The Championship is the division where last season's table is least use - here is what the squads say instead

Last season's Championship table tells you nothing about this season. I checked: across 123 club-seasons since 2020/21, a club's points per game last season (adjusted for which division it earned them in) correlate -0.07 with what the same club does the following season. Not weakly positive. Nothing, and if anything faintly negative.

That is much worse than the divisions below it. In League One the same correlation is +0.17 and in League Two +0.33. The Championship is the division where the table you just watched is least use for the one about to start, which makes sense once you look at what walks through the door every summer: three clubs down from the Premier League with parachute money, three up from League One, and a squad churn nobody else in England has to absorb.

So I built the projection from the other end. Every one of the 731 players registered with the 24 clubs this week, what each of them did last season, and in which division he did it.

The hard part is that a good season in one division is not a good season in another, and you cannot add players up until you know the exchange rate. I did not assume it. There are 8,624 players in my data who moved and were therefore rated in two divisions in consecutive seasons, and fitting all those moves at once puts every division on one scale.

Anchored at League One = 0, in standard deviations of player rating: the Premier League +1.46, La Liga +1.18, the Bundesliga +1.07, Serie A +1.03, Ligue 1 +0.84, the Championship +0.61, the Scottish Premiership +0.02, League Two -0.27, the Eerste Divisie -0.36. A separate term in the same fit absorbs whatever a player loses simply by changing clubs, so that common effect is not blamed on the divisions.

Five squad-level inputs go into the projection, with weights fitted on 362 club-seasons from the Championship, League One and League Two, and tested by holding out one whole season at a time so nothing is ever scored on data it was fitted on. The error comes out at 10.5 points over a 46-game season, against 11.8 points for giving every club the division average and 15.0 for assuming last season repeats. Correlation with what actually happened is 0.46.

Be blunt about the size of that. Beating the division average by 1.3 points is a real edge (paired t-test, p = 0.023) and a small one. Only 58 per cent of clubs land inside their own band. In 2021/22 the model was fractionally worse than simply giving everyone the average. It has no systematic bias, and the calibration slope is 1.06 with a standard error of 0.19, so it is not tilted, but its spread is much narrower than a real table: the projections have a standard deviation of 6.6 points where real Championship seasons have 15.4. It will never produce a 100-point champion or a 30-point bottom club, and it is not trying to.

Where it lands. Southampton project 77 points, West Ham 75, Middlesbrough 74, Millwall 72, Wolves 71. At the bottom, Charlton 48, Bolton 52, Cardiff 53, Portsmouth 55, Blackburn 56. The whole range is 28 points and the error on any one club is 11, which is why those are bands rather than places.

The interesting cases are all newcomers, in both directions.

Lincoln won League One with 103 points and project 60 here, in the bottom half. Cardiff came up with 91 and project 53. Bolton came up through the play-offs on 75 and project 52. Promotion form and a Championship squad are not the same thing, and between 95 and 100 per cent of the minutes those three squads carry were played in divisions my scale rates below this one.

Going the other way: Wolves were relegated from the Premier League on 20 points and project 71, near the top. Burnley went down on 22 and project 63. West Ham went down on 39 and project 75. The model does not know anything about how bad last season was for them; it reads the players who are registered today, and between 68 and 93 per cent of the minutes in those squads were played in the Premier League itself.

Across the whole division, the players registered here carry 10,313 full games of measured football from last season: 69 per cent of it played in the Championship, 15 per cent in League One, 7 per cent in the Premier League and the rest scattered from the Eredivisie to Serie A.

The honest limitations. 219 of the 731 registered players have no measured season in my data at all, mostly academy players and arrivals from divisions I do not cover, so a chunk of every squad list is invisible to the model. The same model run on goals rather than points is a null result in this division: 0.209 of a goal per game of error on goals scored against a 0.224 baseline, and 0.191 against 0.201 on goals conceded, which is to say a squad list tells you roughly where the points land and almost nothing about how they get there. And the window is still open, so every one of these squads will change.

Every club's number, what pushed it up or down, the full division ladder, the backtest table and the club-by-club breakdown are here: https://goalsoon.com/championship-2627-model.html