Jump to content

perpetua

FM Head Researchers
  • Posts

    5,449
  • Joined

  • Last visited

  • Days Won

    1

perpetua last won the day on September 1 2016

perpetua had the most liked content!

Reputation

828 "You're gonna need a bigger boat"

Retained

  • Member Title
    Turkish Co-Head Researcher

About Me

  • About Me
    Visit forum.turksportal.net for Turkish research

Currently Managing

  • Currently Managing
    F.C. ORDB

Recent Profile Visitors

The recent visitors block is disabled and is not being shown to other users.

  1. Thanks. Already reported and replied in the rhread above.
  2. Your statement is predicated upon the assumption that these players are rated correctly. 40 year old Pepe's pace, for example, is 13. Based on your argument, Szymanski should be rated higher. Perhaps 14 or 15. If that's the case, where do we put a truly fast players like Yusuf Ozdemir or Baris Alper Yilmaz or Osayi-Samuel? 17-18-19? Then what about players who are even faster? In my opinion, there is an irrational desire not to rate any player with less than 10 for speed related attributes. So who should be slow in this database? Nobody? If everyone is fast, then speed isn't a factor that makes a difference between teams, making speed an irrelevant attribute. Suppose every player in the game had tackling of 10 or higher. Then every player can defend well. Even worse is if only very few players had tackling of 15 or higher. Then the entire population of footballers, regardless of position, are stuck in a 6 point range for tackling. Everyone can tackle at a similar level, making it meaningless to have someone who can tackle. Same goes for finishing, first touch, passing, decisions etc. etc. etc. The game guide/manual has always indicated that even an attribute level of 1 is meant to represent a professional player who is weakest in this attribute. Key word here is professional. Not someone playing among friends in a five a side game on the weekends. So that player who has a 1 rating is meant to be miles better than the average person. It's the same with pace. Someone with pace = 1 is a slow professional player but is still an athlete who trains every single day. 10.5 is supposed to be about average speed while 20 is supposed to be extraordinary, once in a generation type of speed. So it makes no sense whatsoever to restrict attribute ratings to the 10-20 range like your argument suggests. It's not a formula. We are able to observe players' top speed as they display it in matches. Not every player displays their top speed in matches, in fact they show their top speed perhaps once a season. Bundesliga publish these statistics and can be seen by anyone. Feel free to peruse those lists and see the differences between players. After taking a look at these, I would suggest the following thought exercise. Is there any logical or empirical reason for us to believe that the slowest Bundesliga players should be faster than approximately 50% of the world's professional footballer population (assuming that speed is normally distributed - I would actually suggest that the distribution of attributes is half-normal, meaning that in theory there should be far more players with a 1 rating than a 20 rating). So there is the challenge. How do you prove that the slowest Bundesliga player is faster than half of all professional footballers. Or if I am right and there are far more players in the world with a 1 rating than players with a 20 rating, then really how much better is Bonucci's 11 from the average player worldwide? Here is a hint, Bundesliga 2 also publish players' top speeds. You'll notice that those are not very different than Bundesliga. That is, despite the decline in playing level the distribution of players' top speed doesn't change. There are plenty of players who have a top speed of 36 km/h in Bundesliga 2, just like Bundesliga. And the lowest outfield players run at approximately 30 km/h. Go down another level and perhaps you'll see a slight change in the distribution but not as drastic as what we see in the game database. So the assumption that Bonucci is faster than at least 50% of the footballer population that the Pace rating of 11 implies doesn't appear to have support in this instance. So why do we have this assumption in the database? I do not know.
  3. I appreciate your comment. What he has been at Fenerbahce is a second striker who takes good advantage of the space created for him by Dzeko. As a result, he has scored quite a few nice goals. Perhaps the Fenerbahce researcher is a bit optimistic on him but I don't really think he's too far off in terms of overall ability (ie. CA). Attributes can always be rated differently through different eyes.
