Haaland Luton team 15 technique + 13 long shots + 13 passing = +147gd, 108pts, 1st (+142gd, 107pts, 1st second sample)
Haaland Luton team 15 technique + 13 all technicals except cro, long, pass = +159gd, 107pts, 1st
Haaland Luton team 13 all technicals except cro, long, pass, tech = +121gd, 97pts, 1st
So the passing did a lot better than crossing combo.
I did 15 technique + 13 long shots + 13 passing with the Haaland Luton team and got much better results than technique + long shots + crossing, which only got around +100gd.
But when I tested this with the normal meta team as 14 for tech + long + pass, results were 6th, 3rd, 4th, 6th, 10th = 5.8. Which is zero benefit.
So what we see here with these specific technical combos is that they do improve things if you're already absolutely dominating, but it's not really going come into the equation for realistic play.
Based on previous median PA data I have for Manchester City, and what I know about the factors that matter, I've tried to reverse engineer a workable formula.
So far I've come up with:
((Junior Coaching x 1.5)+(Youth Recruitment)+(Youth Rating/10)+(Factor X))x1.15
Factor X is the hidden nation/division factor, and it is 62 for England with all other nations to be set proportional to it (i.e. Singapore 73 PA > England 116 PA = Singapore 25 Factor X > England 62 Factor X)
I've then tested this on a variety of teams with different nations & facilities to see how accurately it predicts the median PA.
Results:
((19x1.5)+(20)+(13.5)+(62))x1.15 = 142.6 (england - man city real) (~140 actual result previously found)
((10x1.5)+(10)+(13.5)+(62))x1.15 = 115.575 (england artificial result 116.5)
((10x1.5)+(10)+(13.5)+(25))x1.15 = 73.025 (singapore artificial result 73.05)
((15x1.5)+(19)+(14.4)+(49.14))x1.15 = 120.796 (italy - blu-neri real) (120 actual result)
((14x1.5)+(14)+(14.4)+(49.14))x1.15 = 113.32 (italy - torino real) (108 actual result)
((3x1.5)+(15)+(3.5)+(25))x1.15 = 55.2 (singapore - tampines real) (54.5 actual result, 51 second result)
((2x1.5)+(9)+(3.5)+(25))x1.15 = 46.575 (singapore - balestier real) (24 actual result, 28 second result)
((7x1.5)+(8)+(9)+(46.59))x1.15 = 85.2 (switzerland - yverdon real) (70 actual result, 90 second result)
((17x1.5)+(18)+(9)+(46.59))x1.15 = 113.95 (switzerland - zurich real) (83.5 actual result, 111.5 second result)
((11x1.5)+(6)+(9)+(46.59))x1.15 = 89.8 (switzerland - stade lausanne-ouchy real) (90.5 actual result, 96 second result)
Feel like I'm getting pretty close to a reliable formula
Man City - 123.5 Fulham - 121 Brentford - 119.5 Liverpool - 129 Tottenham - 120 West Ham - 140 Crystal Palace - 126 Luton - 113.5
Barcelona - 90.5 Juventus - 98.5 Club Brugge (Belgium) - 104 FC Porto - 94 A. Madrid - 124
To get further with this though, I have to compare the whole league of teams at a time, to remove the element of Youth Recruitment that is clouding things.
Spain complete:
A Bilbao - 98.5 A. Madrid - 95 Alaves - 113 Almeria - 100.5 Atletico Pamplona - 108.5 Barcelona - 117.5 Cadiz - 104 Getafe - 108.5 Girona - 121 Granada - 104 Las Palmas - 106.5 Mallorca - 120 Real Madrid - 124.5 Real Hispalis - 108 Real San Sebastian - 109 Sevilla - 127 Valencia - 96.5 Vallecano - 122.5 Vigo - 102 Villarreal - 120
ZaxanR said: Quick question - When searching for players using the attributes in the first post, is it better to leave them as they are but match 15/16 or 14/16 or even down to 12/16 - or to reduce the value of all attributes by 1 until you find a player that matches the filter?
For example, it's really quite hard to find a CD with 13 dribbling, but 10 pops up easily enough. Or would the better CD be one who has all of the other stats but only 4 dribbling? Expand There's no real right or wrong answer, but I'd probably go with reducing values by 1 until you get options, because perfectly balanced/proportional players seem to do well even with low values (i.e. ~12).
A problem is that the attribute figures given are hard minimums, as the whole template is pushing the envelope of what's possible, and it's not really known how well it scales going down the leagues. However I have done a bit of testing with lower leagues, and it does seem to work scaled down.
With dribbling in particular btw, I have actually tried reducing the template to around ~10 for dribbling recently, because it didn't get high weight from the real player comparisons. However it simply did not work. I also tried a bunch of other minor alterations to other attributes, and similarly got dud results. So I left it alone after that, and it means the template really is quite brittle. You can't get away with a minor subtraction here and there.
If dribbling is really the only problem, not overall quality, then I would suggest perhaps compensating by looking for higher pace/acc or higher key mentals such as anticipation and work rate. Maybe that would offset the loss, is my guess.
So I've known for the better part of a decade now that there's a significant hidden mechanic when it comes to newgens, that seems to be the unique nation itself or something along these lines.
As a refresher on what I already knew to be the case:
Junior coaching ~40% PA effect Nation youth rating ~25% PA effect Youth recruitment ~25% PA effect Club reputation acts as tie breaker for youth recruitment Either unique nation or division ID ~25% (or perhaps even more) PA effect (a hidden, unchangeable factor - it may be 'Nation attribute template' that is listed as an inaccessible debug option in the editor, which sounds like it would be similar to the 'Nation personality template' before it was removed in recent versions) All other factors no effect
How I found this is by swapping England and Romania completely, after realizing the numbers didn't add up after deducing the relevant factors and trying to calculate outcomes with them. It took a lot of work so I've never repeated it since.
It occurred to me that there's a simpler way of going about it: Make every club, division, and nation have identical relevant attributes, and measure the median PA differences that result.
A few conclusions we can already make from this initial data:
1) The hidden nation/division factor is definitely real.
2) It seemingly can't be that a factor such as 'game importance' is having a bug where it's been changed in the pre-game editor, but remains in fact unchanged in the game. Germany is 'very important' and also has highest nation rep & youth rating, but we see is ~10 PA below England & France. Mexico & Turkey have stats pretty close to England, but we see their clubs are ~20-30 PA below.
3) Germany doesn't seem to have much variation, but Israel does. Japan & HK seem to have high variation too. More testing will shed light on this, but I suspect that the hidden mechanic limits how many clubs in a division/nation get high median PA intakes, and/or how often.
4) Minnows such as N. Ireland and HK show there is a massive disparity between nations due to a hidden factor. The difference here is ~65 PA.
