famulor said: Ive seen this "9 important attributes" posted a lot but whenever i press the link it sends me to the tactic testing table. Im sure im missing something so can you explain what im missing here? Expand
That table shows what affects the result at the highest degree.
When it comes to the attributes then it's clearly seen that Acceleration, Pace, Agility, Dribbling, Balance and Vision are the most important attributes.
Ferrari098991 said: Hey, sorry it’s my first FM game and I'm a noob. How do I convert FM file to FMF files so I can use these as a tactic in game? Thanks for the help! Expand
Hi,
You don't need to convert anything.
Tactic files for Football Manager already have *.fmf extension.
If a file has other than *.fmf extension then it isn't a tactic for Football Manager.
runitout said: I did a bunch of PPM testing for strikers one time, and I thought I'd share my results. This is a little long, so tl;dr almost nothing mattered. Sorry to disappoint. Just a disclaimer -- I only did the test with one striker, and it's possible that the PPMs interact with player traits. As I'll explain, if there is such an interaction, I believe it had no effect on my test.
So I had a newgen striker that was amazing, Michael Baroni. Very composed, very fast, good movement. Basically he was good at just about everything, maybe CA 180 or even greater. But he wasn't scoring like I thought he should. It was the usual story -- lots of one-on-ones fired right into the keeper. After reading all the manuals and forums, I thought he would do well with "places shots," and trained him for that. Afterwards, I was second guessing that decision, so hence the motivation for my test.
What I did was fire up a new save in Ligue 1, which has 20 teams. I created 20 clones of Michael Baroni, and put one on every team in Ligue 1. (As an aside, it was interesting to see the salary that the game gave to each clone. It ranged from $22mm/yr for PSG down to $1mm/yr for the poor teams.) I then randomly assigned finishing and movement traits to each clone. I tried four finishing traits -- places shots, shoots with power, lobs keeper, and rounds keeper. I also interacted those with five other traits for movement: no movement trait, beats offside trap, moves into channels, runs with ball often. I was also curious about the "curls ball" trait, so I tried that too. So that's 20 possible combinations: 4 finishing X 5 other traits (4 movement +curls ball). If I had it to do over again, I would have had one test Baroni with no finishing trait, rather than one Baroni with no movement trait. But "lobs keeper" I figured would be basically useless, so would serve as a baseline for comparison for the other finishing traits.
I then simulated the same season four times, rotating which Baroni gets which trait so that it wasn't always a crappy team getting the "shoots with power" trait or whatever. So if you're counting, that's 80 Baroni seasons, with 20 for each finishing trait. I was the Amiens coach, but on vacation mode. The rest I left to the AI. Baroni was good enough to be the first-choice starter on all teams, including PSG. In the first season, I made the mistake of not adjusting injury susceptibility -- it was around 13 or so, and injuries therefore added some noise to the simulation. In subsequent simulations, I set it to 1 for all the Baronis. It was surprising how much time was lost to injury even for the proneness = 1 Baronis: league games missed for the average injury-proned Baroni was 6.5, while for the average non-injury proned Baroni it was 3.68.
On to the results. The outcome variable was goals/90 minutes. Here are the means across the finishing traits: Places: 0.45 Power: 0.45 Rounds: 0.48 Lobs: 0.49
If you are worried that the distribution of g90 is skewed, here are the medians: Places: 0.44 Power: 0.47 Rounds: 0.49 Lobs: 0.47
Long story short, there is almost no difference, nowhere near statistically significant, either taken individually (T-test) or collectively (F-test). I then tested a few other hypotheses that I had, and nothing mattered. For instance, I thought that a player on a good team might face more bunkering and would have fewer one-on-ones. So I looked for whether the impact of the trait differed by media prediction. No dice.
What about movement (and curls ball)? Again, here is average g90: No trait: 0.42 Beats offside trap: 0.44 Moves into channels: 0.53 Runs with ball: 0.48 Curls ball: 0.48
Not exactly inspiring, but "moves into channels" is in fact statistically significant compared to having no movement traits at all. This is the only trait that makes a difference statistically. I mentioned earlier that I dismissed that the PPMs was interacting with attributes. It's possible that such interactions matter, I do not dispute that. But this is a striker who is good at everything, so such interactions are unlikely to matter for this particular exercise. Expand
Those ratings are just your assistant manager opinion about the players' ability and potential but your assistant manager can be very poor at judging these things so I advise you to take those ratings with caution. Also, he can give a 5 star rating to some of your players but it doesn't mean that this player is the best players in the world, it only means that your assistant manager thinks this player is a good player for your team but he might be a very poor player if you put him in a better team.