  4. This really isn't a shocker. You have an underpowered (ie. low CA) team full of players who are excellent athletes that can anticipate and have great in match consistency (ie. concentration). The underpowered team is going to be expected to lose most matches, so they will likely face teams that are taking a lot of risks against them. Fortunately the physical ability of the players at their disposal along with dribbling are very suitable to succeed against teams taking risks and leaving a lot of space undefended. On the other hand you have a powerful (ie. high CA) team full of players who are mediocre athletes. The strong team is going to be expected to win most matches, so they will likely come out attacking and taking a lot of risks. In the meanwhile, their opponents are going to consistently park the bus. The lack of athleticism (across the entire team rather than some players) as well as anticipation and concentration (in addition to dribbling) is going to make it difficult for the strong team to break down their opponents. One of the most effective methods of forcing teams parking the bus to open up is goals from set pieces. However the lack of size (jumping/strength) will be an issue for set pieces, further weakened by relatively low anticipation. So they will be very likely to drop points against weaker clubs who will sit back deep and defend against them since the lack of athleticism and anticipation will also leave them vulnerable on the counter. You don't need a whole team of big/strong players for set pieces but a few will certainly help. None means this isn't an option, further handicapping the stronger team. What we would see, in real life, is that opponents would sit deep and force the athletes to play the ball and consistently lose possession. Simply because the team isn't built for that style of play. As for the powerful team, they would recognize that athleticism isn't their strong point but they can keep the ball and not give it away easily. The opposing team, recognizing that the stronger team isn't a threat to beat them with speed, will likely try to pressure high in order to win the ball. So the strong team would play a very patient game, dominating possession to catch the opponent napping and/or exhausting them after a prolonged press. So this experiment is a joint test of AI management sophistication as well as attributes. The fact that the OP went on holiday and delegated all responsibilities to staff is the flaw that, at least partially, contributes to the results in my opinion. In my experience the AI managers are still quite unsophisticated in FM. So any result comparison oriented test leaving the tactical choices to an AI manager will be flawed unless tactical choices were restricted in a way to help these clubs and opponents play as they would in real life. Blaming and calling for attribute rebalancing alone will likely break the game further, leading to more unexpected results for normal teams while trying to fix the fringes. History doesn't repeat but it rhymes. Similar discussions were going on here 20 years ago. As the game evolved, tactical flexibility for the user was restricted in order to minimize odd results arising from users taking tactical choices to extremes. Now it's player attributes. At the very least, we won't see these kinds of player attributes very often. The issue, in my mind, has always been AI manager not having sufficient sophistication to counter a human player and AI tactics being a little too scripted. This game is at its weakest when you observe what your (AI) opponent does and do the exact things to counter it. The above test has done not much more than show this with the fringe squad makeup without realizing. We are in the age of AI now so there is certainly hope for the improvement of this aspect of the game. Just my 2c.
  5. To further add to my last comments. We observe Turkish clubs in European competitions and how physically superior sides (think Northern European and Scandinavian especially) tend to give more trouble to Turkish teams because of their athleticism or physical size (in addition to their . It's probably a useful exercise to make comparisons with how these sides are rated in comparison to players who are playing in Turkey. I suspect you'll come to the same conclusion with most of the Turkish research team that our players, for the most part, are rated quite fairly. Similarly another useful exercise is to compare players who play different positions. After all, a player plays a specific position because of his attributes. Not because it was randomly decided that the player is a winger or a central midfielder. As a general rule, and this is well established in academic articles, central midfielders tend to be the players with the lowest maximum speed. They are followed by central defenders who are second slowest. Then come strikers, then full-backs and finally the fastest players tend to be wingers on average. We should hopefully see this in the game/database as well. It should be quite rare that a central midfielder or central defender has a higher top speed than an average or below average winger in the same league.
  6. Regarding performances: Player performances fluctuate. This is built into the game with various factors such as tactical suitability, personal traits, injury likelihood, fitness to count a few. We rate player ability. Performance is an indicator of ability in the long run, but in the short run (a few weeks or months) performance is not necessarily a good indicator of ability. So while I appreciate that you may wish to see quick improvements or quick reductions of ability tied to performance of individuals, this does not necessarily work well with the rest of the game mechanics (such as the the transfer market or AI behaviour). Regarding ratings of Krunic and some other players in other leagues. This is a choice by the researcher. If certain attributes are high, it means other attributes are low to compensate and vice versa. Do I think Krunic has that level of pace? No. But it is a choice made by his previous club's researcher which we should respect. I am sure you can identify many more players who should probably have a faster top speed than Krunic in other leagues but aren't rated that way. It is difficult to achieve that cross-border consistency mainly because different individuals rate players with their own interpretations and personal biases. This is not too distinct from different professional club scouts watching the same player and coming to different conclusions about the player's skills. This has always been the case. We will, of course, take a good look at Krunic over the next few months and rate him to the best of our ability at the end of the season in preparation of the FM 25 database. Cheers.
