Exporting Player Data for a Second Opinion

Why Exporting Data Changes How You Think

Football Manager's interface is designed around one player at a time. You open a profile, read a scout report, check the attributes screen, close the window. That workflow is fine for casual browsing, but it is poorly suited to the question most managers actually need to answer: how does this player compare to everyone else in my shortlist? Or: which of my squad's center-backs will still be first-choice in two years?

Those are set-comparison questions, and they require seeing multiple players side by side with consistent columns. The moment you export player data into a flat format — a CSV, an HTML table — those comparisons become trivial. You can sort by any attribute, filter by age, rank by role suitability, and spot the outliers the in-game interface buries under click paths.

This is the same instinct real-world clubs apply when their analysts export match data into a spreadsheet before a recruitment meeting. The game already gave you the information; the export just lets you think about it more clearly.

Method 1: The Built-in Print Screen Export

FM26 includes a native, no-install way to get a structured snapshot of any player list. On any squad screen, shortlist, or player search results page, open the game's dropdown menu and select Print Screen. The game saves the currently visible columns as an HTML file to your Football Manager documents folder — typically Documents\Sports Interactive\Football Manager 2026 on Windows.

That HTML file opens in a browser and pastes cleanly into Google Sheets or Microsoft Excel. The key variable is which columns you have displayed before you trigger the export. Spend a few minutes setting up a custom view first: right-click the column header bar to add, remove, or reorder attributes. The export captures exactly what is on screen — no more, no less — so the value of the snapshot is entirely determined by how thoughtfully you configured the view beforehand.

As the community at the Sports Interactive forums has documented, FM26 removed a dedicated export button that existed in earlier versions, which made Print Screen the primary native route. The limitation is that it only captures what fits in the visible list at export time — it does not auto-scroll through hundreds of results.

Method 2: The FM26 Player Export Plugin

For anything beyond a single squad page — full player database searches, long shortlists, league-wide comparisons — the community has built a more capable solution. The FM26 Player Export plugin, available free from FM Scout and Sort It Out SI, is a BepInEx mod that intercepts the game's player list rendering and writes every row to a CSV file automatically.

The practical difference from Print Screen is auto-scrolling. When you press the plugin's hotkey — F9 in the current v4 release, with Ctrl+P also supported — the plugin scrolls through the entire list on your behalf, capturing every player regardless of list length. A search returning five hundred players takes a few seconds longer than a squad of twenty, but both are handled without manual intervention.

The exported CSV filename includes a timestamp (for example, player_export_20260415_143200.csv) and lands in the same Football Manager documents folder as the Print Screen output. When importing into Excel or Google Sheets, choose semicolon as the delimiter. The columns in the file mirror whatever view you had active before triggering the export, which means the custom-view setup discipline from Method 1 applies here too.

One important note: the plugin reads and exports data the game already shows you — it does not reveal hidden attributes or alter the save file. Always download from the original trusted sources listed above rather than from re-upload sites.

Designing a View Worth Exporting

The quality of analysis downstream is determined by the columns you included upstream. Think about the question you want to answer before you configure the view. For a recruitment comparison, include name, age, club, position, nationality, preferred foot, ability stars, potential stars, contract expiry, and the key technical attributes for the target role. For a squad depth review, prioritise current ability, injury status, preferred roles, and contract length — you are looking for coverage gaps and succession risk, not granular attribute detail.

The Essential FM26 Views guide at FM Scout offers a starting point with pre-built column sets for squad, scouting, and tactics screens that the community has refined over multiple editions. Importing one of those views and then exporting from it is faster than building from scratch, and it gives your CSV a consistent schema you can reuse across windows.

Using Exported Data for Structured Analysis

Once you have a CSV or HTML table, the next step is interpretation — and this is where the investment pays off. In a spreadsheet, you can calculate derived columns: age-to-potential gap, weeks remaining on a contract, or a simple weighted sum of the attributes you care most about for a given role. Sort by any of those columns and shortlist candidates float to the top without any manual cross-referencing.

Dedicated community tools extend this further. Football Manager Data Lab accepts exported player views and produces interactive dashboards with role scoring, squad coverage maps, and moneyball-style value analysis. The workflow is straightforward: import their custom views into FM26, export from those views using Print Screen or the plugin, then upload the resulting file. The tool does the analytical heavy lifting.

AI assistants can also add genuine value here, provided the input is clean and structured. Paste a well-formatted table and ask a focused question: which of these central midfielders has the highest combined Passing and Vision but costs under 10,000 per week? The quality of the answer depends entirely on the quality of the data you feed it — keep the table tidy with consistent column headers and one player per row. FM Dossier's Scout and Full player views export a clean schema with role-fit percentages and positional context already included, which reduces cleanup before passing the data to any analysis tool.

What Exports Cannot Tell You

Responsible use of exported data means understanding its limits clearly. Any snapshot captures visible attributes — the numbers on the profile page. It does not capture hidden attributes: Consistency, Professionalism, Injury Proneness, Important Matches, or any of the personality traits that shape how a player develops and performs under pressure. As Sort It Out SI's hidden attributes guide explains, those values exist in the game's simulation but are deliberately not surfaced in the standard interface to preserve realism. They only become visible through the in-game editor DLC or through the written commentary in scout and coach reports.

This matters practically. A player who looks exceptional in a spreadsheet may carry hidden flags — low Consistency, high Injury Proneness — that a number-only export cannot reveal. Always cross-reference strong spreadsheet candidates against their scout report prose before committing budget. And remember that star ratings are squad-relative: a five-star player in a mid-table Championship save is not the same as a five-star player at a Champions League contender. Treat exported data as a filtering layer, not a final verdict — it narrows your shortlist from hundreds to a manageable handful, and the final call still belongs to the scout report and your read of tactical fit.

Keeping It Clean and Consistent

Use consistent view configurations so that files from different points in the season share the same column schema. Date-stamp your files — the plugin handles this automatically; Print Screen exports do not. And if you share exports with a co-op save group or online community, be transparent about which view you used. A comparison built from scouting-knowledge-limited star ratings will not tell the same story as one built from full-knowledge data. Context is not optional — it is what separates a data-driven decision from a number-driven mistake.