Just prior to this I also tested whether existing players in a team/division have any effect. I reduced the CA and reputation of players in the Premier League to '1', and it made zero difference to the outcome. So that can be ruled out.
Probably not many people have read my stuff on cities and newgen 'pools' and whatnot, so I will add here that all of that stuff I have investigated and found to be purely cosmetic. These results seem to be further evidence there is no regional/national/global pool, as all nations were assigned to the 'UK & Ireland' region, all continent regional strength was set to '1', and we see here some pretty clear arbitrary tiering of nations going on.
It's going to take a while to collect the results and have a think about how to do it, but I reckon it's probably going to be possible now to reliably calculate expected newgen PA of clubs without having to simply brute force test it for each edition.
Here's what was controlled (made identical):
Nation region Nation game importance Nation state of development Nation youth rating Nation reputation Nation tactical attributes (including preferred formations) Nation economic power Nation FA financial power Nation ranking points Club reputation Club morale Club training Club youth coaching Club youth facilities Club youth recruitment Club youth importance Club corporate facilities Club preferred formation Continent regional strength
Only Division level 1 teams were altered Professional status is not controlled, I overlooked this one So the controls aren't exhaustive, but they're pretty extensive
Facilities & morale were set to 10. Club rep to 5000. Nation rep to 7000. Nation youth rating to 135. Basically I went for something moderately high, just to help rule out extremes messing things up somehow.
stefanopt said: For the top tactics, do u use Striker rating for the AMC, or do you use AMC rating? Expand Since the conclusion so far is that all outfield players have the same weightings, you can use any position. For Genie Scout though it has a position proficiency modifier to the %, so in Genie Scout use the position you're targeting (i.e. AMC rating for AMC position).
White Europe said: What's most recent GS ratings to use ? Expand hazar35hazar said: I've been asking about this for FM24 for days too, but no one bothers to treat me like a person and actually answer me. Expand The Premier League 2.1 weights in the updated OP on page 1.
Meta team + 14 crossing/long shots/technique = 7th, 1st, 2nd, 6th, 6th, 4th, 8th = 4.857 position
So that's a little higher (~1 position) than normal which is what I was expecting.
I forgot to mention I retested bravery on DCs only earlier:
6th, 3rd, 5th, 9th (sacked), 5th = 5.6 position
So no significant effect, positive or negative. Note that I've also found previously that 20 bravery on all players is also useless.
I also did a test to see what I can do with a team of 200 CA players at Luton. Got +366 g/d. Best result was 19-0 vs Newcastle. From vague memory the previous best I got at Man City was something like +409.
Might have discovered a meaningful attribute combination.
I started with creating a team of Ederson (GK) + Haaland clones (for each position) at Luton.
A few reasons for this. Man City has sacking issues in tests. Mustermann asked essentially do significant attributes change as environmental attributes change (i.e. condition), which got me thinking about it, so my thinking is let's return to doing some high level tests where technicals may have some impact when physicals drop say. And another reason is my finding is that all positions share the same ideal attributes, so why not take by far the best player and make a team of him and see how it goes.
Ederson + Haalands default = 1st, 101pts, +133
Haalands with most technicals & some mentals at '1' (in line with meta template) = 3rd, 91pts, +58
Haalands with all technicals at '1' except drib, fin = 1st, 89pts, +79
At this point I'm thinking ah geez.. technicals must be back on the menu, but then..
Haalands with all technicals at '1' except drib, fin, cro, lon, tec = 1st, 102pts, +118
However..
Haalands with all technicals at '1' except drib, fin, tec = 2nd, 81pts, +54
Haalands with all technicals at '1' except drib, fin, lon = 1st, 92pts, +84
Haalands with all technicals at '1' except drib, fin, cro = 1st, 94pts, +82
Haalands with all technicals at '1' except drib, fin, cro, tec = 1st, 87pts, +87
So at this point I figured it's probably the combination of crossing + technique + longshots together. This would also explain why it hasn't appeared in prior testing I've done.
So I did more tests on cro + tec + lon:
2nd, 94pts, +100 (this the wildest 2nd I've seen.. beat Man City in the FA cup 8-0, 6-1 in the league) 1st, 97pts, +91 1st, 100pts, +99 1st, 96pts, +84
So that +118 simmered down quite a bit.. but still, it seems to be a significant increase.
I did another test of all technicals except drib, fin at '1' = 3rd, 88pts, +87
To keep this all in context though, we're talking about a sum total of +400 in attribute points for what appears to be ~2 position increase. For comparison, one of the marginally significant attributes, strength, would be equivalently around +140 attribute points for +2 position.
I think it has more application to player ranking dependencies, and perhaps it clues us into a common format that exists (i.e. lon + pass + tec?)
A config file will be created after you run it; see here for a primer on how to configure the weights (but I think it will be straightforward). The app hot reloads after modifying the config so it should make it easy to tweak scales and such.
This was built with speed and convenience in mind so there's no absurd wait time when starting the app. Just run it, load a save and get cracking. (Once you see the number of players cached in the bottom left corner, it's fully primed. Blink and you'll miss it). Expand It was missing some dlls. Worked out I had to install this with both the GTK3 and GTK4 options, and add the '<location>\MSYS2\ucrt64\bin' directory to the system environment path (if anyone else wants to get this working, ask AI how to do the path thing).
The app itself is very janky at the moment.. opening 'squad depth' froze up my 9950x3d for a while!
Some other UI issues that need improvement. Filter by club doesn't seem to be working. First release though, just not ready for use yet.
I'm currently wondering about dribbling, whether it ought to be increased in weight or not.
Having it at low weight just so happened to make the real rankings fit, but of the top players, all have 10+, and more controlled data suggests it is more essential.
I'm thinking that perhaps because I was assessing mainly top players, 10 vs 19 drib didn't make much difference, but something like 6 vs 10 would be a big difference.
I took a look at correlations between the top players using my weightings and the various stat measurements, and the one thing that seemed to be consistent was the inconsistency. So while two did stand out as fairly robust correlates, 'interceptions' and 'fouls committed', overall I suspect that these various stats actually have nothing to do with the win or loss outcome. My guess is that its calculating based on certain attributes and tactics or whatnot, independent of the actual match engine outcome. So cosmetic basically. Just a theory.
I tested HarvestGreen's claim that certain attributes have benefits if one player has them instead of the whole team. I'm sure I must have tested this before, since it's important if true, but I still find that it doesn't improve things. Actually, giving several players each one of the several attributes he listed as '20', seemed make the results worse than standard: 10th, 11th, 5th, 12th. This could be because attributes such as decisions are known to have a negative effect, or it could be another reason. So, unknown cause, but its not inexplicable.
