Tutoring your players to help their development is starting to become common practice in FM. After all, it works in real life as well and with FM17 being a pretty accurate simulation, it will work in the game. Think Ibrahimovic helping out Rashford, Henry and Bergkamp trying to tutor Anelka, Rijkaard helping out the entire Ajax ’95 team. The question remains; how effective exactly is this tutoring? That’s what this article is trying to find out.
In order to research the influence of these factors, I created nine equal newgens in an FM17 save with the help of FMRTE. All have similar positions and age. All of their attributes, including hidden, are set to 10. This means that their development should be pretty much similar.
In a previous research, I ended up with slightly flawed results. By using SI’s own in-game editor, I was able to access the recommended current ability function, which indicated that a player with every attribute set to 10 needed a matching current ability level of 64.
The idea is to run a holiday save for half a season. During this half season, the players will be kept uninjured and motivated by using FMRTE after each match. Their current ability will be too low for them to reach the first team, so this factor is effectively eliminated. After half a season, I will note their development in the following areas:
- Current ability;
- Player Preferred Moves.
The control group
After six months, extracting the relevant data was not that difficult. I started off with the control group.
The numbers are pretty much the same. There are minor differences between the players, which could be attributed to the number of matches these players have played in the youth squad. For those of you who prefer a more graphic representation, please check out the radar chart below.
The Help Improve group
The next group to extract data from was the group that was being tutored using the “help improve” function.
Again, a nice and even spread between the various players. They all played a similar number of matches. For those of you who prefer a more graphic representation, please check out the radar chart below.
The Mentor group
The final group to extract data from was the group that was being tutored using the “mentor” function.
There are significant differences between these players. These cannot be explained for because of the number of games each player played. After looking back, it turns out the player lacking in development had his tutoring cancelled because of an injury to his mentor. That might explain the lack of development compared to the others. For those of you who prefer a more graphic representation, please check out the radar chart below.
Now before anyone starts about the size of the groups, I do realise that the groups are far too small for any conclusive evidence. That isn’t the objective of the experiment. There are too many variables at play to even say anything conclusive with a larger group. This experiment can signal certain trends and help in that regard. This is the data when the average of each group is compared.
Apart from the Personality category, there are no significant differences between the various groups. A point is the maximum difference in all the other categories. That’s so small and could be causes by a myriad of factors, so nothing conclusive can be said about this. For those of you who prefer a more graphic representation, please check out the radar chart below.
What we can conclude is that more research is needed and would be nice. The “mentor”-option of tutoring clearly helps to improve a player’s personality and increases the chances of PPM transferal, but that’s the only conclusion we can draw from this article. As for the impact on the overall development of players, tutoring seems to help, though it does not seem to make a large impact.