Generally first season in new division is much easier than 2nd and onwards. Especially in first half of the season you can really overperform and then ride the momentum until the end of season. Second season is usually more in line with your actual squad and tactic strength.
Not sure how it's distributed between two very different positions, but you can't train him in one position to get attributes up and then retrain into another position at no cost. It'll heavily readjust the attributes to fit them into CA with new attribute weights for new position.
Orion said: So basically B Teams that are in non-playable league and play no official matches can be effectively use for player's growth if we just set assistant to 'Arrange a fixture if there is no match in the week'.
As always thank you very much for providing crucial evidence! Expand B teams in non playable leagues actually do play official matches, that is why the assistant isn't scheduling friendlies for majority of the season (only preseason and winter break). You can see the players are getting competitive league appearances but you cannot see the actual matches or schedule.
The issue with B teams is that they are mostly semipro which is kind of awful for development. Different countries do B teams differently though. For example in France a B team is part of the main club, sharing professional status. In most other countries B team is an affiliate.
harvestgreen22 said: Now that I remember it, here's what happened: If the attribute has reached 20, The grow will still be assigned to this attribute, So this part of the distribution is wasted. Expand That is unfortunate. I guess I could switch to some other focus as soon as the first focused attribute hits 20
harvestgreen22 said: The "reputation" in the table is indicates the reputation of the league in which it is playing , Nothing more (and I don't doubt that league prestige affects friendly matches)
All friendlies in the test were against "Very small reputation teams (foreign)" here Expand Fair, I misunderstood the table
harvestgreen22 said: 1.Before, I tested the "friendly matches" by banning matches. I noticed an anomaly when I did a comparison test, so I checked the archive of previous tests and found that the type ofsuspensionI had before was wrong
The correct situation is: Any player, playing in U18s, U23s, friendlies, official leagues, international competitions... :
All games counted as "matches" (regardless of whether it is a league of any prestige ,and How many prestige the opponent have ) will allow players to "grow more" .
2.Two test groups, each with 11 coaches, each responsible for 1 type of training (set in the coach page)
Set all coaches to half stars (all abilities of all 11 coach are = 1) and compare all coach abilities to 5 stars (abilities = 20) :
I only tested it once, and the difference was about 3%, which is a pretty small difference, It could be a random error (That is, the coach has no influence in game.) , Or it could be that the coaching staff's influence is simply very small
Edit 26/2/2025 : A more precise representation of the numbers looks like this:
Before the age of 24, there is basically no need to worry about participating in high Reputation leagues , You can supplement almost 100% growth with friendly matchs.
Starting at age 24: The mechanics change, at this point friendlies no longer get you all the growth, you need to add a certain level of official play. And the Reputation of the official games began to affect growth. Expand Friendlies don't have the same reputation as league games, in fact they are really low - at least that's how I remember it (could be wrong). So more realistic scenario would be 10 rep for friendly maybe even lower, and league games 100+
Recruitment focuses aren't amazing and you'll scout maybe a dozen or two players per month, not even in full. Plus it costs a fortune in lower leagues. Is it more realistic? Sure, but it'll make the game considerably harder
The best tested tactics are so good you don't ever need to change them. And I don't mean just top3, anything above 55 points probably, perhaps even lower.
Obviously you can adjust in certain scenarios, or switch to something else based on personel. And maybe have a backup vs formations you have trouble with.
Rhumble said: Yep , im lost tbh , it could just be me or something is missing somewhere but i just dont see the information in laymans terms, i read and reread the opening post but whether the translation from Chinese to English isnt quite getting through i dont know, if we could know the attributes needed from important down for each position then it might start to make sense. Expand It's not that complicated. Check the table posted. Perhaps easiest is to look at the difference between 1 and 20 for a certain attribute. The bigger the difference more important it is. Couple of examples: - acceleration: at 1 is -103,1 goal difference and at 20 it's +88,2. So that is roughly 190 difference between 1 and 20, a huge effect - off the ball: at 1 is 8,3; at 20 is 10,4. A difference of only 2 goals which is well within the margin of error meaning on a team level it's not doing much.
