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.
Orion said: The training data was transformed to show player attributes not as 1-20 but I calculated average value for each attribute for every league. Then for every player I changed his attribute value as (actual_attribute_value - average_attribute_value_in_player_league). This way attributes can also be negative - if player has lower attribute value than average for his league. And that was the data that I used to training the model. So model says 'hey, take this 'new attribute value' for the player and multiply it by his coefficient'. Because of this in theory we should check in what league you are playing, check average attributes values for the players in that league, calculated this new 'difference' attribute and then use coefficient to calculate player 'rating'. To make it easier, and because we compare players that will play in the same league, we will just use original attribute values of players. This may introduce some additional error in the rating calculation, but since this makes calculation so much easier we accept this flaw of the method. Expand
Btw how does this work with double attributes? Like Jum^. If the model uses adjusted values then squaring the full number seems odd and potentially overshadowing everything else.
Example: Related attributes: Positioning, Bounce, Statistic type: Key headers: stat_typeÈ
So key_headers (headers that become goals?) the attributes used by the engine is Positioning and Jumping Reach only? I guess bounce I just a bad translation.
You guys are really cutting up the whole game 😅 Expand
I have been playing Football Manager for a few years now, but I am still struggling to master youth development in the game. While I have had some success with scouting and signing young talent, I often find that my youth academy players don’t develop as well as I hope.
I am currently managing a mid-tier team, and I’ve been investing in facilities and coaching staff, but I still feel like I am missing something. Here are a few specific questions I’m hoping the community can help me with:
- Training Schedules: What’s the best approach for creating personalized training schedules for youth players? Should I focus on specific attributes early on, or aim for balanced development? - Mentoring Groups: How effective are mentoring groups, and how should I set them up to ensure my young players benefit the most? - Game Time: How do you balance giving youth players enough game time without negatively impacting your team’s performance? Is it better to loan them out or keep them in the squad? - Hidden Gems: Are there any tips or tools you use to identify high-potential youngsters in your youth intake?
I’d love to hear any strategies, experiences, or tips you have on this topic. Whether it’s about specific tactics, team instructions, or hidden features in FM, I am all ears!
Thanks in advance for your insights!!! Expand There are some things you can do with development, but the most important part is signing the right kind of players. That means generally a good/great starting point for their age, a good personality and obviously high potential. You can find some training schedules on this forum. Many threads started by harvestgreen22 contain tons of different options and analysis. I'd warn that most of those schedules produce weird players, so perhaps some general principles. You don't actually need that many sessions per week to reach quite close to the cap that the game seems to allow. 3-4 sessions per week on double intensity get you almost there. In the end you can even leave the schedule to your assistant - it should be good enough. One key part of training seems to be the intensity and I'd never leave that to assistant/on default. Either use settings from harvestgreen22 or maybe ZaZ https://fm-arena.com/thread/12971-training-and-resting/ (those under "current test"!). That way you keep your players fresh, with less injuries while still maximising growth.
Mentoring is kind of useless. It's very hard to fix a bad personality. Much better strategy is to simply sign good personalities, when you can afford to.
After players reach about 19 years of age they desperately need game time in order to progress so at that point you either need to give them solid minutes in your team or find a good loan for them.
ClaudeJ said: I might be misremembering, but I think it's been known for years that training just assign ability points the player earn playing matches into a specific group of attributes. And the more reputations the team and the league have, the more ability point are earned.
I must admit I don't understand the hype here. Expand
Kind of, yes. But the extent you can funnel these "earned points" is new. Creating 20/20 players on demand was unheard of.
bigloser said: In my experience it's a lot more. I'm surprised the league rep didn't matter in HG's testing.
B teams not in loadable leagues(like German Regional) usually do not develop much after 18 even if you micro manage the roster to make sure guys get phantom games. This may be CA dependent because the especially bad players that I move to the 2nd team to prevent them taking time from better prospects in the youth team tend get up arrows for a year or so before stopping.
Getting consistent 20-30 minutes of game time in blowouts for the first team gets more development than youth teams.
