Having seen the explosion of Python brilliance into the game this year, coupled with the excellent efforts made by FM Arena in finding what attributes most impact team performance, I'm wondering if as a group we can find a standard for player recruitment.
I know we've had the YKYKYK Balanced filters for previous Genie Scouts, but I'm wondering if we can find a different way. Obviously the most important two attributes are pace and acceleration, irrespective of possession.
However, based on the python model of attributes weighted 5, 3 and 1, I'm wondering if there are filters we can come up with, because even with this system, a lot of the players thrown up are still unattainables like Haaland.
Yet, if you mess with the filters too much, i.e. lower things, you get too few players who don't look great.
I wonder if there is a way we could determine and identify what things equate to match engine performance in individual positions.
I know this could vary from person to person, like I could value passing in my DM, whereas someone else could just want a Lee Cattermole style destroyer with no real ability.
A lot of this is a bit of a ramble, but I'm looking mostly for a discussion, see other people's opinions and see if we can come up with something.
Ultimately I think it's up to you, combine your own experience playing the game with the strongest attributes and the YKYKYK numbers. Personally I like work rate on wing-backs and defensive midfielders, while prioritising speed and dribbling on attacking midfielders and wingers.
Filters will only take people so far, as the best players in the game will always have the superior attributes, especially physically.
When recruiting, I tend to look for those attributes that I consider to be most important and then compare that player with my current starter, using the polygons to assess overall footballing ability.
That's a very good point. However, I do wonder if there is a baseline we can reach where we know a player is going to succeed to a certain degree in the match engine.
Chriswin4 said: That's a very good point. However, I do wonder if there is a baseline we can reach where we know a player is going to succeed to a certain degree in the match engine. Expand
I play lower leagues. At the start of each season and at the mid season mid Point i look at clubs ratings on genie scout (i either use MDW or ykykyky). I record best, worst and the mid point. I do this for league up to and including EPL.
I then rate my players against the mid point of each league and get rid of any that won't make the mid point of the League we expect to be in either this season, at the start, or league above at mid season if we look like getting promoted. My spreadsheet then rates the players current and future ratings as a league value.
I have a calculation for potential rating that applies a likely improvement rate based on age and potential positional improvement.
It works for me. No idea how you would code that with python.
I think the issue I’m having is I’m looking for a more universal approach to us, as a group, finding out which attributes are worth prioritising per position. Using the filters available you can find cheap players, but I’m hoping to find a formula to decipher which players will work on the match engine. Like pace and acceleration are a given, the FM Arena test is great, we know which attributes influence a team’s success. I’m wondering how we can narrow that down to individual players though. So on baseball games, a player with incredible plate vision will get get walked to first base a lot and therefore have a high oBP% which is a measurable metric for player value. I’m looking to see if we can find a way to judge players based on attributes, what they will be able to do in the match engine. Like a winger with 16 speed and acc and 16 dribbling, but like 4 in passing, I want to be sure I can discard them. This might not be possible, I’m just wondering if it is, and here is the best place
Mark said: I play lower leagues. At the start of each season and at the mid season mid Point i look at clubs ratings on genie scout (i either use MDW or ykykyky). I record best, worst and the mid point. I do this for league up to and including EPL.
I then rate my players against the mid point of each league and get rid of any that won't make the mid point of the League we expect to be in either this season, at the start, or league above at mid season if we look like getting promoted. My spreadsheet then rates the players current and future ratings as a league value.
I have a calculation for potential rating that applies a likely improvement rate based on age and potential positional improvement.
It works for me. No idea how you would code that with python. Expand
Its a similar methodology. Its fairly easy tbh. A score of 12 in the lower leagues in england is easily good enough. Non league is 10+ and these players are easy to find on frees. I took Truro from national south to the championship on free signings only and selling some of those for £500k to £1.2m along the way which I put into training facilities rather than players. Some of the players who were a 12 in league 2 played all the way upto the Prem. I also had no scouts at all. Using python you can check the ratings of the best teams in the league, one at a time not a list like on Genie, but I didn't bother as I knew what I was aiming for anyway.
Haaland is a 17+, world class is 15-16, 14 is a good prem player and so on. Championship to league2 is 13-12 and of course a lot of players would be 10-11 in leagues1+2 still, but not good enough for me.
Ps just found my old sheets for non league and I had players rated 9-10 in the squad and initially some of those were starters.