Padovan said: Did I see that right? Having 1 in first touch improves 4 goals compared to having 20? Damn, the ME is completely broken. Expand There is some error, I wouldn't make huge conclusions with 4 difference, but we can probably say that difference between 1 to 20 first touch isn't much.
@harvestgreen22 If you are doing any more tests on training, could you check how quickness additional focus works if a player already has 20 pace and 20 acceleration? For example with a [Quickness]+[Match Practice]+[Attacking]+[Recovery]x7+[Double Intensity]+[Addtional Focus Quickness] schedule. Mainly interested if CA growth remains the same even though the attributes it targets have reached the maximum.
Steelwood said: As in tactical familiarity, the bar next to intensity on the tactics page. A player's tactical familiarity is increased by training them in that role but I have absolutely no idea whether it affects results Expand That visual representation hasn't worked for years. I think tests also showed no effect. Plus playing in the position and role will give him enough familiarity to perform.
FREVKY said: It certailny is smaller than before, what I meant is that ST formula still covers jumping reach twice. I just wanted to point out that square root of "X to the power of 2" is "X", so there's no need for making it more complex than it should be from mathematical point of view. Expand Yes but it's a general solution. MRL also has "Acc Agi" combo, interestingly without Agi itself as a solo attribute.
FREVKY said: Updated the spreadsheet with your corrected rating evaluation for positions you mentioned. So now for striker it stacks up jumping reach, as it is taken into equation twice (most and least important coefficient - for the latter sqrt((jumping reach)^2) equals just jumping reach. Expand What do you mean? The effect of jumping reach should be much smaller than it was before.
Although honestly I think for now it would be best to just remove the double attributes for the time being. Too much confusion and desperately trying to make it work for very minimal effect.
MrSphinx said: A screenshot of these, for example. I am unclear which training to do on which day Expand Give players 2 days of rest after the game and then schedule 1 quality session per day until the next match. If you run out of days then combine 2 sessions on same day that are least demanding according to intensity bar. At the end fill the leftover slots with recovery.
Orion said: In linear regression you basically check every single feature and select the one that fits to the data the most. Then you exclude that one and check the model with this first feature + the second one. In polynomial regression you allow model to look for 'single' feature but also combination like feature1 x feature2 or feature1 x feature1. If it fits the data better than 'single' feature it will pick that feature. If 'single' feature fits the data better than 'combined features' it will keep the single one. In this model I allowed searching for quadratic equations. And for some cases it turned out that at some point, like for the Forward, Jum x Jum fits the data better than any single feature that was left in the pool. But for example Jum x Jum gives worse fit that just Jum. Expand Yes but the model was working with adjusted numbers. Let me give an example. Average JR in the league is 12, a striker has 17. The way you explained stuff in the original post and later on basically says you take 17-12=5 so you do the calculations with 5. And isn't it possible that quadratic fits well for adjusted number (5) but not the actual number 17? Squaring numbers like 5 is a lot different that 17. Above 8 it basically dominates every other attribute basically double dipping (or triple since it's also the best attribute for a striker anyway).
Edit: Or to put it another way. Comparing JR contribution in above scenario if striker has 17 or 18 JR. Taking numbers at face up value you'd get roughly 1,27 vs 1,40. So a difference of 0,13 which would roughly be the effect of +6 pace. Using adjusted numbers of 5 and 6 makes the scores 0,49 and 0,55 respectively, a difference of 0,06 so half of the previous difference. Still equals +3 pace which feels a lot.
As always thank you very much for providing crucial evidence!
B teams in non playable leagues actually do play official matches, that is why the assistant isn't scheduling friendlies for majority of the season (only preseason and winter break). You can see the players are getting competitive league appearances but you cannot see the actual matches or schedule.
The issue with B teams is that they are mostly semipro which is kind of awful for development. Different countries do B teams differently though. For example in France a B team is part of the main club, sharing professional status. In most other countries B team is an affiliate.
If the attribute has reached 20, The grow will still be assigned to this attribute,
So this part of the distribution is wasted.