  7. Keep in mind that a player's Pace is how fast he runs at full speed. So you can think of it as the speed at which he runs when he's sprinting. Acceleration, on the other hand, is how fast he runs over short distances. So, for a midfielder or a player who plays in a more crowded area of the pitch, acceleration is a much more important attribute to have than pace. So I would suggest thinking of speed not as a single attribute as defined by pace but rather something observed as a combination of attributes. Acceleration is how quickly he reaches his top speed. Agility is how quickly he is able to change direction without losing speed. Balance is how well he is able to maintain his speed when changing direction. Pace is the top speed at which he can travel. Just because a player's top speed is not very high, doesn't mean he's ineffective. It basically means he's more likely to get beaten by a speedy player when caught in a lot of space. So based on what you describe it looks like the Fenerbahce researcher believes that Fenerbahce's midfield players are relatively weak when caught in lots of space while they are more effective in more crowded areas of the pitch. So perhaps you may want to use a playing style that suits those kinds of players to get the best out of them.
  8. If I recall correctly, the option to buy becomes an obligation when Besiktas avoid relegation from the Turkish Super League. So the purchase of the player should happen automatically in the game when Besiktas avoids relegation in the first season.
  9. Hmm. You are correct. Clubs should be ranked by goal difference when equal on points during the season. The other tie breakers (head-to-head or multi team head-to-head) should apply at the end of the season.
  10. Iron Gomis - ok Mustapha Yatabare - he is registered to the Turkish FA as being born on 20.01.1986 Aytaç Kara - he is registered to the Turkish FA as being born on 22.03.1993 Junior Fernandes - ok Thanks!
  11. Arda Kurtulan currently has Albania and Northern Macedonia nationality added as well as his caps for the U21 teams of both nations. I have changed the ordering of his nationalities so Albania is the first nationality, Northern Macedonia is second and Turkiye is third. Hopefully he will make more appropriate decisions in the game based on this.
  12. The way we had requested this was that the new club owner would make a decision to continue the policy or to abandon it. I am not aware of any instances where the policy continues after a change at the top, though that doesn't mean it doesn't happen. Just that nobody has reported it. This may certainly need some tweaking if abandonment of the policy happens every time. I'll log something regarding this and hopefully the developers can take a look under the hood.
  13. We have set the region to correspond to the regional groupings that the Turkish FA uses to group clubs in regional divisions.
  14. @pietonbambe Thanks. The scheduling issue, I defer to folks at SI who are better qualified to deal with it. You will probably need to provide a save game so they can figure out why the match was scheduled on 30/11/2023. This is something I have not observed before. As I wrote in response to feedback provided by others: 1. Angelino's information is entered correctly in the database. I do not know why it is not appearing in the game and there is already a report for this. 2. Turkish cup details were announced too late to be reflected in the initial release of the game. This has already been reported and should hopefully be fixed in a future game update. 3. Galatasaray's first kit is red and yellow. If we set the third kit to also be red and yellow, the third kit will never be used in the game, leaving Galatasaray to use only 2 kits in the game. Also, the kit that you posted has been declared as an alternate 2nd kit to the Turkish FA. GALATASARAY A.Ş. - Kulüp Bilgileri TFF The smart thing to do here, I think, would be to set the striped kit as a Champions League first kit instead so it can be used in the game. Again, until we saw how Galatasaray was going to use this kit, it was prudent not to reflect it as a kit that will never be used in the game. As a final thought, it's probably useful to recognize that we often have to make choices and prioritize certain things when doing research given our deadlines. What you deem as carelessness is more often than not going to be errors which arise from a mismatch between when information is made public and when we have to deliver the data to be included with the game. Or perhaps we may simply prioritize functionality in game (for example Galatasaray's striped kit) rather than aestethics.