Theoretically you could if you ran enough tests. But the game is too easy as it is with the tools we already have available. Pretty much any rating system on this site will do a good job. To the point that player selection will rarely be a limiting factor in game progress. Club reputation, sponsorships, facilities, country characteristics and similar a the things that will prevent a meteoric rise, not whether player A is 1% better overall than player B.
Also not a fan of league comparisons. Get the best players you can with the budget you have. Whether they are VNN or Championship level doesn't really matter, it's the best you can get at this point in time.
Yarema said: Theoretically you could if you ran enough tests. But the game is too easy as it is with the tools we already have available. Pretty much any rating system on this site will do a good job. To the point that player selection will rarely be a limiting factor in game progress. Club reputation, sponsorships, facilities, country characteristics and similar a the things that will prevent a meteoric rise, not whether player A is 1% better overall than player B. Expand
The progress using python is undoubtedly too fast. Initially I wanted to see test it, fiddle with the code and see how it went. But winning the champions league third year in the prem with Truro was too fast obviously. Although winning the league was harder but that was only because city spent £600m in two seasons and got 100 points two years in a row.
You have to set yourself rules for sure. This could mean only signing a limited number of players each season. Selling your best players or any player who asked to leave because they are too good. If I start a new game I will certainly have rules around transfers and tactics. I have a strong opinion that python is far superior to genie scout, although this is partly because I dont understand how to weight genie scout in the same way. If I did then that would be superior again possibly. Python is also excellent for finding the next best players from 15+.
Chriswin4 said: Having seen the explosion of Python brilliance into the game this year, coupled with the excellent efforts made by FM Arena in finding what attributes most impact team performance, I'm wondering if as a group we can find a standard for player recruitment.
I know we've had the YKYKYK Balanced filters for previous Genie Scouts, but I'm wondering if we can find a different way. Obviously the most important two attributes are pace and acceleration, irrespective of possession.
However, based on the python model of attributes weighted 5, 3 and 1, I'm wondering if there are filters we can come up with, because even with this system, a lot of the players thrown up are still unattainables like Haaland.
Yet, if you mess with the filters too much, i.e. lower things, you get too few players who don't look great.
I wonder if there is a way we could determine and identify what things equate to match engine performance in individual positions.
I know this could vary from person to person, like I could value passing in my DM, whereas someone else could just want a Lee Cattermole style destroyer with no real ability.
A lot of this is a bit of a ramble, but I'm looking mostly for a discussion, see other people's opinions and see if we can come up with something. Expand Another way to decide on the selection filters for the players you buy is to look at the average attributes for the league you play in and create your own filters based on them. Keep in mind though that these will change from time to time so you will need to adjust them accordingly every 6 months I believe.
Chriswin4 said: That's a very good point. However, I do wonder if there is a baseline we can reach where we know a player is going to succeed to a certain degree in the match engine. Expand
josh acheampong is a player who fits this imo. I think he peaked at 12.8 for me but was consistently one of my best players at rb. Was there better out there of course, but his speed and stamina were enough him to be a 7+ every season. His technicals were pretty poor.
keithb said: josh acheampong is a player who fits this imo. I think he peaked at 12.8 for me but was consistently one of my best players at rb. Was there better out there of course, but his speed and stamina were enough him to be a 7+ every season. His technicals were pretty poor. Expand
See I’m having a great year with Faniel Tewelde being my best performing winger, but his key stats for that position aren’t as good as my other winger? I used genie scout and they both have the same consistency, it seems like I’m maybe missing something that influences match engine success. Python is getting me to the pond, but I can’t figure out how to drink.
dzek said: Another way to decide on the selection filters for the players you buy is to look at the average attributes for the league you play in and create your own filters based on them. Keep in mind though that these will change from time to time so you will need to adjust them accordingly every 6 months I believe.
Go to Squad Planner > Report > Comparison
Hope this helped Expand
That is a very helpful suggestion! I’m looking for a way to see how attributes influence match engine performances. Like looking at the chalkboard stats in game, the best performing players rarely have the attributes I believe to be necessary according to FM Arena testing.
Chriswin4 said: That is a very helpful suggestion! I’m looking for a way to see how attributes influence match engine performances. Like looking at the chalkboard stats in game, the best performing players rarely have the attributes I believe to be necessary according to FM Arena testing. Expand To be able to say for each attribute which is better etc you need to use machine learning with AI that tries all possible ways and all combinations of attributes. It might take you as long as it takes to get the new FM out and more.