The thing is, HarvestGreen's data has always turned to be generally correct for me, so long as you take it in the confines of what he is measuring. So this claim of his must be true under certain conditions. And the teamwork result (2 wingers having +8 teamwork improves team result, but whole team at +12 teamwork doesn't) seems to be evidence this kind of thing exists. Obviously it probably has something to do with tactics and/or attribute distributions. Whatever it is, it doesn't seem like you can reduce it to 'chuck in this one guy with 20 decisions'.
I decided to take a look at HarvestGreen's excel data on it, not expecting anything interesting but thought I should probably take a quick look to see if anything further could be gleaned. I saw that he included a table I don't think he mentioned in his posts, which I've translated:
So it looks like he's actually tested some of those key stat measures. It's pretty apparent to me that what these results are showing is that the attributes involved matter, not the combo of them as 'dribbles' or 'interceptions' or whatnot.
I came across one of my notes in regards to player reputation:
Home reputation influences national team call-ups by coaches, but not the selection of starters/substitutes at match time
I'm saving these notes for one big compendium sometime, but since it was raised, thought some of you might be interested in knowing that one.
I've done some more tests of Teamwork 8 > 20: 6th (sacked), 13th (sacked), 4th, 7th (sacked) = 7.5 position
So giving all outfield players teamwork is not good. But giving the wingers teamwork is seemingly good. I suspect this could be due to what HarvestGreen identified as certain attributes being less beneficial the more players that use them, rather than it specifically being a winger thing that Mustermann finds. But who knows.
I realized that I'm being too hasty in doing away with sprints & pressures. I got swept up in what Mustermann had to say, that I completely forgot about what the game files actually say:
| Distance run | Work Rate, Stamina, Pace | | Sprints | Work Rate, Stamina | | Pressures attempted | Work Rate, Anticipation | | Pressure completion | Work Rate, Anticipation, Acceleration |
LightningFlik said: I've always suspected that the coach report is vibes-based, really. It makes sense to me that their current reputation (and possibly even form) influences it, as well as the relative strength of the league and team-mates. I don't for one minute think the game is telling me that a 4.5 star player is unquestionably better than a 4 star player. Expand Now I get the weird star ratings my meta team gets. Even though they have equal attributes, the star ratings are all over the place because of different CA. Setting them to 1 CA, they're all equally 3.5 stars.
For normal play, I think this means that wingers are going to be overrated by your staff (i.e. 4 star because of high CA cost for attributes), whereas DM will be underrated (i.e. 2 star because of low CA cost of attributes). Both of these players are equal quality in reality.
I’ve noticed there have been some new findings regarding FM26 recently. What do you make of them?
We’re getting very close to FM27 now, so do you think these discoveries could have any real impact? And are you planning to release PL 2.2 as a result of them?
Looking forward to hearing your thoughts! Expand I've addressed it further up the page, where I also retested a few of the attributes to be sure. Overall a good idea, but the correlations are simply clouding the correct insights. He's getting a bunch of attributes right, but also a few wrong (i.e. Crossing & Off the Ball), even if we test using his specific suggested positions.
Nonetheless it's still useful in several other ways. For instance, I was theorizing before that what leads to more sprints and pressures would perform better, because that is what the Knap tactic seems to favor. So I was initially excited to see his data, because it shows ostensibly what attributes contribute to sprints & pressures. But his correlations, which I don't dispute the validity of, on sprints & dribbles perhaps suggest that certain attributes inexplicably increase win rate even in spite of decreasing or doing little for sprints & pressures. That actually makes sense to me, because if you're a developer, you're probably likely to overlook that then or know about it but ignore it thinking users won't go for it because it makes no sense.
There won't be a Premier League 2.2 for a while. I feel it's at the standard I want it to be, and so I'm taking a break from that for now. If FM27 is any good, I'll probably do a new version for FM27. If not, it depends on how I feel.
iezzex said: Also i feel like that some of counter type tactics which is meta are just designed for high pace physical players Better technical players may act better with posseios type tactic Untested, just a feeling based on my own long save team acting worse on meta ones Expand It's possible, but I think unlikely. I usually always test with Knap tactic, but we know that other tactics do substantially worse with or without technically gifted players. I don't know Knap's methodology, but it's worth bearing in mind, if my following assumption is correct, that he is finding the best tactic based on the real top teams who are often highly technical, not the way I test with more barebones speed machines.
iezzex said: Feels like doing test in a real league like this is absolutely incorrect RNG do more then this changes huh You better make a test league with capped CA, same teams, tactics etc and do 100 samples imo Expand Adding controls for FM testing often does more harm than it helps in my opinion.
Suppose you do test against teams that have 10 in every attribute. Well then a player of Jumping Reach 11 is going to beat them all, but then in the actual game, Jumping Reach 11 would get your team relegated. You can't take opposition players and tactics out of the equation.
Besides, this has been done. HarvestGreen uses this controlled kind of testing, and so does FM Arena - although I believe FM Arena is a little different where uses a representative set of competitive attributes for its opposition teams (i.e. 13 instead of 10).
Another angle I would tackle it from is that RNG is part of the game, and therefore must also be taken into account. So with teamwork for example, we see the RNG range is 2nd-8th. With real Luton, the top Knap tactic produces ~2nd-9th range.
It's worth pointing out that that RNG range for real Luton is actually easily squashed down a lot by pre-selecting the team so it uses the same players. If pre-selected, the range goes down to ~2nd-4th. So really the RNG is only about -/+1 position difference. People overestimate the impact of the RNG of this game IMO.
With the meta team but with Raheem Sterling replacing AMR, the variance is also very low, getting ~6th almost all the time.
Why does the meta team, having identical outfield players, have a increased variance of 2nd-8th, compared to the meta team with Sterling? Don't know, but keep in mind I'm not using pre-selection for my meta tests either.
Now regardless of whether it's RNG or player fitness or bad luck injuries or whatnot, let's just surmise the reality as this:
You can expect to vary ~2-6 positions each season from expectation. An average save might last say 6 seasons. Are you going to experience the difference between 10 and 15 pace in 6 seasons? Yes, very much so. Are you going to experience the difference between 10 and 15 teamwork in 6 seasons? Probably not really, but when you have 10 of these minor attributes together as part of a weighting system for buying/assessing players, then you will.
This also goes to why I don't think 100 samples is necessary. No one is playing 100 seasons. If I take 9 samples representing 9 seasons, and the end result is an uncertainty of -/+ 1.81 position, then that reflects the reality of normal play and it should be left at that.
Which is the more useful and relevant information?:
The life expectancy of a nation as 82.59 based on measurements of millions of people, or
As a 60 year old with a particular cancer my doctor has guesstimated I most likely have 5-7 years to live based on several similar cases he has seen, or
The doctor telling me 'its all random...we all die sometime anyway'
So teamwork does appear to be doing something here. It shouldn't be above 5 after 9 samples otherwise.
There is upside to having it at high values, but not as much downside to lacking it completely (7th at '1', vs 9th for Aggression at '1' for example, and many other key attributes fare far worse at '1' ).