That table shows what affects the result at the highest degree.
When it comes to the attributes then it's clearly seen that Acceleration, Pace, Agility, Dribbling, Balance and Vision are the most important attributes.
OK, thanks.
How you lined up Man City for this tactic?
I won all trophies! What a great tactic, thanks!
just download the game save for that test and check whether the players were frozen or not
Hi,
You don't need to convert anything.
Tactic files for Football Manager already have *.fmf extension.
If a file has other than *.fmf extension then it isn't a tactic for Football Manager.
I don't find Phoenix v2.0 in the table so I can conclude that it hasn't been tested yet.
got it, thanks
So I had a newgen striker that was amazing, Michael Baroni. Very composed, very fast, good movement. Basically he was good at just about everything, maybe CA 180 or even greater. But he wasn't scoring like I thought he should. It was the usual story -- lots of one-on-ones fired right into the keeper. After reading all the manuals and forums, I thought he would do well with "places shots," and trained him for that. Afterwards, I was second guessing that decision, so hence the motivation for my test.
What I did was fire up a new save in Ligue 1, which has 20 teams. I created 20 clones of Michael Baroni, and put one on every team in Ligue 1. (As an aside, it was interesting to see the salary that the game gave to each clone. It ranged from $22mm/yr for PSG down to $1mm/yr for the poor teams.) I then randomly assigned finishing and movement traits to each clone. I tried four finishing traits -- places shots, shoots with power, lobs keeper, and rounds keeper. I also interacted those with five other traits for movement: no movement trait, beats offside trap, moves into channels, runs with ball often. I was also curious about the "curls ball" trait, so I tried that too. So that's 20 possible combinations: 4 finishing X 5 other traits (4 movement +curls ball). If I had it to do over again, I would have had one test Baroni with no finishing trait, rather than one Baroni with no movement trait. But "lobs keeper" I figured would be basically useless, so would serve as a baseline for comparison for the other finishing traits.
I then simulated the same season four times, rotating which Baroni gets which trait so that it wasn't always a crappy team getting the "shoots with power" trait or whatever. So if you're counting, that's 80 Baroni seasons, with 20 for each finishing trait. I was the Amiens coach, but on vacation mode. The rest I left to the AI. Baroni was good enough to be the first-choice starter on all teams, including PSG. In the first season, I made the mistake of not adjusting injury susceptibility -- it was around 13 or so, and injuries therefore added some noise to the simulation. In subsequent simulations, I set it to 1 for all the Baronis. It was surprising how much time was lost to injury even for the proneness = 1 Baronis: league games missed for the average injury-proned Baroni was 6.5, while for the average non-injury proned Baroni it was 3.68.
On to the results. The outcome variable was goals/90 minutes. Here are the means across the finishing traits:
Places: 0.45
Power: 0.45
Rounds: 0.48
Lobs: 0.49
If you are worried that the distribution of g90 is skewed, here are the medians:
Places: 0.44
Power: 0.47
Rounds: 0.49
Lobs: 0.47
Long story short, there is almost no difference, nowhere near statistically significant, either taken individually (T-test) or collectively (F-test). I then tested a few other hypotheses that I had, and nothing mattered. For instance, I thought that a player on a good team might face more bunkering and would have fewer one-on-ones. So I looked for whether the impact of the trait differed by media prediction. No dice.
What about movement (and curls ball)? Again, here is average g90:
No trait: 0.42
Beats offside trap: 0.44
Moves into channels: 0.53
Runs with ball: 0.48
Curls ball: 0.48
Not exactly inspiring, but "moves into channels" is in fact statistically significant compared to having no movement traits at all. This is the only trait that makes a difference statistically. I mentioned earlier that I dismissed that the PPMs was interacting with attributes. It's possible that such interactions matter, I do not dispute that. But this is a striker who is good at everything, so such interactions are unlikely to matter for this particular exercise.
The attack is good but the defense is a bit weak... https://fm-arena.com/table/6-patch-20-4-4/page-3/?mark=585
I just stumbled across this interesting tactic by dimartino - https://fm-base.co.uk/threads/crazy-5230-no-midfileders-no-strikers-everything-should-go-wrong-and-yet-you-win.164154/
He tested it with Sirius
Can you test it?
Thanks.