Chriswin4 said: See I’m having a great year with Faniel Tewelde being my best performing winger, but his key stats for that position aren’t as good as my other winger? I used genie scout and they both have the same consistency, it seems like I’m maybe missing something that influences match engine success. Python is getting me to the pond, but I can’t figure out how to drink. Expand
would need to see pics of both their attributes. Of course you will still have players who get better ratings that look worse on paper, in genie scout and with the python code. But overall the methods work
keithb said: would need to see pics of both their attributes. Of course you will still have players who get better ratings that look worse on paper, in genie scout and with the python code. But overall the methods work Expand
Bilous the under performing winger -
Tewelde the star -
Both playing as Inverted Winger Support on the Left
Both playing as Inverted Winger Support on the Left Expand
1. We can't see their pros and cons on this screen 2. Tewelde is a better dribbler 3. IWs tend to perform better on the opposite side to their feet. Bilous is left-footed and Tewelde is right-footed
If you are playing IWs, I think you would perform better with Bilous on the right
Steelwood said: 1. We can't see their pros and cons on this screen 2. Tewelde is a better dribbler 3. IWs tend to perform better on the opposite side to their feet. Bilous is left-footed and Tewelde is right-footed
If you are playing IWs, I think you would perform better with Bilous on the right Expand
Here they are with the pros and cons, forgot I'd taken those off to see stats.
Sometimes players need time to settle. There is also a lot of variance season to season. I've had same player score 20 goals in one season and 4 goals in the next and then 15 the next, with similar game time and no tactical or team changes. Sometimes it just clicks and it snowballs into a good season and other times it's a struggle. That's why I think this pursuit of absolutes is pointless. In the end it matters how the player performs and not that we improve the rating system by those last few percentage points.
Do you guys believe there is a difference in how human players play on the match engine and how cpu players play in their simulated matches? It just seems there is no correlation between Attributes to on pitch performances for non-human players.
Standard metric is pace and acceleration, with dribbling and jumping reach as tie breakers. Other attributes are cool, but I would rather pay less for a player with very high value on those attributes, than spend ten times the price for someone balanced across all attributes.
Chriswin4 said: Here they are with the pros and cons, forgot I'd taken those off to see stats.
Expand
For me its the dribbling. You could actually try the other guy up front, even though his finishing is poor. Or on the right
Tewelde definitely one of those player's who over performs and also highlights how his pretty awful attributes in most things except speed and dribbling can really not matter.
I had a Spanish player called Ivan, who would have guessed his name, in 23 and all he had was very high dribbling and agility, cuts in from right wing on his dominant left foot and he was unbelievable. His attributes were a little better than your guys but certainly not world class. Not even elite. It's possible the system you play really is really tailored to him cutting in as well.
I’m going to try and take a new job in my save and not spend over £5m on a player and don’t pay more than 50k per week salary. Reckon you can build a team with those rules and win the European Cup?
Chriswin4 said: I’m going to try and take a new job in my save and not spend over £5m on a player and don’t pay more than 50k per week salary. Reckon you can build a team with those rules and win the European Cup? Expand
I made it with TOULOUSE in FRANCE, EUROPA CUP, and next year, CL. 5 CL in 7 years, but without the rules here. But for 2 first years it was near that.
Falbravv said: I made it with TOULOUSE in FRANCE, EUROPA CUP, and next year, CL. 5 CL in 7 years, but without the rules here. But for 2 first years it was near that.
All that with my own Genie ratings. Expand
Interesting, that's a good achievement. I think we've all been able to do something similar, but I'm looking to maximise how cheaply it can be done.
Chriswin4 said: Interesting, that's a good achievement. I think we've all been able to do something similar, but I'm looking to maximise how cheaply it can be done. Expand
The answer is always ont the same thing, you need low CA player, because the game only take in count the CA to adjust Transfer fee and salary
Falbravv said: The answer is always ont the same thing, you need low CA player, because the game only take in count the CA to adjust Transfer fee and salary Expand
Low CA players with high "meta" stats such as pace, acc, dribble and jumping is the way to go.
Floppyaams said: Low CA players with high "meta" stats such as pace, acc, dribble and jumping is the way to go. Expand
Have rebuilt my Dortmund team to have the second lowest wage bill at 700k a week. I have to say, I think I may have messed up as my team doesn’t seem great, despite having players that are high rated in the meta stats and fit the attribute profiles we use on python.
Having seen the explosion of Python brilliance into the game this year, coupled with the excellent efforts made by FM Arena in finding what attributes most impact team performance, I'm wondering if as a group we can find a standard for player recruitment.
