Wail said: Can you do it automatically through the season ? or we have to do it week by week, its kinda boring copy pasting it. Expand You add it for every week straightaway, but I don't think there's a way around having to copy paste each week
bf3metro said: One practical thing I’m still unsure about: where would you place the 2x Physical + 2x Attacking sessions during the week?
The issue I have is that in weeks with away games, Travel can automatically replace training slots, especially around the day before matches, so sometimes the intended 214 sessions disappear. Expand I think there's an option in the settings to set matches to only be on 2 certain days? I don't use this though, so not sure.
I would do 2 days of [Physical][Attack]
I wish I could remember the details properly, but I can vaguely recall that where you place training doesn't matter like you would think it does. That you can put training straight after a match day, and it won't affect condition recovery rate or injury rate. And that it's actually calculated as a whole 2 week (not even 1 week) block of training.
Not 100% certain on the injury thing, because I would think that unrecovered condition would increase injury rate of training modules, but then again match sharpness (which decreases with time post-match) has a bigger influence on injury rate, so perhaps they cancel each other out.
I won't get into the details because it'll just be confusing, but the Sterling meta team vs. real Luton discrepancy should be fixed now, and you can discard the theory I came up with to try and explain the discrepancy (that roles do take attributes into account in some way).
But this leads me to new ideas.
We see that when position proficiency is equalized, a non-sensical assymetric tactic that I came up with performed equal to Knap's best tactic (5th vs 6th).
We also see that the random variation is subdued a lot with the meta team due it being composed of identical players. Consistent ~6th-7th with Knap tactic, compared to ~2nd-10th for real Luton. And it's unlikely to be mostly on account of injuries, morale, etc. because none of those are controlled with the meta team tests.
A theory I have is that when the assistant manager picks players to play at real Luton, he is choosing based on role rating. Roles are an average(?) of select highlighted attributes. Some of these roles are going to highlight more meta attributes than others.
Now let's take a look at some ST options:
trequartista ST - drib*, fin, ant, com*, vis*, acc*, agil, bal false nine ST - drib*, fin, ant, com*, vis*, acc*, agil*, bal advanced forward ST - drib*, fin*, ant, com*, work, acc*, agil, bal, pace, sta pressing forward ST - agg*, ant*, com, con, work*, acc*, agil, bal, pace*, sta*, str
* denotes its shown as a key attribute for the role.
I've highlighted attributes that contribute 25 or more weight, inferred from the real player testing I've done.
Guess which two of the four Knap's tactic employs.
Now if the assistant manager is selecting based on the role selected in your tactic, then we can suppose if I use AF STs, I will get ~2nd, but if I use False Nine STs maybe I will get ~16th. Not variations between 2nd and 10th. Consider however that because the assistant manager is effectively using a half-blinded assessment, a layer of inconsistency is being added. So for instance, your tactic has 2x AF ST, and your assistant picks 2xST that has very high acc & drib because they have the highest AF ST role score. However, you also have a False Nine ST that has very high det, con, vis, pace, work, and jump that your assistant overlooked, but may nonetheless get rotated in half the time as they are the close 2nd option.
I'll be doing some tests to see if this theory works at all or not.
First result for my tactic with default Man City w/ Blue routines, no player selection or anything. I do set the training intensity to 0-0-0-2x-2x though.
I'm thinking I'll run about 10 tests of Luton & Man City each to see how it goes against the Knap tactic.
I've done 2 tests so far of HIGHWAY STAR 4231 P107 FC, which I've seen Cardoni recommend:
Luton default = 4th, 10th
Another thing I'm thinking of doing is having a 3rd crack at player traits. We know that the tactic is very important, and that player instructions are part of this.. so maybe if we have a team given player traits that align perfectly with the Knap tactic, it will do better - even if its because its giving initial familiarity when normally there is zero starting familiarity. So we'll see if anything results from this approach.
LightningFlik said: With that in mind, how flexible a weighting system do you think is needed to really assess players? Is a simple Pace: 20, Acceleration: 19.2 system sufficient or do you need interdependence between attributes? Expand There isn't the data yet to confirm one way or the other, but my hunch is that there aren't many attribute interactions going on, simply because the evidence shows almost all the technicals don't matter no matter what.
However I believe there is an interaction between aggression and dirtiness for instance that is crucial. Not just because it's a hypothesis that sounds sensible, but because as I was playing around with the weightings, it just seems to make things work out better.
So it would be good if you could include the ability to create complex formulas as FMSS does, but I don't know how difficult that would be to implement.
A fair chunk of my earlier post on tactics is in error, as I changed position proficiency at some point for my meta team and forgot to change them back.. this only affects the statements about meta team vs. real Luton/Man City results. Everything else remains valid. I'll conduct fresh tests on the meta team to sort it out.
I've come up with my own variation of the 4-2-4 formation/Knap tactic that is quite unique I believe, based on a theory I have. Initial results are 5th, 7th, 10th, 3rd as Luton and 6th, 7th as meta team after I've fixed it back up. So possibly equal to the Knap tactic, and perhaps a tweak or two can push it higher. I figure that I would probably only release a tactic if I can get 1st as Luton.
Does anyone know if 1st as Luton has been achieved with a tactic test? Obviously just the default test run, no managing the team throughout the season to achieve it.
LightningFlik said: @GeorgeFloydOverdosed Are you in the market for an FM 24 scouting tool with customisable weights? or do you have one already? Mine is nearly done but there's been so many released recently, I can't even keep track. Expand Yes, I'm still keen to see your go at it. The more options the better.
I guess with FM27 coming soon, its 50/50 whether people will move on entirely from FM24 or not. But if FM27 turns out to be crap 2.0, then I think these new tools will help keep FM24 alive by injecting a bit of novelty into it.
I've been making my first foray into tactic creation. Unfortunately I haven't been able to top Knap's EF 424 IF HP V2 P101 AC, but it did bring out some things worth mentioning. I know most of us are waiting now for FM27, and this stuff should apply to FM27 as well.
I started testing with my meta team + Sterling that always seemed to finish a rock solid ~6th.
