Han106 said: Well I'm glad that my weight balance has some merit to it! Thanks! Expand
well you done 75% of the work, i just tweaked it a little bit.
@Han106 there's something that i am wondering tho, if i should include consistency in the ratings, since a consistent player does get better ratings ingame (tested with same player, just consistency was modified over one season. difference was like 1.5 points between 1 consistency and 20, and about 0.75 between 10 and 20.) results were like this:
1 consistency 6.50 10 consistency 7.12 20 consistency 7.76 all of the above over 40 games simulated, frozen attributes and no injuries on
Han106 said: On the topic of physical training, everything has to do with the my personal weights and how it effects the results I get. You can read how I made the weights for my experiments below or just read the TL;DR if you can trust the weights I've cooked .
How the Weights for my Training experiments were formed
I made weights that are based on the Chinese Machine Learning FM Study. It's probably the most quality test on attributes we might ever see for some time due to sample size and the process that is AI machine learning. You can find the weights from the experiment called ykykyk balanced here from @Mark's post on it.
Here is an example of the Full Backs for ykykyk balanced.
There was a problem with just copying these weights 1 for 1 for me.
I feel that Physicals were not weighted important enough. When I was playing FM using these weights a lot of players I was being recommended(as a lower league club) were over the hill and were really declining the league in the 2 most important attributes Pace and Acceleration, but had great Technical/Mental skill to "make up" for it.
Then I used the weights that @ZaZ created all ratings under 50 minus 25 weights which @Markbalanced here. These weights fixed this problem for me by decreasing weights on the less important attributes which coincidentally really fixed the importance for the Physical Attributes.
Here is an example of the Full Backs for all ratings under 50 minus 25.
However, the problem with these weights is that I'm using the top tactic in the Patch 24.2.0 (v2.0) - Tactic Testing Table. The Machine Learning Weights are based off of this tactic from FM22. The meta tactics for FM24 are different from 2 years ago with the biggest difference being the role of the Fullback. The IWB played more like a recycle the ball DM which shows in these weights. Now the Fullback has the responsibilities of a Winger, and needs more weights to represent this.
Here is an example of changes I made to my weights to attempt to accomplish this which you can find here .
For example, I raised some weights in things like Passing, Crossing, and Technique to what I felt best emulated the role of a FB in that tactic.
I made tweaks like this to these weights to fit the top tactic for FM 24 for not just Fullback but the other roles as well(but should work other 4231 tactics).
TL;DR The weights are my attempt at mixing Chinese Machine Learning with prioritizing Physical Attributes to fit FM 24.
Because of that, almost all of the weights above 70 in my weights are trained with any sort of Physical training. I have screenshots here underlining these attributes in green.
Looking at these weights, Physical Attributes are weighted as importantly as the center of the universe. Because of that I try to maximize their growth as much as reasonably possible instead of being efficient with just 1 or 2 sessions.
If the results from physical training showed that more is better then I would do more, but it seems the maximum training sessions that grow Physical sessions in a week is 3. So that's why in the foundational 11 training schedule there are 3 physical sessions in it. Expand
I have adjusted these and tested them for a few seasons, seems that you do find the right players for the Katana v3.1 tactic on the tests.
Wail said: Did you figure out how to put them into the lineup tool ? Would be amazing if you could share it, I do like using that tool as the scouting center Expand
Had to stop the work, some family issues but will get back to it. I have an idea, yeah
i'll have a look at it and try to pull some data out then
these are the settting that i want o adjust to a correct value, and also the attributes for a position, thats why i asked about MC AMR/L and WBR/L as they were not on that chinese table.