I know we've had the YKYKYK Balanced filters for previous Genie Scouts, but I'm wondering if we can find a different way. Obviously the most important two attributes are pace and acceleration, irrespective of possession.
However, based on the python model of attributes weighted 5, 3 and 1, I'm wondering if there are filters we can come up with, because even with this system, a lot of the players thrown up are still unattainables like Haaland.
Yet, if you mess with the filters too much, i.e. lower things, you get too few players who don't look great.
I wonder if there is a way we could determine and identify what things equate to match engine performance in individual positions.
I know this could vary from person to person, like I could value passing in my DM, whereas someone else could just want a Lee Cattermole style destroyer with no real ability.
A lot of this is a bit of a ramble, but I'm looking mostly for a discussion, see other people's opinions and see if we can come up with something.
Ultimately I think it's up to you, combine your own experience playing the game with the strongest attributes and the YKYKYK numbers. Personally I like work rate on wing-backs and defensive midfielders, while prioritising speed and dribbling on attacking midfielders and wingers.
Filters will only take people so far, as the best players in the game will always have the superior attributes, especially physically.
When recruiting, I tend to look for those attributes that I consider to be most important and then compare that player with my current starter, using the polygons to assess overall footballing ability.
That's a very good point. However, I do wonder if there is a baseline we can reach where we know a player is going to succeed to a certain degree in the match engine.
Chriswin4 said: That's a very good point. However, I do wonder if there is a baseline we can reach where we know a player is going to succeed to a certain degree in the match engine.
I play lower leagues. At the start of each season and at the mid season mid Point i look at clubs ratings on genie scout (i either use MDW or ykykyky). I record best, worst and the mid point. I do this for league up to and including EPL.
I then rate my players against the mid point of each league and get rid of any that won't make the mid point of the League we expect to be in either this season, at the start, or league above at mid season if we look like getting promoted. My spreadsheet then rates the players current and future ratings as a league value.
I have a calculation for potential rating that applies a likely improvement rate based on age and potential positional improvement.
It works for me. No idea how you would code that with python.
I think the issue I’m having is I’m looking for a more universal approach to us, as a group, finding out which attributes are worth prioritising per position. Using the filters available you can find cheap players, but I’m hoping to find a formula to decipher which players will work on the match engine. Like pace and acceleration are a given, the FM Arena test is great, we know which attributes influence a team’s success. I’m wondering how we can narrow that down to individual players though. So on baseball games, a player with incredible plate vision will get get walked to first base a lot and therefore have a high oBP% which is a measurable metric for player value. I’m looking to see if we can find a way to judge players based on attributes, what they will be able to do in the match engine. Like a winger with 16 speed and acc and 16 dribbling, but like 4 in passing, I want to be sure I can discard them. This might not be possible, I’m just wondering if it is, and here is the best place
Mark said: I play lower leagues. At the start of each season and at the mid season mid Point i look at clubs ratings on genie scout (i either use MDW or ykykyky). I record best, worst and the mid point. I do this for league up to and including EPL.
I then rate my players against the mid point of each league and get rid of any that won't make the mid point of the League we expect to be in either this season, at the start, or league above at mid season if we look like getting promoted. My spreadsheet then rates the players current and future ratings as a league value.
I have a calculation for potential rating that applies a likely improvement rate based on age and potential positional improvement.
It works for me. No idea how you would code that with python.
Its a similar methodology. Its fairly easy tbh. A score of 12 in the lower leagues in england is easily good enough. Non league is 10+ and these players are easy to find on frees. I took Truro from national south to the championship on free signings only and selling some of those for £500k to £1.2m along the way which I put into training facilities rather than players. Some of the players who were a 12 in league 2 played all the way upto the Prem. I also had no scouts at all. Using python you can check the ratings of the best teams in the league, one at a time not a list like on Genie, but I didn't bother as I knew what I was aiming for anyway.
Haaland is a 17+, world class is 15-16, 14 is a good prem player and so on. Championship to league2 is 13-12 and of course a lot of players would be 10-11 in leagues1+2 still, but not good enough for me.
Ps just found my old sheets for non league and I had players rated 9-10 in the squad and initially some of those were starters.
Theoretically you could if you ran enough tests. But the game is too easy as it is with the tools we already have available. Pretty much any rating system on this site will do a good job. To the point that player selection will rarely be a limiting factor in game progress. Club reputation, sponsorships, facilities, country characteristics and similar a the things that will prevent a meteoric rise, not whether player A is 1% better overall than player B.