It didn't take me long to come up with an unusual tactic that finished 5th. However when I tested this with real Luton, they only finished 8th-16th, whereas the Knap tactic can finished as high as 2nd (2nd-10th?). My tactic won with Man City, but only with 89 pts (Knap as high as ~100-110?).
And it's not just my tactic. 424 Mountain King did better than the Knap tactic with my test team from memory, but I didn't get 2nd with it for real Luton.
I tested a bunch more Knap tactics. The results in his spreadsheet don't line up with my results, whereas by contrast it seems that FM Arena's testing is accurate in spite of the methodology critiques I would have of it. Nonetheless all the ones I tried did well, at least 9th for real Luton and often better. But nothing got 2nd like EF 424 IF HP V2 P101 AC.
Of the alternatives I tested, FM24.4HGF4231 V3X RM P107 ALL CUPS seemed the best. 3rd, 6th Luton. Man City 1st 94pts.
Curiously I could use my unusual tactic with several positions I had no player proficiency in at all across my meta team, and yet it still did well. Not quite as good, but it held up well.
Now here's the point we can take beyond FM24:
The results suggest that roles or player instructions are in fact dependent on the attributes of players in some respect.
Yet we also know from the meta team results that it's not what the roles highlight, nor combined team quality.
Injuries, differing player choices, etc. can account for the high variation in the real Luton results relative to the meta team test, but it doesn't explain why only the Knap tactic peaks far higher with real Luton.
One idea I have is that perhaps its not combined team quality, but how each player's attribute is relative to others in his team. In the official guide, they talk of 'absolute' vs 'relative' attributes, and most attributes are 'relative'; perhaps this is what they were actually talking about. There is some suggestive evidence that makes me think along these lines, such as that with finishing, you only need a player with ~7 finishing, but any figure can do the job really, and what happens is whoever in the team has the highest finishing is the one scores the most goals, even if they're a DL with 5 finishing. So we see here that a low attribute altered the tactical outcomes, because of how it was relative to others in the team.
So for instance in my meta team all my players have 8 passing and 13 dribbling, the tactic treats them as all equally likely distribute the task of passing and dribbling I suppose. Perhaps an attribute such as 'teamwork' even influences how well these tasks are evenly distributed throughout the team. But then also for each individual player, they would be more likely to dribble (13) than pass (8).
It's pure speculation, but it would explain why virtually every technical attribute matters zero percent. It would be that the tactic minimizes their influence, and that tactics which don't minimize their influence get beat anyway, whereas Knap's tactic wins almost every match. In other words it could be that just the tactics are broken, rather than that the attributes are also broken. 0 direct passes x 20 passing = effectively 0 passing. Or, 20 direct passes x 20 passing x 0% win rate = 0% win rate for 20 passing.
Torresinho said: what about playing time for young players ? Expand 18 or less = Don't need competitive matches, but do play in friendlies (u18s/reserves fine) mainly to keep their match sharpness up in order to avoid injury more than development 21+ = Need at least 15 full matches (1350 minutes) per season to develop adequately, 25-35 is ideal, so this is why loans typically become necessary 19-20 = Inbetween the two above
Don't bother bringing on young players for a few minutes at the end of a game. The game counts experience in terms of minutes not appearances, and I suspect it could also be counting it the same way it counts minutes for match sharpness, which is that it counts in precise 11 minute blocks (I think it was 11 minutes.. something near that anyway).
alexej said: Sorry if this has already been said but are these all at x2 training intensity? Expand I don't know what HarvestGreen tested them with, but he recommends 0-0-0-2x-2x, and I've played around with it myself before and found that to be best too.
So here I am trying to take into account outfield + GK + CA efficiency + intensity.
HarvestGreen didn't include the GK stats for 331 as far as I can see, so I've just inserted a high value of 1000. Even with this high value for GK, it doesn't seem as quite as good overall as 214 or 211, though it does have the highest absolute gain in its favor.
There is one more thing to add into the assessment, which is the effect on other various in-game factors:
331 has a slight edge over 214 due to the better balancing of match sharpness.
211 is much better for match sharpness, but is probably going to wear down condition too much during the competitive season, especially if you have weeks with 2 matches. The main problem with 211 is that it would be so finicky to implement that in all likelihood you're not going to implement it properly every week, and the careful handling of condition would add to this. 211 is nonetheless very good for GK and absolute gain, both of which 214 falls a bit short on.
One more thing to say about 214 is that its what I found to be best using a different method previously. So where things are roughly equal, I'm inclined to lean towards it anyway. And in HarvestGreen's assessment, 214 also scores higher on his 'quality' index than these other 2.
So overall I will still be recommending 214. I just realized that 331 was actually my 2nd recommendation before, I didn't realize until now that that was HarvestGreen's recommendation.
It might be worth setting up 211 for your u21s/u18s, especially if they have no competitive league or cup and you can set and forget it with weekly friendlies for the whole season. Reason is, u21s/u18s easily end up in match sharpness ruts they never get out of, and low match sharpness is a big influence on injury rate, and more injuries = less development.
It's splitting hairs between 214 and 331, so if you feel more comfortable going with 331, that's perfectly fine.
One thing left unaddressed is GK focus. HarvestGreen's data used 'Agility and Balance' as GK focus, so we can't be sure of the effect of any others. But it seems to be the case that Agility isn't as critical as a few others: Determination, Reflexes, Concentration. Personally I've started favoring 'GK reactions' because it focuses on two of those (Reflexes, Concentration). But there's no data on this.
211 = 130% GK, 100% Def, 90% Att 214 = 100% GK, 100% Def, 100% Att 260 = 105% GK, 105% Def, 105% Att 142 = 125% GK, 125% Def, 125% Att
..and now, as I was examining HarvestGreen's own rankings, I gradually cottoned to the fact that there's a huge standout error in my data.
214, 211, 142 and 260 are all at the top of his rankings just like mine.. yet he has 331 as the best. I figured there has to be something amiss here, and sure enough, getting ChatGPT to recalculate it gives 1202.567.
That means HarvestGreen's recommendation of 331, would in fact be the best schedule for outfield.
I could have sworn I verified it with ChatGPT as 1020.63 three times just to be sure at the time. So I went back to check, since I still had the convo open:
Fuckin' ChatGPT man..
