Random values for attributes

[Sopel]

As someone who was able to dip into the research world with this edition, I'd like to propose a quick idea regarding the attributes.

But before I start I want to stress that assigning the exact attributes to the player's abilities is the best way to go. My idea is aimed more at the lower levels, it's kind of a "quality of life" change. 

At lower levels, you get less time/opportunities to research certain players (especially youngsters) so assessing the exact number of a certain attribute can be hard and may require a bit of a guesswork which may lead to some over/underestimated attributes.

The simple solution to that would be to adapt the current PA randomization system (negative numbers) into the attributes, like this:
-1 = 1-4
-2 = 5-8
-3 = 9-12
-4 = 13-16
-5 = 17-20

Attributes with these values allow researchers to mark the attributes with a rough estimate of the quality of said attribute - a 1-5 range gives us a nice a clean divider of "terrible, bad, average, good, top-notch"
Also, since it's already working for PA - the "half values" could also be incorporated, basically:
-15 = 3-6
-25 = 7-10
-35 = 11-14
-45 = 15-18
It allows even greater division of attributes that would f.e. help to mark the differences in skill across the team.

This allows the researcher to let the game randomize the stat in a certain value range that actually stays true to the real skill of the player while giving a placeholder stat which lets the researcher work on ironing out these details. Also, it makes the scouting a bit quicker for covering large groups and creating a general draft of new players (mostly youngsters) while still highlighting their positive and negative sides. Also, it would be somewhat of a guideline in case the said player is "transferred" to another scout - the new one can quickly see where the preceding one had a general idea but not the definitive opinion.

The suggestion comes from a personal experience when I could recognize the player's overall skill of the attribute but was forced to either give it an uncertain score or leave it completely up to the randomness of the game - there is simply no middle ground.
Of course, this method shouldn't be used notoriously, especially for established players, but could prove useful for those new in the database/professional football or those coming from countries/leagues where research may be trickier.

[Jimmy Wong]

Reviewed so locked.