8 > 16 is quite a big jump for a relatively small position gain of ~2 position, but that's only +1.6 per outfield player.
Overall I would now classify teamwork an attribute of minor importance, above Strength but probably below Aggression. Or maybe equal to Aggression, since the test team has 11 Aggression and only manages ~5th-7th on average.
Another thing to note is that because the test team's outfield players are identical, it wouldn't be the case that teamwork is simply handing over the ball to the players with the better attributes.
I'll be testing it at 20 on all players again to see what results that shows.
So versatility doesn't seem to do much. Possibly a very slight benefit. Too hard to tell like crossing.
Dirtiness surprisingly did worse at '1'. Perhaps it just requires more samples, but even so, one would expect '1' dirtiness to do better than 5th-7th given its deduced importance based on real player performance. In comparing the real players, there is a significant difference between 8 and 2 dirtiness, so it's not just about it being under '10' say. Only possibility I can think of, aside from simply requiring more samples, is that perhaps dirtiness interacts with temperament and/or sportsmanship and/or controversy, where high dirtiness can be beneficial (more hard tackles) when machiavellian sociopath but not when prone to losing temper and getting red carded for no gain.
Here's a very quick test. There are three metrics for reputation in the game:
- Home - Current - World
Other websites can probably explain (or guess) what they do but I'm just here to see if they affect contract negotiations. (How could they not?) I'll play with the values (and use my unchanged player as a baseline) and record them below.
| Home rep | Current rep | World rep | Salary demand | 3,115 | 4,372 | 1,1911 | Important player, £53k p/a | 10,000 | 4,372 | 1,1911 | Important player, £55k p/a (plus small bonus increases) | 0 | 4,372 | 1,1911 | Same as baseline | 3,115 | 10,000 | 1,1911 | Wants to talk but thinks I can't afford him (1) | 3,115 | 0 | 1,1911 | Important player, £36k p/a (also his bonus demands have halved and the coach's estimation of his ability has decreased) | 3,115 | 4,372 | 10,1000 | Important player, £86k p/a (plus large bonus increases) | 3,115 | 4,372 | 0 | Important player, £51.5k p/a (plus small bonus decreases)
(1) This was true even after I adjusted my budget sliders and tried again and after I adjusted the club's reputation to be 10,000
N.b. after changing reputations I advance a few in-game hours so the system registers it
Other notes 1. I saw no change after setting my wage budget as low as it would go (£428k p/a) and as high as it would go (£1.2m p/a) even for the 10,000 world rep experiment. (But if someone on Reddit said it did then I'm not going to dispute that.) 2. World reputation is the only thing that changed the player's reputation on his Personal Information page. It was 5 grey stars ("Minimal" at 0 and 5 gold stars ("Exceptional" at 10,000. 3. It makes sense that Current Reputation would have such a big impact on demands + your star rating if it's meant to be the sense of how hot you are as a player. 4. I also tested the baseline player when the club had a reputation of 0 and 10,000.
0: Important player, £58k p/a 2,920 (baseline): Important player, £53k p/a 3,115 (player's home rep): Important player, £54k p/a 10,000: Important player, £64k p/a
5. I also tried setting the CA/PA of the player to various values:
6. I changed the manager's Home, Current and World reputations to 10,000 and it made no difference (although it made people like me more).
Here's a dump of screenshots showing (most) of the above. I know a lot of this might not be new information but it's a start.
Baseline
CA 120/120
Club rep 0
Club rep 10,000
Player current rep 0
Player current rep 10,000
Player home rep 0
Player home rep 10,000
Player world rep 10,000
EDIT: From reading the game's code I can tell you that the reputation of the league you're going to be playing in next season is a factor (or the current league, if next season's isn't decided yet). It's a minimal impact though, seemingly. If I tell Isaac that we're going to the Premier League next season instead of League Two, he asks for a tiny bit more money and his coach summary rating drops an entire star.
From the looks of the code, it seems like a few things are summed (reputations) and then scored (given a grade?) That is, I don't think changes are linear; I think you get bucketed in to discrete grades, which represent how strong your bargaining position is. After enough reputation points gained/lost, you might find yourself in the next bucket.
This has taken _far_ longer than I anticipated and I'm knackered so I might look at the actual calculations tomorrow (no promises though).
EDIT again: I can't help myself.
If you have a "Front End" Sugar Daddy, the player's demands increase. (+15 to the score it keeps track of). Expand I found out recently what the three different reps mean exactly. I've forgot it now, but I'll post it later on. I think it was explained in a 2011 guide by two of the developers.
But yeah, there's not much to go on in regards to what affects wage demands. Perhaps someone on Youtube has done it in the past few years. I haven't looked into it myself.
Interesting that the coach rating decreased with lower current rep. Wouldn't have thought that.
Some handy findings there. So CA matters and PA doesn't. Club rep and manager rep doesn't matter, would have expected somewhat otherwise.
You know, I'm thinking this could kind of be integrated into the rating system if you use FMSS. You could do something like add 'divide by current/world rep & CA' to the formula. Makes it more useful for gameplay.
Haaland Luton team 15 technique + 13 long shots + 13 passing = +147gd, 108pts, 1st (+142gd, 107pts, 1st second sample)
Haaland Luton team 15 technique + 13 all technicals except cro, long, pass = +159gd, 107pts, 1st
Haaland Luton team 13 all technicals except cro, long, pass, tech = +121gd, 97pts, 1st
So the passing did a lot better than crossing combo.
I did 15 technique + 13 long shots + 13 passing with the Haaland Luton team and got much better results than technique + long shots + crossing, which only got around +100gd.
But when I tested this with the normal meta team as 14 for tech + long + pass, results were 6th, 3rd, 4th, 6th, 10th = 5.8. Which is zero benefit.
So what we see here with these specific technical combos is that they do improve things if you're already absolutely dominating, but it's not really going come into the equation for realistic play.
So far I've come up with:
((Junior Coaching x 1.5)+(Youth Recruitment)+(Youth Rating/10)+(Factor X))x1.15
Factor X is the hidden nation/division factor, and it is 62 for England with all other nations to be set proportional to it (i.e. Singapore 73 PA > England 116 PA = Singapore 25 Factor X > England 62 Factor X)
I've then tested this on a variety of teams with different nations & facilities to see how accurately it predicts the median PA.