I presume it got at least most of them right, but now I can't be certain some weren't miscalculated by ChatGPT.
Anyway, at least we know from the backing of HarvestGreen's rankings that 331, 260, 211, 214 and 142 are the top ones and that the numbers are most likely correct for at least those.
You should be aware also this mirroring of HarvestGreen's data is a pleasant unexpected surprise. I did have HarvestGreen's weights as a starting or reference point for Premier League 2.1, but as you can see with Rain's comparison test of HarvestGreen's weights vs. Premier League 2.1, things should have changed substantially in the end. So it's surprising that the favored training schedules nonetheless align.
bf3metro said: If you had to pick only one between 214 and 260 for the entire squad, which one would you use? Expand I'll get back to you in a day or two, as things are still evolving right now, as you can see from my words above
I've done most of the remaining training schedules in HarvestGreen's spreadsheet.
We have a new top one, that I've highlighted green. This one was actually suggested by tam1236 back in january. He took the HarvestGreen attribute test findings and did a calculation on it to find this as the best training schedule.
It even has pretty good efficiency, though I suspect the workload could be too high to be worth using with all those modules. Very impressive though given it also has one of the highest CA gains (37.75), so it's particularly good if you want to keep your players looking well rounded for aesthetic reasons without compromising on actual performance.
It turns out there are a lot of very high efficiency options above 1000 (so still ~85%+ of the absolute best), and the most efficient is now Recoveryx13. I wouldn't recommend it, but it's interesting there's a profound difference in training quality between rest and recovery on their own.
I've highlighted in yellow some schedules that stand out to me, but I haven't taken a close look yet.
masterjackfruit said: I personally like the training schedules with recovery the most, I try to keep my backup players sharpness as high as possible and recovery seems to preserve sharpness better than rest. Also I notice that for some reason the Attacking session yields an unusual number of injuries, more so than Defending or Overall. I could be wrong, but it's something I've noticed in my saves. Expand It's a more subjective matter, but what I found is that using home friendly matches against the worst team possible is better than using recovery periods in training.
Friendly matches improve morale, build familiarity, build up match sharpness a lot better, and I daresay even result in less injuries.
When using all recovery I noticed that it tends to result in too low condition and eventually fatigue, so it had to be half recovery half rest, which also can be tedious to set up properly each week.
I can't remember if this is the case, but recovery might also interact differently with the other training modules to produce different results than what it shown in HarvestGreen's spreadsheets.
bf3metro said: Hey, based on all the testing you’ve done here, do you have what you’d consider an optimal schedule to actually use week-to-week over a full season?
I’ve been using ZaZ’s Growth 2, but in my save it really isn’t delivering the development I expected.
What I’m mainly looking for is a schedule that pushes CA growth as fast as possible so players reach their PA quickly, rather than just maximizing CA efficiency.
Would you recommend switching fully to something like 260 / 214 / 156 depending on the players’ CA–PA gap, or do you have a specific weekly/monthly rotation you think is optimal in practice? Expand ZaZ Growth 2 would be 1064.2675-1115.573
Oddly enough the 2-match Physicalx2 Attackingx2 scores better than the Physicalx5 Attackingx5 and results in higher CA gain too.
Because CA-PA gap is a critical accelerant to growth, you actually want the lowest overall CA growth possible - while highest in the CA growth where it matters. There is a hard cap on CA per season anyway, which is ~20-25 (someone has reported ~30 i think). If your players aren't developing much, it's more likely that they're over 18 and not getting enough match experience. No match experience for older players can reduce growth to ~1 CA/season.
I've re-examined training according to what matters in the Premier League 2.1 weights, for both outfield and GK.
This time I was able to calculate everything quickly and comprehensively utilizing ChatGPT with HarvestGreen's excel sheets.
I haven't calculated every schedule exhaustively, just the ones you see here, most of which were the most promising previously.
Overall I recommend either 260 [Physical][Match Practice][Attacking]x2[Quickness Focus] for squad with high CA-PA gap or 156 [Physical][Quickness][Transition Restrict][Quickness Focus] with low CA-PA gap. Or 214 [Physical]x2[Attacking]x2[Quickness Focus] for something inbetween.
Green = The new best training schedules, in my opinion Light blue = The two schedules I have last recommended. They're both still worth considering. Deep blue = ZaZ's recommended schedule Pink = A long time popular meta Purple = HarvestGreen's last recommendation
Where no focus is listed, it's Quickness Focus.
Workload will be a little inaccurate, as I eyeballed the intensity bars rather than calculated it.
bf3metro said: So whatever attribute-count limitation you ran into doesn’t seem to reproduce on my current FMSS version. Maybe it was related to an older build/plugin or a different part of the data pipeline. Expand I figured it could be this. I'm using the latest version I believe. I'll try doing a reinstall later on.
You've got it working, and anyone who uses FMSS can use your weights.
Trying to debug code frustrates the hell out of me. I don't know how people willingly do it every day for a living. I've also found it tedious translating the FMST26 weights to GS.
I'm not quite satisfied with the GS weights, especially in light of Rain's recent test, and the 15% discrepancy rate between the FMST26 and GS weights. I want my weights to perform at least slightly better in every respect than anything else ideally. I give 8/10 now though.
I guess Rain's finding that there isn't too much difference overall between different weightings makes sense when you do the math on it.
5/11 players @ +2% = +10% for +2.75 position = +0.55 position per player @ +2% Maeda (83%) 3.0 vs. Dybala (69%) 6.4 = +14% for +3.4 position
+10% for +2.75 position = +3.63% for +1 position +14% for +3.4 position = +4.11% for +1 position
Could be just a coincidental correlation, but I reckon it's probably reflecting a consistent effect. The 80%/78%/76%/74% team test does suggest that the % differences can be simplified to addition, as there were strong distinctions in the results.
I'm putting my comparison test of keithb's biggest discrepancies with Premier League 2.1 on hold for now, but if we just take Maeda vs. Heung-Min Son for a quick picture, there's a ~8.9% discrepancy. Let's say in a worst case scenario you sign 4 of your starting 11 as these discrepancies:
8.9% x 4 = 35.6% If ~4% ≈ 1 position, then 35.6% = 8.9 position
So the most difference you could get from keithb or GS default weights say and mine, or whatever is best, is probably 9th vs 18th.