This may be selection bias since I'm more likely to force game time for high PA players. Expand
Like I said maybe in another thread. Issue with such B teams is that they are semipro. So players don't train full time and they will hardly develop.
juliius said: I hope some of you guys know this, because i don't. How much value do the u18 and u21 games have in comparison to first team football, in terms of generating player growth? I seem to remember first team football being more valuable. Am i wrong? Expand
Youth games aren't much better than friendlies in terms of development
rossbalch said: So here's a question, it seems like league reputation doesn't matter. But what about first team, vs say a "B" team. If you set it up so both the First Team and the B team compete in the same league, do the first team players develop better than the First Team players? Expand The issue with B teams is that they are usually semipro
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.
Because of this in theory we should check in what league you are playing, check average attributes values for the players in that league, calculated this new 'difference' attribute and then use coefficient to calculate player 'rating'.
To make it easier, and because we compare players that will play in the same league, we will just use original attribute values of players. This may introduce some additional error in the rating calculation, but since this makes calculation so much easier we accept this flaw of the method.
Btw how does this work with double attributes? Like Jum^. If the model uses adjusted values then squaring the full number seems odd and potentially overshadowing everything else.
Example:
Related attributes: Positioning, Bounce, Statistic type: Key headers: stat_typeÈ
So key_headers (headers that become goals?) the attributes used by the engine is Positioning and Jumping Reach only? I guess bounce I just a bad translation.
You guys are really cutting up the whole game 😅
Except not all key headers are a goal threat
I have been playing Football Manager for a few years now, but I am still struggling to master youth development in the game. While I have had some success with scouting and signing young talent, I often find that my youth academy players don’t develop as well as I hope.
I am currently managing a mid-tier team, and I’ve been investing in facilities and coaching staff, but I still feel like I am missing something. Here are a few specific questions I’m hoping the community can help me with:
- Training Schedules: What’s the best approach for creating personalized training schedules for youth players? Should I focus on specific attributes early on, or aim for balanced development?
- Mentoring Groups: How effective are mentoring groups, and how should I set them up to ensure my young players benefit the most?
- Game Time: How do you balance giving youth players enough game time without negatively impacting your team’s performance? Is it better to loan them out or keep them in the squad?
- Hidden Gems: Are there any tips or tools you use to identify high-potential youngsters in your youth intake?
I’d love to hear any strategies, experiences, or tips you have on this topic. Whether it’s about specific tactics, team instructions, or hidden features in FM, I am all ears!
Thanks in advance for your insights!!!
There are some things you can do with development, but the most important part is signing the right kind of players. That means generally a good/great starting point for their age, a good personality and obviously high potential.
You can find some training schedules on this forum. Many threads started by harvestgreen22 contain tons of different options and analysis. I'd warn that most of those schedules produce weird players, so perhaps some general principles.
You don't actually need that many sessions per week to reach quite close to the cap that the game seems to allow. 3-4 sessions per week on double intensity get you almost there. In the end you can even leave the schedule to your assistant - it should be good enough.
One key part of training seems to be the intensity and I'd never leave that to assistant/on default. Either use settings from harvestgreen22 or maybe ZaZ https://fm-arena.com/thread/12971-training-and-resting/ (those under "current test"!). That way you keep your players fresh, with less injuries while still maximising growth.
Mentoring is kind of useless. It's very hard to fix a bad personality. Much better strategy is to simply sign good personalities, when you can afford to.
After players reach about 19 years of age they desperately need game time in order to progress so at that point you either need to give them solid minutes in your team or find a good loan for them.
And the more reputations the team and the league have, the more ability point are earned.
I must admit I don't understand the hype here.
Kind of, yes. But the extent you can funnel these "earned points" is new. Creating 20/20 players on demand was unheard of.
B teams not in loadable leagues(like German Regional) usually do not develop much after 18 even if you micro manage the roster to make sure guys get phantom games. This may be CA dependent because the especially bad players that I move to the 2nd team to prevent them taking time from better prospects in the youth team tend get up arrows for a year or so before stopping.
Getting consistent 20-30 minutes of game time in blowouts for the first team gets more development than youth teams.
This may be selection bias since I'm more likely to force game time for high PA players.
Like I said maybe in another thread. Issue with such B teams is that they are semipro. So players don't train full time and they will hardly develop.
How much value do the u18 and u21 games have in comparison to first team football, in terms of generating player growth? I seem to remember first team football being more valuable. Am i wrong?
Youth games aren't much better than friendlies in terms of development
The issue with B teams is that they are usually semipro