £7.7, Aston Villa) with figures -45.62% and -37.03% (>2 days), a short-term +0.44% and a live rank of 47. Another listed line shows Wirtz (MID, £8.3) with -21.2% and -31.46% (>2 days), a -0.53% recent change and rank 382. The LiveFPL tool also chronicles price steps for clubs such as Newcastle, showing sequential price points from £6.6 up to £7.3, and historical entries such as C. Jones (Liverpool) moving from £5.5 to £5.4 on 2025-08-23.

FPLedits daily changes and anomalies

FPLedits’ daily logs for late January–early February 2026 list numerous percentage signals and price points. For example, entries on Friday 30 January include 2.0% • £4.6m • FWD and 38.8% • £7.0m • DEF; 29 January records include 24.3% • £6.1m • MID and 22.7% • £5.7m • DEF; 28 January shows 14.9% • £8.4m • MID. Observers also noted anomalies: Solanke experienced heavy transfers out yet avoided a price fall for several days, an outcome that appeared inconsistent with other algorithm-driven changes.

Conclusion: what managers should take from this

Price-change predictors provide useful signals but are inherently probabilistic because the FPL algorithm and transfer-counting rules are not fully transparent. Managers should follow multiple sources (LiveFPL, FPLedits and in-game indicators), watch ownership and transfer surges near deadlines and treat single anomalies—like Solanke’s delayed fall—as reminders to avoid overreliance on any one tool. In practice, combining live predictor outputs with transfer-volume awareness can reduce the chance of unexpected value loss and improve transfer planning.