If we suppose the chance of a Maeda-like discrepancy (+ the curve leading up to Maeda) is ~8% total, then:
1/11 discrepancy ≈ 39.4% chance of -2.22 position 2/11 discrepancy ≈ 17.3% chance of -4.45 position 3/11 discrepancy ≈ 4.6% chance of -6.67 position 4/11 discrepancy ≈ 0.82% chance of -8.9 position
That is to be added on top of the common ~2% difference in ratings.
So let's say its a realistic worst case scenario where its 2x Maeda + 3x identical + 6x the typical ~2% difference:
~15% chance, with result of -7.45 position (i.e. 9 vs 16.45 position)
You add it for every week straightaway, but I don't think there's a way around having to copy paste each week
bf3metro said: One practical thing I’m still unsure about: where would you place the 2x Physical + 2x Attacking sessions during the week?
The issue I have is that in weeks with away games, Travel can automatically replace training slots, especially around the day before matches, so sometimes the intended 214 sessions disappear.
I think there's an option in the settings to set matches to only be on 2 certain days? I don't use this though, so not sure.
I would do 2 days of [Physical][Attack]
I wish I could remember the details properly, but I can vaguely recall that where you place training doesn't matter like you would think it does. That you can put training straight after a match day, and it won't affect condition recovery rate or injury rate. And that it's actually calculated as a whole 2 week (not even 1 week) block of training.
Not 100% certain on the injury thing, because I would think that unrecovered condition would increase injury rate of training modules, but then again match sharpness (which decreases with time post-match) has a bigger influence on injury rate, so perhaps they cancel each other out.
But this leads me to new ideas.
We see that when position proficiency is equalized, a non-sensical assymetric tactic that I came up with performed equal to Knap's best tactic (5th vs 6th).
We also see that the random variation is subdued a lot with the meta team due it being composed of identical players. Consistent ~6th-7th with Knap tactic, compared to ~2nd-10th for real Luton. And it's unlikely to be mostly on account of injuries, morale, etc. because none of those are controlled with the meta team tests.
A theory I have is that when the assistant manager picks players to play at real Luton, he is choosing based on role rating. Roles are an average(?) of select highlighted attributes. Some of these roles are going to highlight more meta attributes than others.
Now let's take a look at some ST options:
trequartista ST - drib*, fin, ant, com*, vis*, acc*, agil, bal
false nine ST - drib*, fin, ant, com*, vis*, acc*, agil*, bal
advanced forward ST - drib*, fin*, ant, com*, work, acc*, agil, bal, pace, sta
pressing forward ST - agg*, ant*, com, con, work*, acc*, agil, bal, pace*, sta*, str
* denotes its shown as a key attribute for the role.
I've highlighted attributes that contribute 25 or more weight, inferred from the real player testing I've done.
Guess which two of the four Knap's tactic employs.
Now if the assistant manager is selecting based on the role selected in your tactic, then we can suppose if I use AF STs, I will get ~2nd, but if I use False Nine STs maybe I will get ~16th. Not variations between 2nd and 10th. Consider however that because the assistant manager is effectively using a half-blinded assessment, a layer of inconsistency is being added. So for instance, your tactic has 2x AF ST, and your assistant picks 2xST that has very high acc & drib because they have the highest AF ST role score. However, you also have a False Nine ST that has very high det, con, vis, pace, work, and jump that your assistant overlooked, but may nonetheless get rotated in half the time as they are the close 2nd option.
I'll be doing some tests to see if this theory works at all or not.
any news on trainings? which one came out on top?
My conclusion is here
My preferred training schedule remains 214 [Physical]x2[Attacking]x2[Quickness Focus]
331 [Physical][Match Practice][Attacking][Defending][Quickness Focus] has the best absolute attribute gain
Results: 8th, 4th, 5th, 5th, 7th = 5.8 position
Recall that default was ~6.3 I think it was, so I don't think the player traits are making any difference here.
iezzex said: Where i can find those trainings?
You just manually enter it in your training schedule
First, this is a great tactic. Still proving very difficult to beat.
I have a few questions:
1) Have you ever had a result with Luton (or the worst team) where they finished 1st?
2) What set piece routines do you recommend to use today? I see you recommended Azure before, but that was in 2024.
3) What do you think is the best overall tactic for default FM24 today? Particularly for an underdog team, if that's a necessary distinction
First result for my tactic with default Man City w/ Blue routines, no player selection or anything. I do set the training intensity to 0-0-0-2x-2x though.
I'm thinking I'll run about 10 tests of Luton & Man City each to see how it goes against the Knap tactic.
I've done 2 tests so far of HIGHWAY STAR 4231 P107 FC, which I've seen Cardoni recommend:
Luton default = 4th, 10th
Another thing I'm thinking of doing is having a 3rd crack at player traits. We know that the tactic is very important, and that player instructions are part of this.. so maybe if we have a team given player traits that align perfectly with the Knap tactic, it will do better - even if its because its giving initial familiarity when normally there is zero starting familiarity. So we'll see if anything results from this approach.
There isn't the data yet to confirm one way or the other, but my hunch is that there aren't many attribute interactions going on, simply because the evidence shows almost all the technicals don't matter no matter what.
However I believe there is an interaction between aggression and dirtiness for instance that is crucial. Not just because it's a hypothesis that sounds sensible, but because as I was playing around with the weightings, it just seems to make things work out better.
So it would be good if you could include the ability to create complex formulas as FMSS does, but I don't know how difficult that would be to implement.
I've come up with my own variation of the 4-2-4 formation/Knap tactic that is quite unique I believe, based on a theory I have. Initial results are 5th, 7th, 10th, 3rd as Luton and 6th, 7th as meta team after I've fixed it back up. So possibly equal to the Knap tactic, and perhaps a tweak or two can push it higher. I figure that I would probably only release a tactic if I can get 1st as Luton.