Results:
((19x1.5)+(20)+(13.5)+(62))x1.15 = 142.6 (england - man city real) (~140 actual result previously found)
((10x1.5)+(10)+(13.5)+(62))x1.15 = 115.575 (england artificial result 116.5)
((10x1.5)+(10)+(13.5)+(25))x1.15 = 73.025 (singapore artificial result 73.05)
((15x1.5)+(19)+(14.4)+(49.14))x1.15 = 120.796 (italy - blu-neri real) (120 actual result)
((14x1.5)+(14)+(14.4)+(49.14))x1.15 = 113.32 (italy - torino real) (108 actual result)
((3x1.5)+(15)+(3.5)+(25))x1.15 = 55.2 (singapore - tampines real) (54.5 actual result, 51 second result)
((2x1.5)+(9)+(3.5)+(25))x1.15 = 46.575 (singapore - balestier real) (24 actual result, 28 second result)
((7x1.5)+(8)+(9)+(46.59))x1.15 = 85.2 (switzerland - yverdon real) (70 actual result, 90 second result)
((17x1.5)+(18)+(9)+(46.59))x1.15 = 113.95 (switzerland - zurich real) (83.5 actual result, 111.5 second result)
((11x1.5)+(6)+(9)+(46.59))x1.15 = 89.8 (switzerland - stade lausanne-ouchy real) (90.5 actual result, 96 second result)
Feel like I'm getting pretty close to a reliable formula
Edit:
Spain results
((19x1.5)+(20)+(14.5)+(56.71))x1.15 = 137.66 - Barcelona 126, 138.5
((14x1.5)+(15)+(14.5)+(56.71))x1.15 = 123.29 - Real Hispalis 125, 124
((11x1.5)+(13)+(14.5)+(56.71))x1.15 = 115.816 - Almeria 112.5, 101
Will be interesting to see what results for attributes he gets
HJK (Finland) - 102.5
Derry City (Ireland) - 83.5
Forge FC (Canada) - 82.5
Santos (Brazil) - 127
Magallanes (Chile) - 105.5
Man City - 123.5
Fulham - 121
Brentford - 119.5
Liverpool - 129
Tottenham - 120
West Ham - 140
Crystal Palace - 126
Luton - 113.5
Barcelona - 90.5
Juventus - 98.5
Club Brugge (Belgium) - 104
FC Porto - 94
A. Madrid - 124
To get further with this though, I have to compare the whole league of teams at a time, to remove the element of Youth Recruitment that is clouding things.
Spain complete:
A Bilbao - 98.5
A. Madrid - 95
Alaves - 113
Almeria - 100.5
Atletico Pamplona - 108.5
Barcelona - 117.5
Cadiz - 104
Getafe - 108.5
Girona - 121
Granada - 104
Las Palmas - 106.5
Mallorca - 120
Real Madrid - 124.5
Real Hispalis - 108
Real San Sebastian - 109
Sevilla - 127
Valencia - 96.5
Vallecano - 122.5
Vigo - 102
Villarreal - 120
Average median PA: 110.325
---
Singapore complete:
Albirex (S) - 70
Balestier - 82
DPMM - 74.5
Geyland Int. - 67
Hougang Utd - 63
LC Sailors - 82
Tampines - 84.5
Tanjong Pagar - 65.5
Young Lions - 69
Average median PA: 73.05
---
England complete:
Arsenal - 98.5
Aston Villa - 120
Bournemouth - 125.5
Brentford - 114
Brighton - 111.5
Burnley - 110.5
Chelsea - 121.5
Crystal Palace - 116
Everton - 121.5
Fulham - 102.5
Liverpool - 115
Luton - 110
Manchester City - 139
Man UFC - 122
Newcastle - 118.5
Nottm Forest - 123
Sheff Utd - 119
Tottenham - 120.5
West Ham - 103.5
Wolves - 118
Average median PA: 116.5
---
Switzerland complete:
Basel - 91
Grasshoppers - 91
Lausanne - 95
Lugano - 108.5
Luzern - 99
Servette - 100.5
St Gallen - 94
Stade Lausanne-Ouchy - 99.5
Winterthur - 100
Young Boys - 106
Yverdon - 93.5
Zurich - 102.5
Average median PA: 98.375
---
Italy complete:
AS Roma - 105
Atalanta - 104.5
Blu-neri - 111.5
Bologna - 108
Brianza - 106
Cagliari - 109.5
Casciavit - 121
Empoli - 101.5
Fiorentina - 101
Frosinone - 102.5
Hellas Verona - 111
Juventus - 102
Lazio - 102.5
Parthenope - 106
Salento - 106
Salernitana - 103.5
Sassuolo - 106
Torino - 102.5
Udinese - 105.5
Average median PA: 100.775
For example, it's really quite hard to find a CD with 13 dribbling, but 10 pops up easily enough. Or would the better CD be one who has all of the other stats but only 4 dribbling?
There's no real right or wrong answer, but I'd probably go with reducing values by 1 until you get options, because perfectly balanced/proportional players seem to do well even with low values (i.e. ~12).
A problem is that the attribute figures given are hard minimums, as the whole template is pushing the envelope of what's possible, and it's not really known how well it scales going down the leagues. However I have done a bit of testing with lower leagues, and it does seem to work scaled down.
With dribbling in particular btw, I have actually tried reducing the template to around ~10 for dribbling recently, because it didn't get high weight from the real player comparisons. However it simply did not work. I also tried a bunch of other minor alterations to other attributes, and similarly got dud results. So I left it alone after that, and it means the template really is quite brittle. You can't get away with a minor subtraction here and there.
If dribbling is really the only problem, not overall quality, then I would suggest perhaps compensating by looking for higher pace/acc or higher key mentals such as anticipation and work rate. Maybe that would offset the loss, is my guess.
So I've known for the better part of a decade now that there's a significant hidden mechanic when it comes to newgens, that seems to be the unique nation itself or something along these lines.
As a refresher on what I already knew to be the case:
Junior coaching ~40% PA effect
Nation youth rating ~25% PA effect
Youth recruitment ~25% PA effect
Club reputation acts as tie breaker for youth recruitment
Either unique nation or division ID ~25% (or perhaps even more) PA effect (a hidden, unchangeable factor - it may be 'Nation attribute template' that is listed as an inaccessible debug option in the editor, which sounds like it would be similar to the 'Nation personality template' before it was removed in recent versions)
All other factors no effect
How I found this is by swapping England and Romania completely, after realizing the numbers didn't add up after deducing the relevant factors and trying to calculate outcomes with them. It took a lot of work so I've never repeated it since.
It occurred to me that there's a simpler way of going about it: Make every club, division, and nation have identical relevant attributes, and measure the median PA differences that result.