  15. I tried to post this in the Bug Tracker but for some reason it just wouldn't post. I started a game as a test in the Turkish league with all players from the top division in Europe loaded into the game as well as all international players from other continents to get a database with approximately 51K players. This should hopefully provide sufficient players in the market to fill the appetite of Turkish clubs. All clubs in the Turkish Super League and Turkish 1. League are subscribed to the continent scouting package, which should allow them to see sufficient transfer targets. My primary goal in running this test was to try to understand why Turkish lower divisions erode in player quality a few seasons into the game. Below is a table which shows the number of players in each CA range as of September (post transfer window close) in 2023, 2024, 2025 and 2026. So the 170 row shows the number of players with CA between 170 and 179; 160 row shows the number of players between 160 and 169 etc. << See uploaded screenshot AI_Player_Hoarding_Table_1.png >>> The table to the left shows evolution of the total number of players in the active divisions. The main observation from this table is the fact that the number of players with 110-149 CA declines quite significantly. The table in the middle shows the evolution of the total number of Turkish players in the active divisions. The 110-119 range declines, the 130-139 range increases, everything else pretty much stays as it should be. The 1-60 range, I'm not paying too much attention since this is a result of the newgen explosion as the game progresses. On the right is a table which shows the evolution of the total number of Foreign players in the active divisions. The decline in the 110-149 range we observed for the total arises from the decline in foreign players. So essentially Turkish clubs aren't signing players from abroad. Is it merely a financial issue? Not really. Most of the clubs have a portion of their wage/transfer budget remaining. They could also use the loan market to supplement their squads, bringing in players who aren't going to be getting much playing time at stronger clubs. But this doesn't appear to happen. Where are these players that could potentially be signed by these clubs, on permanent transfer or on loan? Let's examine this. The table below shows the best 30 clubs. On the left is the best 30 in 2023. On the right is the best 30 in 2026. I am only taking into consideration the best 25 players at the club. Mean shows the average CA of those 25 players. Std shows the standard deviation of CAs of the 25 players. Min shows the CA of the 25th best player at each club. << See uploaded screenshot AI_Player_Hoarding_Table_2.png >>> Avg Diff column shows us the CA difference of the same ranked clubs. For example in 2023 R. Madrid's best 25 has a CA average of 153.7 and they rank first in the world. In 2025 Man City's best 25 has a CA average of 161.4 and they rank first in the world. The first ranked club has improved by 7.8 CA. However this improvement isn't a result of better players in the starting 11. It's a result of better players who would be deemed fringe players in the squad. The weakest player in the top club's 25 player squad has gone up from 115 CA ot 140 CA. The second club's weakest player has improved from 113 to 147. The third weakest club's player has improved from 116 to 139. On average, the best 30 clubs have improved an average of 4.8 CA points for their 25 player squad. And the weakest player of these 30 clubs have improved an average of 18.5 CA points. Should these players on the weaker end of the squad be content with their fringe player status, instead of going elsewhere to play more regularly? If we extend this list to the top 50 clubs, the average CA increases by 4.3 points for the 25 player squad. The weakest player in the squad is higher by an average of 15.5 points. When the top clubs hoard players, the lower divisions start to lack quality as the game progresses and it only takes a matter of 2-3 seasons for this to happen from what I can see. This also impacts the makeup of squads in the game. Stronger clubs (ie. those with a higher CA average for the 25 players) end up with less dispersion in quality while weaker clubs end up with more dispersion in quality, contrary to what we have in the database. Table below shows the average standard deviation for groups of 25 clubs. << See uploaded screenshot AI_Player_Hoarding_Table_3.png >>> 1-25 shows the average standard deviation of the best 25 clubs' squads. Note that in 2023 these clubs have the highest standard deviation, meaning the spread of CAs in these squads is quite large on average. That is, you can have a squad of 25 where the weakest player is 115 and the strongest player is 190, for example. By 2026, the standard deviation is quite a bit lower. When we go down to the 76-100 ranked clubs, in 2023 the squad spread is relatively narrow. So you basically have a squads where the weakest player is 115 and the strongest player is 140. By 2026 the standard deviation is quite a bit higher. If I were to extend this to the 1000th best club, in 2023 the standard deviation in CAs will be around 7-8 while in 2026 it will be around 12-14. I haven't done the number crunching for this using this data but anecdotal evidence tells me the result in the table above will persist.
×
×
  • Create New...