Also not a fan of league comparisons. Get the best players you can with the budget you have. Whether they are VNN or Championship level doesn't really matter, it's the best you can get at this point in time.
Yarema said: Theoretically you could if you ran enough tests. But the game is too easy as it is with the tools we already have available. Pretty much any rating system on this site will do a good job. To the point that player selection will rarely be a limiting factor in game progress. Club reputation, sponsorships, facilities, country characteristics and similar a the things that will prevent a meteoric rise, not whether player A is 1% better overall than player B.
The progress using python is undoubtedly too fast. Initially I wanted to see test it, fiddle with the code and see how it went. But winning the champions league third year in the prem with Truro was too fast obviously. Although winning the league was harder but that was only because city spent £600m in two seasons and got 100 points two years in a row.
You have to set yourself rules for sure. This could mean only signing a limited number of players each season. Selling your best players or any player who asked to leave because they are too good. If I start a new game I will certainly have rules around transfers and tactics. I have a strong opinion that python is far superior to genie scout, although this is partly because I dont understand how to weight genie scout in the same way. If I did then that would be superior again possibly. Python is also excellent for finding the next best players from 15+.
Chriswin4 said: Having seen the explosion of Python brilliance into the game this year, coupled with the excellent efforts made by FM Arena in finding what attributes most impact team performance, I'm wondering if as a group we can find a standard for player recruitment.
I know we've had the YKYKYK Balanced filters for previous Genie Scouts, but I'm wondering if we can find a different way. Obviously the most important two attributes are pace and acceleration, irrespective of possession.
However, based on the python model of attributes weighted 5, 3 and 1, I'm wondering if there are filters we can come up with, because even with this system, a lot of the players thrown up are still unattainables like Haaland.
Yet, if you mess with the filters too much, i.e. lower things, you get too few players who don't look great.
I wonder if there is a way we could determine and identify what things equate to match engine performance in individual positions.
I know this could vary from person to person, like I could value passing in my DM, whereas someone else could just want a Lee Cattermole style destroyer with no real ability.
A lot of this is a bit of a ramble, but I'm looking mostly for a discussion, see other people's opinions and see if we can come up with something.
Another way to decide on the selection filters for the players you buy is to look at the average attributes for the league you play in and create your own filters based on them. Keep in mind though that these will change from time to time so you will need to adjust them accordingly every 6 months I believe.
Go to Squad Planner > Report > Comparison
Hope this helped
Chriswin4 said: That's a very good point. However, I do wonder if there is a baseline we can reach where we know a player is going to succeed to a certain degree in the match engine.
josh acheampong is a player who fits this imo. I think he peaked at 12.8 for me but was consistently one of my best players at rb. Was there better out there of course, but his speed and stamina were enough him to be a 7+ every season. His technicals were pretty poor.
keithb said: josh acheampong is a player who fits this imo. I think he peaked at 12.8 for me but was consistently one of my best players at rb. Was there better out there of course, but his speed and stamina were enough him to be a 7+ every season. His technicals were pretty poor.
See I’m having a great year with Faniel Tewelde being my best performing winger, but his key stats for that position aren’t as good as my other winger? I used genie scout and they both have the same consistency, it seems like I’m maybe missing something that influences match engine success. Python is getting me to the pond, but I can’t figure out how to drink.
dzek said: Another way to decide on the selection filters for the players you buy is to look at the average attributes for the league you play in and create your own filters based on them. Keep in mind though that these will change from time to time so you will need to adjust them accordingly every 6 months I believe.
Go to Squad Planner > Report > Comparison
Hope this helped
That is a very helpful suggestion! I’m looking for a way to see how attributes influence match engine performances. Like looking at the chalkboard stats in game, the best performing players rarely have the attributes I believe to be necessary according to FM Arena testing.
Chriswin4 said: That is a very helpful suggestion! I’m looking for a way to see how attributes influence match engine performances. Like looking at the chalkboard stats in game, the best performing players rarely have the attributes I believe to be necessary according to FM Arena testing.
To be able to say for each attribute which is better etc you need to use machine learning with AI that tries all possible ways and all combinations of attributes. It might take you as long as it takes to get the new FM out and more.