The idea worked:
Man City (England) — 139, 132.5, 121.5
Paris SG (France) — 138
Man UFC (England) — 136.5
Maccabi Haifa (Israel) — 132.5, 95.5
Fulham (England) - 129, 133.5
Borussia M'gladbach (Germany) — 125
Hapoel Haifa (Israel) — 125, 97
FC Bayern (Germany) — 124.5, 113
Liverpool (England) — 124
Orlando Pirates (South Africa) — 123.5
Brentford (England) - 122.5, 126.5
Dortmund (Germany) — 121.5
Augsberg (Germany) — 120
Chelsea (England) — 117.5
Kashima (Japan) — 117.5
Vfb Stuttgart (Germany) — 117.5
Zenit (Russia) — 117
Kongsvinger (Norway) — 112.5
Beijing Guo'an (China) — 111
Ferencvaros (Hungary) — 111
Jeonbuk (Korea) — 110
Maccabi Tel-Aviv (Israel) — 108
Pumas (Mexico) — 106
Salernitana (Italy) — 105
Perth Glory (Australia) — 104
Beitar Jerusalem (Israel) — 104
Seoul (Korea) — 104
Ludogorets (Bulgaria) — 103
Celtic (Scotland) — 101.5
FCSB (Romania) — 100.5
Maribor (Slovenia) — 100
Barry (Wales) — 97.5
Konyaspor (Turkey) — 93
Lee Man (HK) — 90.5
Bnei Sakhnin (Israel) — 90
BATE (Belarus) — 90
Kashiwa (Japan) — 87
Lincoln (Gibraltar) — 80
Ballymena United (N. Ireland) — 67
HKFC (HK) — 65.5
North District (HK) — 65
A few conclusions we can already make from this initial data:
1) The hidden nation/division factor is definitely real.
2) It seemingly can't be that a factor such as 'game importance' is having a bug where it's been changed in the pre-game editor, but remains in fact unchanged in the game. Germany is 'very important' and also has highest nation rep & youth rating, but we see is ~10 PA below England & France. Mexico & Turkey have stats pretty close to England, but we see their clubs are ~20-30 PA below.
3) Germany doesn't seem to have much variation, but Israel does. Japan & HK seem to have high variation too. More testing will shed light on this, but I suspect that the hidden mechanic limits how many clubs in a division/nation get high median PA intakes, and/or how often.
4) Minnows such as N. Ireland and HK show there is a massive disparity between nations due to a hidden factor. The difference here is ~65 PA.
Just prior to this I also tested whether existing players in a team/division have any effect. I reduced the CA and reputation of players in the Premier League to '1', and it made zero difference to the outcome. So that can be ruled out.
Probably not many people have read my stuff on cities and newgen 'pools' and whatnot, so I will add here that all of that stuff I have investigated and found to be purely cosmetic. These results seem to be further evidence there is no regional/national/global pool, as all nations were assigned to the 'UK & Ireland' region, all continent regional strength was set to '1', and we see here some pretty clear arbitrary tiering of nations going on.
It's going to take a while to collect the results and have a think about how to do it, but I reckon it's probably going to be possible now to reliably calculate expected newgen PA of clubs without having to simply brute force test it for each edition.
Here's what was controlled (made identical):
Nation region
Nation game importance
Nation state of development
Nation youth rating
Nation reputation
Nation tactical attributes (including preferred formations)
Nation economic power
Nation FA financial power
Nation ranking points
Club reputation
Club morale
Club training
Club youth coaching
Club youth facilities
Club youth recruitment
Club youth importance
Club corporate facilities
Club preferred formation
Continent regional strength
Only Division level 1 teams were altered
Professional status is not controlled, I overlooked this one
So the controls aren't exhaustive, but they're pretty extensive
Facilities & morale were set to 10. Club rep to 5000. Nation rep to 7000. Nation youth rating to 135. Basically I went for something moderately high, just to help rule out extremes messing things up somehow.
Since the conclusion so far is that all outfield players have the same weightings, you can use any position. For Genie Scout though it has a position proficiency modifier to the %, so in Genie Scout use the position you're targeting (i.e. AMC rating for AMC position).
hazar35hazar said: I've been asking about this for FM24 for days too, but no one bothers to treat me like a person and actually answer me.
The Premier League 2.1 weights in the updated OP on page 1.
Link: https://files.catbox.moe/9n18q0.grf
I strongly recommend using FMST26 with the weights provided on page 1 instead of Genie Scout though if you can.
I won't be doing an update until at least the release of FM27, but so far there's no major changes to make anyway.
So that's a little higher (~1 position) than normal which is what I was expecting.
I forgot to mention I retested bravery on DCs only earlier:
6th, 3rd, 5th, 9th (sacked), 5th = 5.6 position
So no significant effect, positive or negative. Note that I've also found previously that 20 bravery on all players is also useless.
I also did a test to see what I can do with a team of 200 CA players at Luton. Got +366 g/d. Best result was 19-0 vs Newcastle. From vague memory the previous best I got at Man City was something like +409.
I started with creating a team of Ederson (GK) + Haaland clones (for each position) at Luton.
A few reasons for this. Man City has sacking issues in tests. Mustermann asked essentially do significant attributes change as environmental attributes change (i.e. condition), which got me thinking about it, so my thinking is let's return to doing some high level tests where technicals may have some impact when physicals drop say. And another reason is my finding is that all positions share the same ideal attributes, so why not take by far the best player and make a team of him and see how it goes.
Ederson + Haalands default = 1st, 101pts, +133
Haalands with most technicals & some mentals at '1' (in line with meta template) = 3rd, 91pts, +58
Haalands with all technicals at '1' except drib, fin = 1st, 89pts, +79
At this point I'm thinking ah geez.. technicals must be back on the menu, but then..
Haalands with all technicals at '1' except drib, fin, cro, lon, tec = 1st, 102pts, +118
However..
Haalands with all technicals at '1' except drib, fin, tec = 2nd, 81pts, +54
Haalands with all technicals at '1' except drib, fin, lon = 1st, 92pts, +84
Haalands with all technicals at '1' except drib, fin, cro = 1st, 94pts, +82
Haalands with all technicals at '1' except drib, fin, cro, tec = 1st, 87pts, +87
So at this point I figured it's probably the combination of crossing + technique + longshots together. This would also explain why it hasn't appeared in prior testing I've done.
So I did more tests on cro + tec + lon:
2nd, 94pts, +100 (this the wildest 2nd I've seen.. beat Man City in the FA cup 8-0, 6-1 in the league)
1st, 97pts, +91
1st, 100pts, +99
1st, 96pts, +84
So that +118 simmered down quite a bit.. but still, it seems to be a significant increase.
I did another test of all technicals except drib, fin at '1' = 3rd, 88pts, +87
To keep this all in context though, we're talking about a sum total of +400 in attribute points for what appears to be ~2 position increase. For comparison, one of the marginally significant attributes, strength, would be equivalently around +140 attribute points for +2 position.
I think it has more application to player ranking dependencies, and perhaps it clues us into a common format that exists (i.e. lon + pass + tec?)
A config file will be created after you run it; see here for a primer on how to configure the weights (but I think it will be straightforward). The app hot reloads after modifying the config so it should make it easy to tweak scales and such.
This was built with speed and convenience in mind so there's no absurd wait time when starting the app. Just run it, load a save and get cracking. (Once you see the number of players cached in the bottom left corner, it's fully primed. Blink and you'll miss it).