Does anyone know if 1st as Luton has been achieved with a tactic test? Obviously just the default test run, no managing the team throughout the season to achieve it.
Yes, I'm still keen to see your go at it. The more options the better.
I guess with FM27 coming soon, its 50/50 whether people will move on entirely from FM24 or not. But if FM27 turns out to be crap 2.0, then I think these new tools will help keep FM24 alive by injecting a bit of novelty into it.
I started testing with my meta team + Sterling that always seemed to finish a rock solid ~6th.
It didn't take me long to come up with an unusual tactic that finished 5th. However when I tested this with real Luton, they only finished 8th-16th, whereas the Knap tactic can finished as high as 2nd (2nd-10th?). My tactic won with Man City, but only with 89 pts (Knap as high as ~100-110?).
And it's not just my tactic. 424 Mountain King did better than the Knap tactic with my test team from memory, but I didn't get 2nd with it for real Luton.
I tested a bunch more Knap tactics. The results in his spreadsheet don't line up with my results, whereas by contrast it seems that FM Arena's testing is accurate in spite of the methodology critiques I would have of it. Nonetheless all the ones I tried did well, at least 9th for real Luton and often better. But nothing got 2nd like EF 424 IF HP V2 P101 AC.
Of the alternatives I tested, FM24.4HGF4231 V3X RM P107 ALL CUPS seemed the best. 3rd, 6th Luton. Man City 1st 94pts.
Curiously I could use my unusual tactic with several positions I had no player proficiency in at all across my meta team, and yet it still did well. Not quite as good, but it held up well.
Now here's the point we can take beyond FM24:
The results suggest that roles or player instructions are in fact dependent on the attributes of players in some respect.
Yet we also know from the meta team results that it's not what the roles highlight, nor combined team quality.
Injuries, differing player choices, etc. can account for the high variation in the real Luton results relative to the meta team test, but it doesn't explain why only the Knap tactic peaks far higher with real Luton.
One idea I have is that perhaps its not combined team quality, but how each player's attribute is relative to others in his team. In the official guide, they talk of 'absolute' vs 'relative' attributes, and most attributes are 'relative'; perhaps this is what they were actually talking about. There is some suggestive evidence that makes me think along these lines, such as that with finishing, you only need a player with ~7 finishing, but any figure can do the job really, and what happens is whoever in the team has the highest finishing is the one scores the most goals, even if they're a DL with 5 finishing. So we see here that a low attribute altered the tactical outcomes, because of how it was relative to others in the team.
So for instance in my meta team all my players have 8 passing and 13 dribbling, the tactic treats them as all equally likely distribute the task of passing and dribbling I suppose. Perhaps an attribute such as 'teamwork' even influences how well these tasks are evenly distributed throughout the team. But then also for each individual player, they would be more likely to dribble (13) than pass (8).
It's pure speculation, but it would explain why virtually every technical attribute matters zero percent. It would be that the tactic minimizes their influence, and that tactics which don't minimize their influence get beat anyway, whereas Knap's tactic wins almost every match. In other words it could be that just the tactics are broken, rather than that the attributes are also broken. 0 direct passes x 20 passing = effectively 0 passing. Or, 20 direct passes x 20 passing x 0% win rate = 0% win rate for 20 passing.
That's my thinking so far.
18 or less = Don't need competitive matches, but do play in friendlies (u18s/reserves fine) mainly to keep their match sharpness up in order to avoid injury more than development
21+ = Need at least 15 full matches (1350 minutes) per season to develop adequately, 25-35 is ideal, so this is why loans typically become necessary
19-20 = Inbetween the two above
Don't bother bringing on young players for a few minutes at the end of a game. The game counts experience in terms of minutes not appearances, and I suspect it could also be counting it the same way it counts minutes for match sharpness, which is that it counts in precise 11 minute blocks (I think it was 11 minutes.. something near that anyway).
I don't know what HarvestGreen tested them with, but he recommends 0-0-0-2x-2x, and I've played around with it myself before and found that to be best too.
211 = (((10x1182.2185) + 1000.59) / ((10x37.75) + 43.25)) / 0.977272 = 31.1847
331 = (((10x1202.567) + 1000) / ((10x39.62) + 43)) / 1.05 = 28.2454
260 = (((10x1156.35) + 965.23) / ((10x38.98) + 43.00)) / 1.05 = 27.5696
142 = (((10x1135.2835) + 1048.42) / ((10x36.43) + 42.33)) / 1.25 = 24.3981
So here I am trying to take into account outfield + GK + CA efficiency + intensity.
HarvestGreen didn't include the GK stats for 331 as far as I can see, so I've just inserted a high value of 1000. Even with this high value for GK, it doesn't seem as quite as good overall as 214 or 211, though it does have the highest absolute gain in its favor.
There is one more thing to add into the assessment, which is the effect on other various in-game factors:
214 [Physical]x2[Attacking]x2[Quickness Focus]
331 [Physical][Match Practice][Attacking][Defending][Quickness Focus]
211 [Handling][Shot Stopping][Attacking][Physical][Chance Conversion][Aerial Defence][Ground Defence] [Distribution][Quickness Focus]
331 has a slight edge over 214 due to the better balancing of match sharpness.
211 is much better for match sharpness, but is probably going to wear down condition too much during the competitive season, especially if you have weeks with 2 matches. The main problem with 211 is that it would be so finicky to implement that in all likelihood you're not going to implement it properly every week, and the careful handling of condition would add to this. 211 is nonetheless very good for GK and absolute gain, both of which 214 falls a bit short on.
One more thing to say about 214 is that its what I found to be best using a different method previously. So where things are roughly equal, I'm inclined to lean towards it anyway. And in HarvestGreen's assessment, 214 also scores higher on his 'quality' index than these other 2.
So overall I will still be recommending 214. I just realized that 331 was actually my 2nd recommendation before, I didn't realize until now that that was HarvestGreen's recommendation.
It might be worth setting up 211 for your u21s/u18s, especially if they have no competitive league or cup and you can set and forget it with weekly friendlies for the whole season. Reason is, u21s/u18s easily end up in match sharpness ruts they never get out of, and low match sharpness is a big influence on injury rate, and more injuries = less development.
