Solio Analytics

Last major update to our #FPL projections now pushed after today's press conferences Late team news and market data will continue to feed in until the deadline Best of luck this GW all! 👉 fpl.solioanalytics.com

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Ok think I will call it there, thanks again for your interesting questions, and sorry if I didn't manage to get to yours! - JC 🚀

Running the calculation this year again, we have a fairly low value for team value increases in the current state of play - only ~0.21pts per gameweek for every extra £1.0m of team value. Historically we have seen this number often nearer ~0.3 If we were to assume Bruno Fernandes is never viable and Saka remains injured for the rest of the season (extreme assumptions, for illustrative purposes only), then this value does drop a little, but only to ~0.19 The point at which team value is meaningless tops out a little lower there though at 114.0m, instead of 119.6m

This depends a lot on the landscape at the time. We can think of all plans as sitting somewhere within a region on a plane with one axis representing total projected points, and one axis representing amound of relative risk to the field. The shape of this region depends on the state of play at the time, including which players are projected to score well, and which players everyone else owns. You can see for example from two regions we mapped out last season for FH33 and FH34 that these can be of different shapes. In GW33, it was much more costly to dial up your relative risk than it was in GW34, but it was quite cheap to dial the relative risk down. (See how far to the right or left the "raw optimal" orange dot is on the upper frontier of the shaded reagion, and how steep the drop-off is moving to the left or right of it). I think the best approach is to try a few of the presets and see what changes, to better understand the cost of tuning your relative risk, and whether that is a cost you are willing to take based on your objectives. With regards to optimistic vs safe, those are more to do with absolute risk and plan fragility. A plan that depends on a lot of the landscape remaining the same might project more points if those assumptions hold, but a plan that is more cautious will be able to adapt to big changes more readily. Sometimes the fragile plan will come off, and sometimes the robust plan will still hit a run of injuries and fall behind anyway. When we tested over the course of a full season with different ways of valuing your free transfers back when the new rolling to 5 mechanic was introduced, similarly skilled managers could differ by around 15-20 projected points over 12 or so gameweeks in extreme examples, just from whether their team was more or less fortunate with injuries, rotations, changes in player or team strengths, etc. And that's before any variance from real points over projected points!

We backtest and refine on many seasons worth of historic predictive data and inferences from efficient sharp betting markets. I'd like to think projection models influence the talk of the town, rather than the other way round.

Both are good options, only a mistake if you were hoping to go with the crowd and you misread, or if you valued the price change and missed that last night.

A big chunk of the difference comes down to playing time beliefs, their projected baseline rates for goals and assists is fairly similar. Projected over next 12 gameweeks (including fantasy assists): Barcola 0.29 npG/90, 0.24 A/90 Gakpo 0.26 npG/90, 0.26 A/90 Historic (not including fantasy assists): Barcola (26/27) 0.22 npxG/90, 0.12 xAG/90 Gakpo (26/27) 0.16 npxG/90, 0.45 xAG/90 Gakpo (25/26) 0.28 npxG/90, 0.22 xAG/90

I would say common mistakes (made by me also) are attributing too much value to small samples of data and metrics which hold little predictive value

Antonio Silva, Maxim De Cuyper, Pascal Groß

When I ran solves for chip plans across the first half of the season in GW1, the worst chip plan I could come up with only scored ~10 projected points less than the best chip plan I could find. Of course that was just with a snapshot in preseason, and the landscape is dynamic, so it's likely the hindsight optimal best and worst strategies would have diverged more than that. I think the same still holds true for the upcoming stretch though. It will be more important how you play the chip line, than which chip line you use.

If money were no restriction, then I think most people would agree Isak over Jackson. It might not seem like budget is an issue now, but that can change quickly and it uses transfers to change your team structure around, so I wouldn't rule it out that you might need the money later.

If I run a GW1-8 solve using our gameweek projections from each deadline (with no chips, and only a few transfers planned), I get a squad something like this: GW1: Raya, non-playing 4.0 Gabriel, Calafiori, N.Williams, De Cuyper, Thomas B.Fernandes, Mbeumo, Palmer, Szoboszlai, Groß Isak, Calvert-Lewin, Wissa GW2: Roll GW3: B.Fernandes, Isak → Gomez, Haaland GW4: Szoboszlai → Rogers I think on a WC9 solve, we sould probably still expect to see Raya, and Arsenal defender or two, De Cuyper, Thomas if he's fit, Palmer, Groß, Haaland, and Calvert-Lewin? Mbeumo / Rogers / Isak might be in there too. So N.Williams, B.Fernandes, Szoboszlai, and Wissa probably the ones who wouldn't make it.

There is no singular point at which a player becomes good or bad, this is binary thinking, which our brains use as a shortcut. As I said in an earlier post, if you think Palmer's underlying projections are too high, then one (or both) of two things must therefore be true: - Chelsea's team attack is rated too high - Chelsea's others attackers are rated too low nitter.cf/SolioAnalytics/status/… We are currently projecting him at 0.32 non-pen goals p90 for the next 12 gameweeks, and he put up 0.27 last season in the Premier League, and 0.38 the season before.