It was missing some dlls. Worked out I had to install this with both the GTK3 and GTK4 options, and add the '<location>\MSYS2\ucrt64\bin' directory to the system environment path (if anyone else wants to get this working, ask AI how to do the path thing).
The app itself is very janky at the moment.. opening 'squad depth' froze up my 9950x3d for a while!
Some other UI issues that need improvement. Filter by club doesn't seem to be working. First release though, just not ready for use yet.
@GeorgeFloydOverdosed
Crazy CB 88,6 Rating
And how does he fair?
I'm currently wondering about dribbling, whether it ought to be increased in weight or not.
Having it at low weight just so happened to make the real rankings fit, but of the top players, all have 10+, and more controlled data suggests it is more essential.
I'm thinking that perhaps because I was assessing mainly top players, 10 vs 19 drib didn't make much difference, but something like 6 vs 10 would be a big difference.
I tested HarvestGreen's claim that certain attributes have benefits if one player has them instead of the whole team. I'm sure I must have tested this before, since it's important if true, but I still find that it doesn't improve things. Actually, giving several players each one of the several attributes he listed as '20', seemed make the results worse than standard: 10th, 11th, 5th, 12th. This could be because attributes such as decisions are known to have a negative effect, or it could be another reason. So, unknown cause, but its not inexplicable.
The thing is, HarvestGreen's data has always turned to be generally correct for me, so long as you take it in the confines of what he is measuring. So this claim of his must be true under certain conditions. And the teamwork result (2 wingers having +8 teamwork improves team result, but whole team at +12 teamwork doesn't) seems to be evidence this kind of thing exists. Obviously it probably has something to do with tactics and/or attribute distributions. Whatever it is, it doesn't seem like you can reduce it to 'chuck in this one guy with 20 decisions'.
I decided to take a look at HarvestGreen's excel data on it, not expecting anything interesting but thought I should probably take a quick look to see if anything further could be gleaned. I saw that he included a table I don't think he mentioned in his posts, which I've translated:
So it looks like he's actually tested some of those key stat measures. It's pretty apparent to me that what these results are showing is that the attributes involved matter, not the combo of them as 'dribbles' or 'interceptions' or whatnot.
Home reputation influences national team call-ups by coaches, but not the selection of starters/substitutes at match time
I'm saving these notes for one big compendium sometime, but since it was raised, thought some of you might be interested in knowing that one.
I've done some more tests of Teamwork 8 > 20: 6th (sacked), 13th (sacked), 4th, 7th (sacked) = 7.5 position
So giving all outfield players teamwork is not good. But giving the wingers teamwork is seemingly good. I suspect this could be due to what HarvestGreen identified as certain attributes being less beneficial the more players that use them, rather than it specifically being a winger thing that Mustermann finds. But who knows.
I realized that I'm being too hasty in doing away with sprints & pressures. I got swept up in what Mustermann had to say, that I completely forgot about what the game files actually say:
| Distance run | Work Rate, Stamina, Pace |
| Sprints | Work Rate, Stamina |
| Pressures attempted | Work Rate, Anticipation |
| Pressure completion | Work Rate, Anticipation, Acceleration |
I've got some ideas I'm going to look into now.
Now I get the weird star ratings my meta team gets. Even though they have equal attributes, the star ratings are all over the place because of different CA. Setting them to 1 CA, they're all equally 3.5 stars.
For normal play, I think this means that wingers are going to be overrated by your staff (i.e. 4 star because of high CA cost for attributes), whereas DM will be underrated (i.e. 2 star because of low CA cost of attributes). Both of these players are equal quality in reality.
I’ve noticed there have been some new findings regarding FM26 recently. What do you make of them?
We’re getting very close to FM27 now, so do you think these discoveries could have any real impact? And are you planning to release PL 2.2 as a result of them?
Looking forward to hearing your thoughts!
I've addressed it further up the page, where I also retested a few of the attributes to be sure. Overall a good idea, but the correlations are simply clouding the correct insights. He's getting a bunch of attributes right, but also a few wrong (i.e. Crossing & Off the Ball), even if we test using his specific suggested positions.
Nonetheless it's still useful in several other ways. For instance, I was theorizing before that what leads to more sprints and pressures would perform better, because that is what the Knap tactic seems to favor. So I was initially excited to see his data, because it shows ostensibly what attributes contribute to sprints & pressures. But his correlations, which I don't dispute the validity of, on sprints & dribbles perhaps suggest that certain attributes inexplicably increase win rate even in spite of decreasing or doing little for sprints & pressures. That actually makes sense to me, because if you're a developer, you're probably likely to overlook that then or know about it but ignore it thinking users won't go for it because it makes no sense.
There won't be a Premier League 2.2 for a while. I feel it's at the standard I want it to be, and so I'm taking a break from that for now. If FM27 is any good, I'll probably do a new version for FM27. If not, it depends on how I feel.
iezzex said: Also i feel like that some of counter type tactics which is meta are just designed for high pace physical players
Better technical players may act better with posseios type tactic
Untested, just a feeling based on my own long save team acting worse on meta ones
It's possible, but I think unlikely. I usually always test with Knap tactic, but we know that other tactics do substantially worse with or without technically gifted players. I don't know Knap's methodology, but it's worth bearing in mind, if my following assumption is correct, that he is finding the best tactic based on the real top teams who are often highly technical, not the way I test with more barebones speed machines.
RNG do more then this changes huh
You better make a test league with capped CA, same teams, tactics etc and do 100 samples imo
Adding controls for FM testing often does more harm than it helps in my opinion.
Suppose you do test against teams that have 10 in every attribute. Well then a player of Jumping Reach 11 is going to beat them all, but then in the actual game, Jumping Reach 11 would get your team relegated. You can't take opposition players and tactics out of the equation.
Besides, this has been done. HarvestGreen uses this controlled kind of testing, and so does FM Arena - although I believe FM Arena is a little different where uses a representative set of competitive attributes for its opposition teams (i.e. 13 instead of 10).
Another angle I would tackle it from is that RNG is part of the game, and therefore must also be taken into account. So with teamwork for example, we see the RNG range is 2nd-8th. With real Luton, the top Knap tactic produces ~2nd-9th range.
It's worth pointing out that that RNG range for real Luton is actually easily squashed down a lot by pre-selecting the team so it uses the same players. If pre-selected, the range goes down to ~2nd-4th. So really the RNG is only about -/+1 position difference. People overestimate the impact of the RNG of this game IMO.
With the meta team but with Raheem Sterling replacing AMR, the variance is also very low, getting ~6th almost all the time.
Why does the meta team, having identical outfield players, have a increased variance of 2nd-8th, compared to the meta team with Sterling? Don't know, but keep in mind I'm not using pre-selection for my meta tests either.