Only done the GK position as you can see in the pic
the reason why i am using this app is because is simple to use, loads in an instant, can look for players based on your positions from tactic and the best part: you don't see their CA or PA attributes or personality
does this work for any tactic or just the ZAZ one? as i didn't find anything in the chinese table mentioning positions like MC, AML/AMR, WBR/WBL
there is a piece of software named FMLineupTool that can be used to prioritise the atributes needed and i would like to modify the ratings there to suit my needs
hey guys, found one of my old tactics from fm19 and decided to give it a go in fm22 i must say it works even better than in fm19
i havent added any screensots yet but will do in the following days as i started a new save in a vely low league where players are shite here is the resuls so far and the tactic itself:
positives: all team scores (wbr and wbr goals+loads of assists) high numbers of goals scored not very leaky in defence
negatives: counter atacks are a issue hard to get the right players in lower leagues
Mark said: So my work here is now complete. There were some issues. There were 2 of the managers that didn't work because I hadn't taken control of them, That left us with 7 sides we have control of. One of course was Man City whose Manager was sacked every test as they couldn't compete against the ZaZ Blue tactics.
The methodology was to take the best rated XI for each ratings and compare the average ratings for each side. I ran 5 tests and then dropped any player that had less than 50 games over the 5 runs or 190 games. I only selected players rated best from the 7 teams we were working with who all used ZaZ Blue DM tactics.
So they were playing the same role for the majority of the time and played substantial games in the role.
I have to say the results very much favor the Chinese machine learning research we were all interested in.
I tested 6 ratings files plus the default Genie Scout rating file. The main ratings files were ZaZ, my MDW, ykykyk the one based on the Chinese machine learning research, and 3 variants of that proposed by @ZaZ.
I used either end of season team of the year for the squad or the highest positional rating to determine the position for each player. Players with less than 50 games of the 5 tests were excluded. Only players in the 7 controlled teams were included, Arsenal, Chelsea, Leicester, Liverpool, Man Utd, Newcastle, Spurs.
First we have the control test which is the default Genie Scout ratings. Here is their side:
So of the main 3 ratings files, MDW, ykykyk and ZaZ here are the results:
And here are the 3 test tactics from ZaZ using the Chinese machine learning technology.
The Analysis from our Chinese friends has been very impressive, Expand
used this for a while and worked perfect with any teams with impressive results, my question is, how do i supply it to the test? i know is low games but every save it is the same i went from promotion to finishing 2nd two years in a row in the first league then championsver since
this looks interesting
https://fm-arena.com/thread/9313-untested-meta-attribute-training-schedule-v1/
well you done 75% of the work, i just tweaked it a little bit.
@Han106 there's something that i am wondering tho, if i should include consistency in the ratings, since a consistent player does get better ratings ingame (tested with same player, just consistency was modified over one season. difference was like 1.5 points between 1 consistency and 20, and about 0.75 between 10 and 20.)
results were like this:
1 consistency 6.50
10 consistency 7.12
20 consistency 7.76
all of the above over 40 games simulated, frozen attributes and no injuries on
Was just posted a few days ago on fm scout (not making any publicity towards it)
https://www.fmscout.com/a-fmplus24.html
How the Weights for my Training experiments were formed I made weights that are based on the Chinese Machine Learning FM Study. It's probably the most quality test on attributes we might ever see for some time due to sample size and the process that is AI machine learning. You can find the weights from the experiment called ykykyk balanced here from @Mark's post on it.
Here is an example of the Full Backs for ykykyk balanced.
There was a problem with just copying these weights 1 for 1 for me.
I feel that Physicals were not weighted important enough. When I was playing FM using these weights a lot of players I was being recommended(as a lower league club) were over the hill and were really declining the league in the 2 most important attributes Pace and Acceleration, but had great Technical/Mental skill to "make up" for it.
Then I used the weights that @ZaZ created all ratings under 50 minus 25 weights which @Mark balanced here. These weights fixed this problem for me by decreasing weights on the less important attributes which coincidentally really fixed the importance for the Physical Attributes.
Here is an example of the Full Backs for all ratings under 50 minus 25.
However, the problem with these weights is that I'm using the top tactic in the Patch 24.2.0 (v2.0) - Tactic Testing Table. The Machine Learning Weights are based off of this tactic from FM22. The meta tactics for FM24 are different from 2 years ago with the biggest difference being the role of the Fullback. The IWB played more like a recycle the ball DM which shows in these weights. Now the Fullback has the responsibilities of a Winger, and needs more weights to represent this.
