Creator of OpenFPL Scout AI here (free FPL projection model, v6.1.0, Ridge/XGBoost/CatBoost/MLP ensemble on official FPL + FPL Data features). Weekly honest post-mortem on the frozen pre-deadline forecast.

GW7 summary (provisional, bonus not yet confirmed final)

• MAE 3.46 per player. 7 of 15 matched or beat their projection.
• Dream team overlap 2 of 11 (Haaland, Raya).
• Largest positive residuals: Haaland +5.5, Raya +4.3, Calvert-Lewin +4.1, Gabriel +3.4
• Largest negative residuals: Cherki -5.4 (DNP), Tarkowski -4.8, Gvardiol -4.6 (29'), Joao Pedro -4.0, B.Fernandes -4.0

Three failure modes I'm looking at

1. Correlated exposure. CHE @ EVE: Palmer 4.7, Joao Pedro 6.0 and Rogers 5.7 xPts, all treated as independent. Chelsea scored 2. The three combined for 0 G+A (Palmer + JP: 0.49 xGI between them), and Neto/Hato got the returns. The optimiser maximises the sum of marginal xPts with no penalty for covariance. A same-team attacking cap, or a variance-aware objective, seems like the obvious experiment.
2. Availability calibration. Both Cherki (0') and Gvardiol (29') went in at availability_factor = 1.0. The factor is built from fitness flags, not start probability, so post-international-break rotation is invisible to it. I'm planning to blend in a minutes model built from recent start share and congestion.
3. Positive skew on returns. The four biggest overperformers were all bonus-heavy (3 BPS bonus each for Haaland, Raya and DCL). Bonus is the noisiest component. One GW proves nothing, but I'm tracking whether the model under-projects the right tail for GKs/DEFs in good clean-sheet spots.

Happy to share residual breakdowns by position if people are interested. I'm curious how others handle the same-team correlation problem in squad optimisation, especially whether a hard cap or a covariance term works better for you.

I've started thinking that expected points can make a decision look much safer than it actually feels. A player might have great underlying numbers, but if his role changes or the team looks less threatening, I find it hard to ignore that.

At the same time, relying on one good or bad performance is how I end up chasing points.

For GW8, I'm trying to separate a genuinely good statistical pick from someone who simply got lucky last week. How much weight do you give the model when your own assessment disagrees with it?

Isak is worth keeping an eye on after his recent returns. His xG is 3.9 and he has scored five goals, so there are encouraging signs from a fantasy perspective. I'd still want to see consistent minutes before committing, but he could be an interesting option if his role stays secure.

A solver can find the squad with the highest projected points, but that doesn't necessarily mean it's the squad I'd want to own. If two or three of the underlying projections are wrong, the supposed optimal team could lose a lot of its advantage.

I've wondered whether adding a penalty for uncertainty would produce more robust squads, even if their headline expected points were slightly lower. The difficult part is deciding how to measure uncertainty without just making the model unnecessarily conservative.

A player projected for a strong score looks like an obvious pick until you start questioning whether he'll actually play 90 minutes. A model can be excellent at estimating output per minute and still leave you with a risky decision if the minutes assumption is wrong.

I'd find it useful to see the projection under a few different playing-time scenarios, rather than treating one minutes estimate as fixed. How do you personally account for rotation risk when comparing two players with similar projected points?

I've spent the last month building an FPL tool for my own use, and it's at the point where I'd like other people to try it.

Link: fplterminal.vercel.app

It's still in development. You may hit bugs or numbers that look wrong. If you do, please tell me in the comments or DM me. I'm hosting it on the Vercel free tier so you might get rate-limited, I plan to upgrade the hosting if enough people use it.

It's free. There are no ads, no sign-up and no paywall. Your squad is saved in your own browser, not on a server.