Now regardless of whether it's RNG or player fitness or bad luck injuries or whatnot, let's just surmise the reality as this:
You can expect to vary ~2-6 positions each season from expectation.
An average save might last say 6 seasons.
Are you going to experience the difference between 10 and 15 pace in 6 seasons? Yes, very much so.
Are you going to experience the difference between 10 and 15 teamwork in 6 seasons? Probably not really, but when you have 10 of these minor attributes together as part of a weighting system for buying/assessing players, then you will.
This also goes to why I don't think 100 samples is necessary. No one is playing 100 seasons. If I take 9 samples representing 9 seasons, and the end result is an uncertainty of -/+ 1.81 position, then that reflects the reality of normal play and it should be left at that.
Which is the more useful and relevant information?:
The life expectancy of a nation as 82.59 based on measurements of millions of people, or
As a 60 year old with a particular cancer my doctor has guesstimated I most likely have 5-7 years to live based on several similar cases he has seen, or
The doctor telling me 'its all random...we all die sometime anyway'
So teamwork does appear to be doing something here. It shouldn't be above 5 after 9 samples otherwise.
There is upside to having it at high values, but not as much downside to lacking it completely (7th at '1', vs 9th for Aggression at '1' for example, and many other key attributes fare far worse at '1' ).
8 > 16 is quite a big jump for a relatively small position gain of ~2 position, but that's only +1.6 per outfield player.
Overall I would now classify teamwork an attribute of minor importance, above Strength but probably below Aggression. Or maybe equal to Aggression, since the test team has 11 Aggression and only manages ~5th-7th on average.
Another thing to note is that because the test team's outfield players are identical, it wouldn't be the case that teamwork is simply handing over the ball to the players with the better attributes.
I'll be testing it at 20 on all players again to see what results that shows.
I also tested two other attributes:
Dirtiness 8 > 1 = 4th, 10th (sacked), 9th (sacked), 9th (sacked) = 8 position
Versatility 8 > 20 = 5th, 10th (sacked), 3rd, 3rd, 8th (sacked), 5th = 5.666 position
So versatility doesn't seem to do much. Possibly a very slight benefit. Too hard to tell like crossing.
Dirtiness surprisingly did worse at '1'. Perhaps it just requires more samples, but even so, one would expect '1' dirtiness to do better than 5th-7th given its deduced importance based on real player performance. In comparing the real players, there is a significant difference between 8 and 2 dirtiness, so it's not just about it being under '10' say. Only possibility I can think of, aside from simply requiring more samples, is that perhaps dirtiness interacts with temperament and/or sportsmanship and/or controversy, where high dirtiness can be beneficial (more hard tackles) when machiavellian sociopath but not when prone to losing temper and getting red carded for no gain.
Here's a very quick test. There are three metrics for reputation in the game:
- Home
- Current
- World
Other websites can probably explain (or guess) what they do but I'm just here to see if they affect contract negotiations. (How could they not?) I'll play with the values (and use my unchanged player as a baseline) and record them below.
| Home rep | Current rep | World rep | Salary demand
| 3,115 | 4,372 | 1,1911 | Important player, £53k p/a
| 10,000 | 4,372 | 1,1911 | Important player, £55k p/a (plus small bonus increases)
| 0 | 4,372 | 1,1911 | Same as baseline
| 3,115 | 10,000 | 1,1911 | Wants to talk but thinks I can't afford him (1)
| 3,115 | 0 | 1,1911 | Important player, £36k p/a (also his bonus demands have halved and the coach's estimation of his ability has decreased)
| 3,115 | 4,372 | 10,1000 | Important player, £86k p/a (plus large bonus increases)
| 3,115 | 4,372 | 0 | Important player, £51.5k p/a (plus small bonus decreases)
(1) This was true even after I adjusted my budget sliders and tried again and after I adjusted the club's reputation to be 10,000
N.b. after changing reputations I advance a few in-game hours so the system registers it
Other notes
1. I saw no change after setting my wage budget as low as it would go (£428k p/a) and as high as it would go (£1.2m p/a) even for the 10,000 world rep experiment. (But if someone on Reddit said it did then I'm not going to dispute that.)
2. World reputation is the only thing that changed the player's reputation on his Personal Information page. It was 5 grey stars ("Minimal"
3. It makes sense that Current Reputation would have such a big impact on demands + your star rating if it's meant to be the sense of how hot you are as a player.
4. I also tested the baseline player when the club had a reputation of 0 and 10,000.
0: Important player, £58k p/a
2,920 (baseline): Important player, £53k p/a
3,115 (player's home rep): Important player, £54k p/a
10,000: Important player, £64k p/a
5. I also tried setting the CA/PA of the player to various values:
| CA | PA | Demands
| 67 | 120 | £53k p/a (baseline)
| 67 | 200 | Unchanged
| 67 | 67 | Unchanged
| 120 | 120 | Not willing to discuss!
| 1 | 200 | Unchanged
6. I changed the manager's Home, Current and World reputations to 10,000 and it made no difference (although it made people like me more).
Here's a dump of screenshots showing (most) of the above. I know a lot of this might not be new information but it's a start.
Baseline
CA 120/120
Club rep 0
Club rep 10,000
Player current rep 0
Player current rep 10,000
Player home rep 0
Player home rep 10,000
Player world rep 10,000
EDIT: From reading the game's code I can tell you that the reputation of the league you're going to be playing in next season is a factor (or the current league, if next season's isn't decided yet).
It's a minimal impact though, seemingly. If I tell Isaac that we're going to the Premier League next season instead of League Two, he asks for a tiny bit more money and his coach summary rating drops an entire star.
From the looks of the code, it seems like a few things are summed (reputations) and then scored (given a grade?) That is, I don't think changes are linear; I think you get bucketed in to discrete grades, which represent how strong your bargaining position is. After enough reputation points gained/lost, you might find yourself in the next bucket.
This has taken _far_ longer than I anticipated and I'm knackered so I might look at the actual calculations tomorrow (no promises though).
EDIT again: I can't help myself.
If you have a "Front End" Sugar Daddy, the player's demands increase. (+15 to the score it keeps track of).
I found out recently what the three different reps mean exactly. I've forgot it now, but I'll post it later on. I think it was explained in a 2011 guide by two of the developers.
But yeah, there's not much to go on in regards to what affects wage demands. Perhaps someone on Youtube has done it in the past few years. I haven't looked into it myself.
Interesting that the coach rating decreased with lower current rep. Wouldn't have thought that.
Some handy findings there. So CA matters and PA doesn't. Club rep and manager rep doesn't matter, would have expected somewhat otherwise.
You know, I'm thinking this could kind of be integrated into the rating system if you use FMSS. You could do something like add 'divide by current/world rep & CA' to the formula. Makes it more useful for gameplay.
11th (sacked), 8th (sacked), 6th, 8th (sacked), 12th (sacked) = 9 position