That is unfortunate. I guess I could switch to some other focus as soon as the first focused attribute hits 20
All friendlies in the test were against "Very small reputation teams (foreign)" here
Fair, I misunderstood the table
The correct situation is:
Any player, playing in U18s, U23s, friendlies, official leagues, international competitions... :
All games counted as "matches" (regardless of whether it is a league of any prestige ,and How many prestige the opponent have ) will allow players to "grow more" .
2.Two test groups, each with 11 coaches, each responsible for 1 type of training (set in the coach page)
Set all coaches to half stars (all abilities of all 11 coach are = 1) and compare all coach abilities to 5 stars (abilities = 20) :
I only tested it once, and the difference was about 3%, which is a pretty small difference,
It could be a random error (That is, the coach has no influence in game.) ,
Or it could be that the coaching staff's influence is simply very small
Edit 26/2/2025 :
A more precise representation of the numbers looks like this:
Before the age of 24, there is basically no need to worry about participating in high Reputation leagues , You can supplement almost 100% growth with friendly matchs.
Starting at age 24: The mechanics change, at this point friendlies no longer get you all the growth, you need to add a certain level of official play.
And the Reputation of the official games began to affect growth.
Friendlies don't have the same reputation as league games, in fact they are really low - at least that's how I remember it (could be wrong). So more realistic scenario would be 10 rep for friendly maybe even lower, and league games 100+
Obviously you can adjust in certain scenarios, or switch to something else based on personel. And maybe have a backup vs formations you have trouble with.
You could try filtering by scouting knowledge, test it out a bit which level throws out the players with all attributes revealed.
It's not that complicated. Check the table posted. Perhaps easiest is to look at the difference between 1 and 20 for a certain attribute. The bigger the difference more important it is. Couple of examples:
- acceleration: at 1 is -103,1 goal difference and at 20 it's +88,2. So that is roughly 190 difference between 1 and 20, a huge effect
- off the ball: at 1 is 8,3; at 20 is 10,4. A difference of only 2 goals which is well within the margin of error meaning on a team level it's not doing much.
There is some error, I wouldn't make huge conclusions with 4 difference, but we can probably say that difference between 1 to 20 first touch isn't much.
That visual representation hasn't worked for years. I think tests also showed no effect. Plus playing in the position and role will give him enough familiarity to perform.
It doesn't differentiate by role
Yes but it's a general solution. MRL also has "Acc Agi" combo, interestingly without Agi itself as a solo attribute.
What do you mean? The effect of jumping reach should be much smaller than it was before.
Although honestly I think for now it would be best to just remove the double attributes for the time being. Too much confusion and desperately trying to make it work for very minimal effect.
Give players 2 days of rest after the game and then schedule 1 quality session per day until the next match. If you run out of days then combine 2 sessions on same day that are least demanding according to intensity bar. At the end fill the leftover slots with recovery.
In polynomial regression you allow model to look for 'single' feature but also combination like feature1 x feature2 or feature1 x feature1. If it fits the data better than 'single' feature it will pick that feature. If 'single' feature fits the data better than 'combined features' it will keep the single one.
In this model I allowed searching for quadratic equations. And for some cases it turned out that at some point, like for the Forward, Jum x Jum fits the data better than any single feature that was left in the pool. But for example Jum x Jum gives worse fit that just Jum.
Yes but the model was working with adjusted numbers. Let me give an example. Average JR in the league is 12, a striker has 17. The way you explained stuff in the original post and later on basically says you take 17-12=5 so you do the calculations with 5. And isn't it possible that quadratic fits well for adjusted number (5) but not the actual number 17? Squaring numbers like 5 is a lot different that 17. Above 8 it basically dominates every other attribute basically double dipping (or triple since it's also the best attribute for a striker anyway).
Edit: Or to put it another way. Comparing JR contribution in above scenario if striker has 17 or 18 JR. Taking numbers at face up value you'd get roughly 1,27 vs 1,40. So a difference of 0,13 which would roughly be the effect of +6 pace.
Using adjusted numbers of 5 and 6 makes the scores 0,49 and 0,55 respectively, a difference of 0,06 so half of the previous difference. Still equals +3 pace which feels a lot.