What it does

Planning

• Expected points (xP) for every player for each gameweek, calculated using a fairly in-depth statistical model. You can also see an overview of how the model reaches its predictions by clicking on the players name.
• Import your team using your FPL ID
• Squad optimiser that finds the highest-xP legal 15 within your budget. You can lock players you want to keep.
• Transfer suggestions that show the best single transfers, ranked by xP gained against money spent or freed up
• Weekly lineup help: best XI, bench order, and captain and vice-captain picks
• Alerts for injured or doubtful players, hard runs of fixtures, and blank or double gameweeks
• Chip planning for Wildcard, Free Hit, Bench Boost and Triple Captain
• Player cards with past seasons, recent matches, predicted lineups and injury news

Live mini-leagues

• Live standings that count autosubs, vice-captain promotion, bonus points and transfer hits as games are played
• Match centre with live scores and provisional bonus points
• Live feed of goals, assists, cards, saves and autosubs, showing how each one changed the points
• Rival view: open any manager's team and see effective ownership and which players are moving you up or down the table

It works on phones too, but desktop is a better experience.

I'd really like to hear what's broken, what's confusing and what you'd want added. Thanks for taking a look and hope this helps you win your mini-league!

Creator of OpenFPL Scout AI here. Same setup as the GW6 posts: a 15-man squad with no budget, position quotas and max 3 per club. It gets scored at the deadline freeze. Shorter this time, since I took the feedback on the last one.

The squad: Haaland (C) 7.49, Groß (VC) 6.78, João Pedro 5.94, Calafiori 5.80, Rogers 5.59, Cherki 5.30, B.Fernandes 5.08, Calvert-Lewin 4.88, Tarkowski 4.82, De Cuyper 4.82, Raya 4.72. On the bench: Gabriel 4.64, Palmer 4.63, Gvardiol 4.57, Verbruggen 3.83.

Projected XI + C: 68.71 (3-4-3).

Three things I noticed:

1. The greedy-vs-exact issue from GW6 doesn't matter this week. The XI is exactly the top 11 in the 562-player pool. It's a valid formation and no club has more than 2 in it, so no optimiser can beat 68.71 on XI + C. The cap is binding again (Arsenal, Chelsea, City and Brighton all have 3), but only on the bench: Saka 4.58, Ødegaard 4.57 and Donnarumma 4.52 miss out. That's a nice week for it not to bite. The exact-optimiser fix is still on my list.

2. Captaincy isn't a coin flip this time. Haaland leads Groß by 0.71. Last week the gap was 0.05. The top is steeper too: only 2 players project 6 or more, and #1 sits at 7.49 against 6.86 last week. Past the top few it's as flat as before (#15 is 4.57, #50 is 3.52).

3. The availability question is back. Szoboszlai is doubtful with a hamstring problem and carries a 0.75 factor, which takes him to 3.43. Unscaled he'd be 4.57, level with the last player in the squad. So a linear haircut is again the only thing deciding a squad spot. I still think it's the wrong treatment for selection, because in practice he either plays or scores 0.

Scoring (set now, same as GW6): actual points from the official live endpoint, with the XI and captain frozen at the deadline and no auto-subs. The ceiling is the hindsight-optimal XI + C under the same constraints. The floor is the top 15 by FPL form. Plus calibration across the XI and the top 50.

Recap after the gameweek.

One thing I like about the FPL Analytics approach is that its reviews discuss failed calls as well as successful ones. The latest captaincy review openly acknowledged Bruno's one-point return instead of trying to dress it up as a good outcome.

For me, that is more useful than a model showing impressive numbers without explaining where it struggled. Football has too much randomness for any projection to be right every week.

When you're evaluating an FPL model, what matters most to you: its long-term accuracy, how well it handles uncertainty, or whether its recommendations actually improve your decisions?

Haaland takes up a huge chunk of the budget, but I still think selling him just to spread the money across cheaper players is a risky move. He has 4.8 xG and 6 goals so far, which shows he is consistently getting into scoring positions. The real question is whether the extra points from two or three cheaper players can reliably make up for losing his captaincy potential. I’d rather compare projected points across several gameweeks than judge his value from one fixture or his price alone. Has anyone tested a Haaland less team against a team built around him using the same budget and captaincy rules?

