Reading club accounts
Our financial figures come straight from accounts filed at Companies House, read from the original documents. Most clubs file in the iXBRL format, a machine-readable version of the accounts, and we parse the relevant figures directly from it: turnover, wage costs, net debt, profit or loss, and the going-concern note.
Some clubs file on paper or as scanned PDFs. For those we extract the figures and check them by hand against the document. Where a club files abridged accounts that leave a figure out, we mark it undisclosed. Each finance page shows the filing year it draws on.
PSR Watch
The Premier League's Profit and Sustainability Rules cap losses at £105m over three reporting years. PSR Watch tracks each club's rolling three-year pre-tax result against that cap.
We use the headline pre-tax figure from the filed accounts. The official PSR test allows clubs to deduct spending on youth, women's football, infrastructure and community work, and those deductions are not disclosed publicly. So our number is deliberately conservative: a club's real PSR position is usually healthier than the headline we show. We treat the figure as an exposure indicator that flags risk.
Debt League
Net debt is total borrowings minus cash, taken from the most recent filed accounts. We include bank loans, bonds and amounts owed to parent or group companies, because owner loans are still money the club owes. A club funded by interest-free owner loans carries real debt on this measure even if the terms are soft, and we note that distinction where the accounts make it clear.
Sack-o-Meter
The Sack-o-Meter ranks managers by how much pressure they are under right now. It weighs recent results, where the team sits against where its resources say it should sit, the run of fixtures just gone, and how long the manager has been in post.
A manager overperforming a small budget scores calm even after a couple of losses. One underperforming an expensive squad scores hot even mid-table. It is a read on the temperature around a job, drawn from form and expectation, and it carries no inside information.
Race Watch
Race Watch answers "how likely is this?" by playing the rest of the season out thousands of times. For each remaining fixture we estimate a result from current form and relative strength, then simulate every game to the end of the campaign. Do that many thousands of times and count how often each club finishes champion, goes up, makes the play-offs or goes down.
This is a Monte Carlo simulation. A club shown with a 30% promotion chance went up in roughly 30 of every 100 simulated seasons. The probabilities move as real results come in, so the picture sharpens as the season runs down.
Predictability
This measures how often a division throws up the unexpected. We compare actual results against what form and table position would predict, then aggregate the surprises across the league. A division where favourites keep slipping up scores as less predictable. It is a way of putting a number on the old line about a division where anyone can beat anyone.
Rumour source scores
Not every transfer report is worth the same. We log transfer claims against the journalist or outlet that made them, then reconcile them against deals that actually happen, using confirmed Sportmonks data. Over time that builds a hit rate per source: how often their reported moves come off. The score is built on a track record we can show.
What these numbers cannot tell you
Data has edges, and we name them. Filed accounts are historic, often a year or more old by the time they appear. Simulations describe odds, never certainties. Source scores describe the past, and the next report is its own question. Where a figure is uncertain or undisclosed, we mark it as such on the page.
Spotted something that looks wrong? Tell us through corrections and we will check it.