So good luck
Chriswin4 said: See I’m having a great year with Faniel Tewelde being my best performing winger, but his key stats for that position aren’t as good as my other winger? I used genie scout and they both have the same consistency, it seems like I’m maybe missing something that influences match engine success. Python is getting me to the pond, but I can’t figure out how to drink.
would need to see pics of both their attributes. Of course you will still have players who get better ratings that look worse on paper, in genie scout and with the python code. But overall the methods work
keithb said: would need to see pics of both their attributes. Of course you will still have players who get better ratings that look worse on paper, in genie scout and with the python code. But overall the methods work
Bilous the under performing winger -
Tewelde the star -
Both playing as Inverted Winger Support on the Left
Chriswin4 said: Bilous the under performing winger -
Tewelde the star -
Both playing as Inverted Winger Support on the Left
1. We can't see their pros and cons on this screen
2. Tewelde is a better dribbler
3. IWs tend to perform better on the opposite side to their feet. Bilous is left-footed and Tewelde is right-footed
If you are playing IWs, I think you would perform better with Bilous on the right
Steelwood said: 1. We can't see their pros and cons on this screen
2. Tewelde is a better dribbler
3. IWs tend to perform better on the opposite side to their feet. Bilous is left-footed and Tewelde is right-footed
If you are playing IWs, I think you would perform better with Bilous on the right
Here they are with the pros and cons, forgot I'd taken those off to see stats.
Sometimes players need time to settle. There is also a lot of variance season to season. I've had same player score 20 goals in one season and 4 goals in the next and then 15 the next, with similar game time and no tactical or team changes. Sometimes it just clicks and it snowballs into a good season and other times it's a struggle. That's why I think this pursuit of absolutes is pointless. In the end it matters how the player performs and not that we improve the rating system by those last few percentage points.
Chriswin4 said: Here they are with the pros and cons, forgot I'd taken those off to see stats.
These are two excellent footballers it's just that one suits the system more
Do you guys believe there is a difference in how human players play on the match engine and how cpu players play in their simulated matches? It just seems there is no correlation between
Attributes to on pitch performances for non-human players.
How to evaluate if it is not clear how the evaluation system for a match works?
Sorry for my English
Standard metric is pace and acceleration, with dribbling and jumping reach as tie breakers. Other attributes are cool, but I would rather pay less for a player with very high value on those attributes, than spend ten times the price for someone balanced across all attributes.
Chriswin4 said: Here they are with the pros and cons, forgot I'd taken those off to see stats.
For me its the dribbling. You could actually try the other guy up front, even though his finishing is poor. Or on the right
Tewelde definitely one of those player's who over performs and also highlights how his pretty awful attributes in most things except speed and dribbling can really not matter.
I had a Spanish player called Ivan, who would have guessed his name, in 23 and all he had was very high dribbling and agility, cuts in from right wing on his dominant left foot and he was unbelievable. His attributes were a little better than your guys but certainly not world class. Not even elite. It's possible the system you play really is really tailored to him cutting in as well.
I’m going to try and take a new job in my save and not spend over £5m on a player and don’t pay more than 50k per week salary. Reckon you can build a team with those rules and win the European Cup?
Chriswin4 said: I’m going to try and take a new job in my save and not spend over £5m on a player and don’t pay more than 50k per week salary. Reckon you can build a team with those rules and win the European Cup?
I made it with TOULOUSE in FRANCE, EUROPA CUP, and next year, CL. 5 CL in 7 years, but without the rules here. But for 2 first years it was near that.
All that with my own Genie ratings.
Falbravv said: I made it with TOULOUSE in FRANCE, EUROPA CUP, and next year, CL. 5 CL in 7 years, but without the rules here. But for 2 first years it was near that.
All that with my own Genie ratings.
Interesting, that's a good achievement. I think we've all been able to do something similar, but I'm looking to maximise how cheaply it can be done.
Chriswin4 said: Interesting, that's a good achievement. I think we've all been able to do something similar, but I'm looking to maximise how cheaply it can be done.
The answer is always ont the same thing, you need low CA player, because the game only take in count the CA to adjust Transfer fee and salary
Falbravv said: The answer is always ont the same thing, you need low CA player, because the game only take in count the CA to adjust Transfer fee and salary
Low CA players with high "meta" stats such as pace, acc, dribble and jumping is the way to go.
Floppyaams said: Low CA players with high "meta" stats such as pace, acc, dribble and jumping is the way to go.
Have rebuilt my Dortmund team to have the second lowest wage bill at 700k a week. I have to say, I think I may have messed up as my team doesn’t seem great, despite having players that are high rated in the meta stats and fit the attribute profiles we use on python.