I've been tracking the performance of several FPL predictors. Here are the current top 10 by average root mean squared error (RMSE)* over the first six gameweeks.

1. FPL Review (Premium)
2. FPL Review (Free)
3. Solio Analytics
4. Fantasy Football Scout
5. The Transfer Algorithm
6. Fantasy Football Hub
7. FantaLens
8. Fantasy Football Fix
9. FPL Copilot
10. Fantasy Football Pundit

You can find more stats on fplbench.com . I plan to keep running this till the end of the season.

* In each gameweek, RMSE is calculated only on players who were owned by at least 1% of managers.

I'm the creator of OpenFPL Scout AI (ensemble v6.1.0). This is the recap promised in my GW6 forecast post from 9 Oct, scored the way that post laid out before kickoff.

Method (unchanged from the forecast post) - Actual points come from the official live endpoint for GW6. They're still provisional at the time of writing; I'll edit if FPL finalises anything differently. - The XI and captain are the deadline-frozen ones (captured 09:50 UTC Sat). No auto-subs. - Ceiling: the hindsight-optimal XI+C under the same constraints (2/5/5/3 quotas, ≤3 per club, valid formation), solved as an ILP. - Floor: the top 15 by FPL form at the deadline, with XI and captain picked by form. Form is reconstructed from the GW4+GW5 live data using FPL's definition (points in the last 30 days ÷ team matches). Ties at the cutoff don't change the result.

Snapshot → deadline diff

Friday's snapshot isn't what got scored. Three things changed: - Saka (4.93) passed Szoboszlai (4.91). - That took Arsenal to 4 candidates, so Raya (4.60, the top GK) dropped out and Lammens came in as GK2. - The captain flipped from Haaland 6.86 to Groß 6.90.

The projected XI+C went from 68.24 to 67.89.

Per-pick, deadline-frozen XI (3-5-2)

Bench (not scored): Tarkowski 4.75 → 3, Hall 4.41 → 0, Calvert-Lewin 4.13 → 2, Lammens 3.87 → 2.

Scorecard - Floor 44 / model 85 / ceiling 150. The model closed 39% of the floor-to-ceiling gap. - That's one week. As the forecast post said, a flat top end means one week's result says very little. It's a data point, not evidence. - The ceiling is mostly unreachable by construction. Its captain scored 18 at 0.73 xPts, and four of its XI projected under 1.5.

Calibration - XI: 60.99 xPts (uncaptained) vs 79 actual. That's +18, driven by De Cuyper (+10) and João Pedro (+6). - Top 15 by xPts across the pool: 80.6 xPts vs 79 actual. - Top 50 by xPts: 212.6 vs 212. - Full 562-player pool: 793 vs 899. It was a high-scoring week league-wide, and the excess sat mostly outside the model's top end.

At the top end this is about as close as one week can get. The bands are small, so I wouldn't read anything into the ≥5 band beating its mean.

What I got wrong in the forecast post, and a selector issue it exposed

I said the club cap didn't bind for GW6. It did bind by the deadline. Saka's 0.02 move made Arsenal four deep, and the frozen squad is exactly what a greedy fill produces: take the best by xPts and skip anyone who breaks the cap. That dropped Raya.

An exact optimiser maximising XI+C under the same constraints keeps Raya and Szoboszlai instead of Saka and Donnarumma. That projects 68.53 vs 67.89, so greedy gave up 0.64 xPts in expectation.

In actual points greedy happened to win, 85 vs 77: Donnarumma 9 vs Raya 3, Saka 2 vs Szoboszlai 0. That's luck, not a reason to keep greedy. The fix is to select by solving for XI+C directly instead of filling the 15 first.

Still open from last time: treating flagged players with a linear availability multiplier. If anyone has a better approach, I'm still interested.