Why We Don't Put J2 Per-90s Next to Pro League Numbers

The short answer

A per-90 number describes what a player produced in a specific league, for a specific team, against specific opponents. Moving that number to another league without adjustment treats all of that context as if it did not exist. We do not do that, and this page explains why.

Every figure on Far Post Analytics is presented as a J-League figure, ranked against a J-League pool. When a report discusses how a player might translate to a European league, that discussion is written as a qualitative judgement with its limits stated, not as a converted number.

What a per-90 actually measures

Per-90 scaling solves one problem: it lets a player with 1,200 minutes be compared with a player with 2,800 minutes on the same footing. It does not solve the problem of context. A per-90 is still a rate of output inside one competitive environment.

That environment includes the quality of opposition, the share of the ball the player's team usually has, the role the coach assigns him, and the game states he typically plays in. Change any of those and the rate changes, even if the player does not.

Four reasons a J2 number does not travel unadjusted

Opponent quality. Output against J2 defences is not interchangeable with output against Pro League, Eredivisie or Primeira Liga defences. The direction of the adjustment is usually downward for attacking output, but the size of it varies by position and by player type.

Team context. A full-back in a J2 side that controls possession will record more progressive actions than the same player would in a side that defends deep. Many J-League-to-Europe moves are also moves from a dominant team to a mid-table or lower team, which changes the volume of actions available.

Role and game state. Players who spend long periods in leading or trailing game states accumulate different kinds of actions. A number built mostly in one game state can overstate or understate what the player does in the other.

Sample size. Below roughly 900 minutes, per-90 figures move too much on single matches to support conclusions. We omit per-90 tables for players under that threshold and say so in the article, rather than publishing a table that looks more certain than it is.

What we do instead

FPA Score is a weighted composite of three components: Production, AgeScore and Availability. Its percentiles are calculated within our J-League player pool, not against European leagues. A high FPA Score means a player stands out relative to J-League peers; it is not a claim about where he would rank in Belgium or England.

Football LAB Chance Building Point (CBP) data is our main layer for chance-creation and build-up contribution. Football LAB publishes rankings but not the full size of the ranked pool, so we present CBP positions as rank-based indices, not true percentiles. Where a visual bar is shown, the assumed pool is labelled.

Every table carries a data vintage. Our current per-90 layer is built on the 2024 J1, J2 and J3 seasons. When a report is written after that season, the gap between the data and the player's present situation is stated in the report, not left for the reader to discover.

Where a figure is not available from our sources, we write 'Data not available'. We do not estimate missing values to complete a table.

Why we do not publish a single conversion coefficient

A common shortcut is to multiply a smaller league's figures by one league-strength factor. We do not publish such a factor for three reasons.

First, a single coefficient implies a precision that the underlying evidence does not support. The translation of output between leagues differs by position and by action type; one number hides that variation.

Second, most public league-strength ratings measure team strength. They are useful for comparing competitions, but they were not built to translate an individual full-back's progressive carries or a forward's shot volume from one league to another.

Third, our own evidence base is still small. Our internal dataset of first moves from the K League and J-League to Europe currently holds fewer than 30 recorded cases. That is enough to study patterns descriptively. It is not enough to estimate reliable translation factors, and we will not present it as if it were.

How to read our numbers as a recruiter

Treat a strong FPA Score or CBP ranking as a reason to watch a player, not as a projection of his output abroad. Our reports are written to shorten a watch list, not to replace live or video scouting.

Check the minutes and the data vintage before the percentile. A high rank on a small or old sample carries less weight than a moderate rank on a full, recent season.

Read the role context in each report. A player whose numbers depend on his team dominating the ball is a different recruitment case from one whose output holds in a low-possession side.

Use the Risk flags section. League adaptation, work-permit rules and contract timing are listed there because they decide whether a statistically interesting player is a realistic target.

What would change this approach

If we introduce a league adjustment, it will be published on the Methodology page with its inputs, its version number and the date it took effect. Earlier reports will keep the figures they were published with, so that our Track Record remains checkable against what we actually said at the time.

Sources and disclosure

Base match statistics: API-Football, J1/J2/J3 2024 seasons. Chance-creation metrics: Football LAB (football-lab.jp), Chance Building Point rankings, pool size not published. Market value and transfer history, where referenced in our reports: Transfermarkt and Soccerway, treated as third-party estimates, not club-confirmed figures.

Far Post Analytics is an independent analysis publication. We do not represent players, clubs or agents, and nothing on this site is an offer to broker a transfer.