It's splitting hairs between 214 and 331, so if you feel more comfortable going with 331, that's perfectly fine.
One thing left unaddressed is GK focus. HarvestGreen's data used 'Agility and Balance' as GK focus, so we can't be sure of the effect of any others. But it seems to be the case that Agility isn't as critical as a few others: Determination, Reflexes, Concentration. Personally I've started favoring 'GK reactions' because it focuses on two of those (Reflexes, Concentration). But there's no data on this.
142 GK - 1048.42 / 42.33 = 24.76643
211 GK - 1000.59 / 43.25 = 23.14023
260 GK - 965.23 / 43.00 = 22.44721
212 GK - 868.76 / 41.00 = 21.18927
214 GK - 805.20 / 39.33 = 20.45888
211 = 130% GK, 100% Def, 90% Att
214 = 100% GK, 100% Def, 100% Att
260 = 105% GK, 105% Def, 105% Att
142 = 125% GK, 125% Def, 125% Att
..and now, as I was examining HarvestGreen's own rankings, I gradually cottoned to the fact that there's a huge standout error in my data.
214, 211, 142 and 260 are all at the top of his rankings just like mine.. yet he has 331 as the best. I figured there has to be something amiss here, and sure enough, getting ChatGPT to recalculate it gives 1202.567.
That means HarvestGreen's recommendation of 331, would in fact be the best schedule for outfield.
I could have sworn I verified it with ChatGPT as 1020.63 three times just to be sure at the time. So I went back to check, since I still had the convo open:
Fuckin' ChatGPT man..
I presume it got at least most of them right, but now I can't be certain some weren't miscalculated by ChatGPT.
Anyway, at least we know from the backing of HarvestGreen's rankings that 331, 260, 211, 214 and 142 are the top ones and that the numbers are most likely correct for at least those.
You should be aware also this mirroring of HarvestGreen's data is a pleasant unexpected surprise. I did have HarvestGreen's weights as a starting or reference point for Premier League 2.1, but as you can see with Rain's comparison test of HarvestGreen's weights vs. Premier League 2.1, things should have changed substantially in the end. So it's surprising that the favored training schedules nonetheless align.
bf3metro said: If you had to pick only one between 214 and 260 for the entire squad, which one would you use?
I'll get back to you in a day or two, as things are still evolving right now, as you can see from my words above
We have a new top one, that I've highlighted green. This one was actually suggested by tam1236 back in january. He took the HarvestGreen attribute test findings and did a calculation on it to find this as the best training schedule.
It even has pretty good efficiency, though I suspect the workload could be too high to be worth using with all those modules. Very impressive though given it also has one of the highest CA gains (37.75), so it's particularly good if you want to keep your players looking well rounded for aesthetic reasons without compromising on actual performance.
It turns out there are a lot of very high efficiency options above 1000 (so still ~85%+ of the absolute best), and the most efficient is now Recoveryx13. I wouldn't recommend it, but it's interesting there's a profound difference in training quality between rest and recovery on their own.
I've highlighted in yellow some schedules that stand out to me, but I haven't taken a close look yet.
104 [Recovery]x13 = 1008.64 / 17.32 = 58.23557
85 [Match Review] = 1008.62 / 17.40 = 57.96667
100 [Match Review]x2 = 1005.48 / 17.72 = 56.74831
105 [Quickness][Attacking] = 1014.63 / 17.84 = 56.87276
52 [Match Tactics] = 1033.08 / 19.54 = 52.87001
124 [Physical][Quickness][Aerial Defence][Recovery]x10 = 1001.86 / 21.70 = 46.16820
127 [Physical][Quickness][Aerial Defence][Match Review] = 1002.89 / 22.92 = 43.75742
125 [Physical]x2[Aerial Defence] = 1032.49 / 24.20 = 42.66488
126 [Quickness]x2[Aerial Defence] = 1013.15 / 23.92 = 42.35535
122 [Physical][Quickness][Ground Defence] = 1020.02 / 24.26 = 42.04700
116 [Physical]x2[Chance Conversion] = 1022.72 / 24.57 = 41.61579
94 [Physical][Tactical][Recovery]x7 = 1053.14 / 25.88 = 40.69397
118 [Physical]x3[Tactical] = 1042.33 / 25.51 = 40.85927
138 [Physical][Quickness][Resistance][Tactical] = 1046.47 / 26.48 = 39.51926
93 [Physical][Tactical] = 1061.43 / 27.12 = 39.13827
215 [Physical]x3[Attacking] = 1018.42 / 25.91 = 39.30606
213 [Physical]x2[Attacking] = 1043.1425 / 27.79 = 37.53665
95 [Match Practice][Recovery]x7 = 1052.22 / 28.04 = 37.52568
106 [Quickness][Attacking][Overall] = 1051.52 / 28.96 = 36.31077
325 [Physical][Quickness][Resistance][Defending][Defending Engaged] = 1126.288 / 31.62 = 35.61379
321 [Physical][Quickness][Aerial Defence][Attacking] = 1081.229 / 31.46 = 34.36834
340 [Physical]x2[Attacking Wings][Attacking][All in Attack Group] = 1085.2745 / 31.27 = 34.73855
334 [Physical]x2[Aerial Defence][Attacking][All in Defend Group] = 1078.23 / 31.21 = 34.54758
317 [Physical]x2[Chance Conversion][Attacking][All in Attack Group] = 1070.2455 / 30.71 = 34.84811
186 [Physical][Quickness][Aerial Defence][Attacking] = 1074.0845 / 31.24 = 34.38555
53 [Match Practice] = 1038.74 / 30.02 = 34.60293
335 [Physical][Quickness][Ground Defence][Attacking][All in Defend Group] = 1103.957 / 32.56 = 33.90531
96 [Physical][Tactical][Match Practice][Recovery]x7 = 1112.92 / 32.98 = 33.74530
98 [Defending]x3[Attacking]x2[Physical]x3[Match Practice]x2[Ground Defence] = 1112.56 / 33.72 = 32.99525
91 [Attacking]x5[Defending]x5[Match Practice]x2[GoalKeeping][No focus] = 1126.31 / 34.78 = 32.38384
338 [Physical][Match Practice][Attacking][Defending][Recovery]x7 = 1117.508 / 34.99 = 31.93792
112 [Physical][Match Practice][Chance Conversion] = 1117.34 / 35.60 = 31.38596
212 2x Physical + 2x Match Practice + Attack + Defend + Set Pieces = 1126.966 / 35.78 = 31.49709
211 Handling, Shot Stopping, Attacking, Physical, Chance Conversion, Aerial Defence, Ground Defence and Distribution = 1182.2185 / 37.75 = 31.317
149 [Match Practice][Attacking][Match Tactics]x2[Tactical]x2 = 1100.35 / 35.50 = 30.99577
205 Game preset training 1 'Preset-Training Style-Balance' [Overall][Defending][Attacking][Set Piece Routines][Outfield][Recovery]x2 = 1125.04 / 36.50 = 30.82301
97 [Chance creation][Attacking][Aerial Defense][Handling][Defending from the front][Quickness] = 1122.54 / 36.48 = 30.77138
It's a more subjective matter, but what I found is that using home friendly matches against the worst team possible is better than using recovery periods in training.