Here is an example of changes I made to my weights to attempt to accomplish this which you can find here
For example, I raised some weights in things like Passing, Crossing, and Technique to what I felt best emulated the role of a FB in that tactic.
I made tweaks like this to these weights to fit the top tactic for FM 24 for not just Fullback but the other roles as well(but should work other 4231 tactics).
TL;DR The weights are my attempt at mixing Chinese Machine Learning with prioritizing Physical Attributes to fit FM 24.
Because of that, almost all of the weights above 70 in my weights are trained with any sort of Physical training. I have screenshots here underlining these attributes in green.
Looking at these weights, Physical Attributes are weighted as importantly as the center of the universe. Because of that I try to maximize their growth as much as reasonably possible instead of being efficient with just 1 or 2 sessions.
If the results from physical training showed that more is better then I would do more, but it seems the maximum training sessions that grow Physical sessions in a week is 3. So that's why in the foundational 11 training schedule there are 3 physical sessions in it.
I have adjusted these and tested them for a few seasons, seems that you do find the right players for the Katana v3.1 tactic on the tests.
Feel free to look and please provide a feedback
https://www.mediafire.com/file/0pbx7cv1hsdtnta/attributes+doru.grf/file
Had to stop the work, some family issues but will get back to it. I have an idea, yeah
@Mark The ykykyk balanced ratings file
i'll have a look at it and try to pull some data out then
these are the settting that i want o adjust to a correct value, and also the attributes for a position, thats why i asked about MC AMR/L and WBR/L as they were not on that chinese table.
Only done the GK position as you can see in the pic
the reason why i am using this app is because is simple to use, loads in an instant, can look for players based on your positions from tactic and the best part: you don't see their CA or PA attributes or personality
Mark said: I definitely am. And thanks for asking.
@Mark @ZaZ
does this work for any tactic or just the ZAZ one?
as i didn't find anything in the chinese table mentioning positions like MC, AML/AMR, WBR/WBL
there is a piece of software named FMLineupTool that can be used to prioritise the atributes needed and i would like to modify the ratings there to suit my needs
Please reply guys
found one of my old tactics from fm19 and decided to give it a go in fm22
i must say it works even better than in fm19
i havent added any screensots yet but will do in the following days as i started a new save in a vely low league where players are shite
here is the resuls so far and the tactic itself:
positives: all team scores (wbr and wbr goals+loads of assists)
high numbers of goals scored
not very leaky in defence
negatives: counter atacks are a issue
hard to get the right players in lower leagues
Please provide feedback and enjoy the game
The methodology was to take the best rated XI for each ratings and compare the average ratings for each side. I ran 5 tests and then dropped any player that had less than 50 games over the 5 runs or 190 games. I only selected players rated best from the 7 teams we were working with who all used ZaZ Blue DM tactics.
So they were playing the same role for the majority of the time and played substantial games in the role.
I have to say the results very much favor the Chinese machine learning research we were all interested in.
I tested 6 ratings files plus the default Genie Scout rating file. The main ratings files were ZaZ, my MDW, ykykyk the one based on the Chinese machine learning research, and 3 variants of that proposed by @ZaZ.
I used either end of season team of the year for the squad or the highest positional rating to determine the position for each player. Players with less than 50 games of the 5 tests were excluded. Only players in the 7 controlled teams were included, Arsenal, Chelsea, Leicester, Liverpool, Man Utd, Newcastle, Spurs.
First we have the control test which is the default Genie Scout ratings. Here is their side:
So of the main 3 ratings files, MDW, ykykyk and ZaZ here are the results:
And here are the 3 test tactics from ZaZ using the Chinese machine learning technology.
The Analysis from our Chinese friends has been very impressive,
so what ratings should we use in genie scout?
i know is low games but every save it is the same
i went from promotion to finishing 2nd two years in a row in the first league then championsver since