Friendly matches improve morale, build familiarity, build up match sharpness a lot better, and I daresay even result in less injuries.
When using all recovery I noticed that it tends to result in too low condition and eventually fatigue, so it had to be half recovery half rest, which also can be tedious to set up properly each week.
I can't remember if this is the case, but recovery might also interact differently with the other training modules to produce different results than what it shown in HarvestGreen's spreadsheets.
I’ve been using ZaZ’s Growth 2, but in my save it really isn’t delivering the development I expected.
What I’m mainly looking for is a schedule that pushes CA growth as fast as possible so players reach their PA quickly, rather than just maximizing CA efficiency.
Would you recommend switching fully to something like 260 / 214 / 156 depending on the players’ CA–PA gap, or do you have a specific weekly/monthly rotation you think is optimal in practice?
ZaZ Growth 2 would be 1064.2675-1115.573
Oddly enough the 2-match Physicalx2 Attackingx2 scores better than the Physicalx5 Attackingx5 and results in higher CA gain too.
[Physical]x2[Attacking]x2 = 1115.573 / 33.83 = 32.976
[Physical]x5[Attacking]x5 = 1064.2675 / 27.85 = 38.214
Both of these are very close to the best.
Because CA-PA gap is a critical accelerant to growth, you actually want the lowest overall CA growth possible - while highest in the CA growth where it matters. There is a hard cap on CA per season anyway, which is ~20-25 (someone has reported ~30 i think). If your players aren't developing much, it's more likely that they're over 18 and not getting enough match experience. No match experience for older players can reduce growth to ~1 CA/season.
This time I was able to calculate everything quickly and comprehensively utilizing ChatGPT with HarvestGreen's excel sheets.
I haven't calculated every schedule exhaustively, just the ones you see here, most of which were the most promising previously.
Overall I recommend either 260 [Physical][Match Practice][Attacking]x2[Quickness Focus] for squad with high CA-PA gap or 156 [Physical][Quickness][Transition Restrict][Quickness Focus] with low CA-PA gap. Or 214 [Physical]x2[Attacking]x2[Quickness Focus] for something inbetween.
Weighted attribute improvement:
260: [Physical][Match Practice][Attacking]x2 = 1156.35
142: [Physical][Quickness][Attacking]x3 = 1135.2835
212: 2x Physical + 2x Match Practice + Attack + Defend + Set Pieces = 1126.97
97: [Chance creation][Attacking][Aerial Defense][Handling][Defending from front][Quickness][Quick focus] = 1122.54
338: [Physical][Match Practice][Attacking][Defending][Recovery]x7[Quickness Focus] = 1117.508
214: [Physical]x2[Attacking]x2[Quickness Focus] = 1115.573
149: [Match Practice][Attacking][Match Tactics]x2[Tactical]x2 = 1101.13
139: [Physical][Quickness][Resistance][Defending] = 1091.794
339: [Quickness][Attacking][Match Practice] = 1086.43
243: [Quickness][Match Practice[Attackingx2][Quickness focus] = 1079.689
150: [Attackingx6][Quickness focus] = 1079.6675
334: [Physical]x2[Aerial Defence][Attacking] = 1078.23
90: [Attacking]x3 = 1061.16
466: [Quickness][Physical][Attacking] Additional focus: Ball Control = 1056.47
147: [Attacking][Match Tactics]x3 = 1046.77
164: [Physical][Quickness][Aerial Defence]x2[Match Review] = 1039.84
166: [Resistance][Quickness][Chance Conversion] = 1028.64
156: [Physical][Quickness][Transition Restrict] = 1026.7215
331: [Physical][Match Practice][Attacking][Defending] = 1020.63
160: [Physical][Quickness][Resistance][Transition Restrict]x2 = 1018.89
148: [Attacking][Match Tactics]x3[Tactical]x2 = 1011.46
327: [Quickness][Match Practice][Attacking]x2[Strength Focus] = 1005.93
116: [Physical]x2[Chance Conversion] = 1001.58
65: [Chance Creation] = 1000.90
53: [Match Practice] = 992.97
170: [Endurance][Quickness][Chance Conversion] = 962.78
123: [Quickness][Attacking][Transition Restrict] = 958.12
106: [Quickness][Attacking][Overall] = 948.62
83: [Community Outreach] = 940.47
113: [Quickness][Match Practice][Chance Conversion][Quickness focus] = 927.185
161: [Physical][Quickness][Aerial Defence][Recovery]x7 = 916.81
75: [One on Ones] = 910.01
54: [Attacking Wings] = 907.79
55: [Attacking Patient] = 891.86
99: [Chance Conversion][Match Review] = 848.14
168: [Quickness]x2[Chance Conversion] = 838.56
86: [Rest]Quickness Focus] = 792.26
43: [Rest][No Focus] = 735.1305
Weighted attribute improvement divided by CA cost:
86: [Rest]Quickness Focus] = 792.26 / 17.53 = 45.194
43: [Rest][No Focus] = 735.1305 / 16.85 = 43.628
156: [Physical][Quickness][Transition Restrict] = 1026.7215 / 24.20 = 42.42
166: [Resistance][Quickness][Chance Conversion] = 1028.64 / 25.71 = 40.010
65: [Chance Creation] = 1000.90 / 25.80 = 38.794
139: [Physical][Quickness][Resistance][Defending] = 1091.794 / 28.71 = 38.027
466: [Quickness][Physical][Attacking] Additional focus: Ball Control = 1056.47 / 29.00 = 36.430
334: [Physical]x2[Aerial Defence][Attacking] = 1078.23 / 31.21 = 34.545
214: [Physical]x2[Attacking]x2[Quickness Focus] = 1115.573 / 33.83 = 32.973
338: [Physical][Match Practice][Attacking][Defending][Recovery]x7[Quickness Focus] = 1117.508 / 34.99 = 31.939
212: 2x Physical + 2x Match Practice + Attack + Defend + Set Pieces = 1126.97 / 35.78 = 31.495
142: [Physical][Quickness][Attacking]x3 = 1135.2835 / 36.43 = 31.164
149: [Match Practice][Attacking][Match Tactics]x2[Tactical]x2 = 1101.13 / 35.50 = 31.017
97: [Chance creation][Attacking][Aerial Defense][Handling][Defending from front][Quickness][Quick focus] = 1122.54 / 36.48 = 30.771
339: [Quickness][Attacking][Match Practice] = 1086.43 / 35.72 = 30.416
90: [Attacking]x3 = 1061.16 / 34.98 = 30.335
150: [Attackingx6][Quickness focus] = 1079.6675 / 36.20 = 29.825
260: [Physical][Match Practice][Attacking]x2 = 1156.35 / 38.98 = 29.664
243: [Quickness][Match Practice[Attackingx2][Quickness focus] = 1079.689 / 37.93 = 28.460
331: [Physical][Match Practice][Attacking][Defending] = 1020.63 / 39.62 = 25.759
GK:
142: [Physical][Quickness][Attacking]x3 = 1048.42
260: [Physical][Match Practice][Attacking]x2 = 965.23
214: [Physical]x2[Attacking]x2[Quickness Focus] = 805.20
156: [Physical][Quickness][Transition Restrict] = 717.03
139: [Physical][Quickness][Resistance][Defending] = 662.44
243: [Quickness][Match Practice[Attackingx2][Quickness focus] = 614.57
86: [Rest][Quickness Focus] = 310.616
43: [Rest][No Focus] = 282.70
10x outfield + 1x GK:
260: [Physical][Match Practice][Attacking]x2 = 1138.975
142: [Physical][Quickness][Attacking]x3 = 1127.386
214: [Physical]x2[Attacking]x2[Quickness Focus] = 1087.357
139: [Physical][Quickness][Resistance][Defending] = 1052.762
243: [Quickness][Match Practice[Attackingx2][Quickness focus] = 1037.405
156: [Physical][Quickness][Transition Restrict] = 998.567
86: [Rest][Quickness Focus] = 748.474
43: [Rest][No Focus] = 694.000
Workload:
156: [Physical][Quickness][Transition Restrict] = 95%
260: [Physical][Match Practice][Attacking]x2 = 100%
214: [Physical]x2[Attacking]x2 = 105%
243: [Quickness][Match Practice[Attackingx2][Quickness focus] = 120%
142: [Physical][Quickness][Attacking]x3 = 125%
139: [Physical][Quickness][Resistance][Defending] = 135%
Notes:
Green = The new best training schedules, in my opinion
Light blue = The two schedules I have last recommended. They're both still worth considering.
Deep blue = ZaZ's recommended schedule
Pink = A long time popular meta
Purple = HarvestGreen's last recommendation
Where no focus is listed, it's Quickness Focus.
Workload will be a little inaccurate, as I eyeballed the intensity bars rather than calculated it.
I figured it could be this. I'm using the latest version I believe. I'll try doing a reinstall later on.
You've got it working, and anyone who uses FMSS can use your weights.
Trying to debug code frustrates the hell out of me. I don't know how people willingly do it every day for a living. I've also found it tedious translating the FMST26 weights to GS.
I'm not quite satisfied with the GS weights, especially in light of Rain's recent test, and the 15% discrepancy rate between the FMST26 and GS weights. I want my weights to perform at least slightly better in every respect than anything else ideally. I give 8/10 now though.
I guess Rain's finding that there isn't too much difference overall between different weightings makes sense when you do the math on it.
5/11 players @ +2% = +10% for +2.75 position = +0.55 position per player @ +2%
Maeda (83%) 3.0 vs. Dybala (69%) 6.4 = +14% for +3.4 position
+10% for +2.75 position = +3.63% for +1 position
+14% for +3.4 position = +4.11% for +1 position
Could be just a coincidental correlation, but I reckon it's probably reflecting a consistent effect. The 80%/78%/76%/74% team test does suggest that the % differences can be simplified to addition, as there were strong distinctions in the results.
I'm putting my comparison test of keithb's biggest discrepancies with Premier League 2.1 on hold for now, but if we just take Maeda vs. Heung-Min Son for a quick picture, there's a ~8.9% discrepancy. Let's say in a worst case scenario you sign 4 of your starting 11 as these discrepancies:
8.9% x 4 = 35.6%
If ~4% ≈ 1 position, then 35.6% = 8.9 position
So the most difference you could get from keithb or GS default weights say and mine, or whatever is best, is probably 9th vs 18th.
If we suppose the chance of a Maeda-like discrepancy (+ the curve leading up to Maeda) is ~8% total, then:
1/11 discrepancy ≈ 39.4% chance of -2.22 position
2/11 discrepancy ≈ 17.3% chance of -4.45 position
3/11 discrepancy ≈ 4.6% chance of -6.67 position
4/11 discrepancy ≈ 0.82% chance of -8.9 position
That is to be added on top of the common ~2% difference in ratings.
So let's say its a realistic worst case scenario where its 2x Maeda + 3x identical + 6x the typical ~2% difference:
~15% chance, with result of -7.45 position (i.e. 9 vs 16.45 position)