[Groundhog]

I'm revisiting the whole player generation part of the sim now, as the rest of the logic is now all in place to create a new universe.

When I started to learn Python one of the first scripts I came up with was a random name generator, to add more flavour to the foreign recruits in my FBCB game. When putting together the player generation code it was also one of the first things I coded. I set out to make it smarter over the weekend, and allow for different settings for each nation - things like hyphenated names, no surnames, middle names, 'I, II, III, IV, Jnr' names, etc. Although names are purely cosmetic, in the world of text sims I personally find little details like this are important because it gives a bit more uniqueness to individual players which for me adds another important layer of non-technical abstraction between the user and the random number generator that's at the core of all simulators.

Each nation has 2 or 3 name files built mostly by text scraping national soccer league team pages on wiki where possible (and a much more manual process where not). In addition there is a name rules csv file in the same folder that determines % of players with no surnames (Portuguese styled sportsmen - Nene, etc.), % of players with ', II' appended at the end or hyphenated names etc., most of which I determined by data scraping every Div I college basketballer and coming up with %s. You can also specify substitute nations and a % chance of the name being chosen from there. For example, I didn't bother scraping Canada names, instead assigning USA as 100% to be chosen instead. For the USA itself there's a slight chance of a 'Puerto Rican' name, etc.

When I run the name generator now, I specify a nation, and it will produce a name, taking into account the different rules, and spit out a first name and a last name.

Player hometowns work in a similar fashion, except are weighted selections, with more populated cities in each nation a better chance of being selected. USA is slightly different as I included state distribution as well. Again using Div 1 basketball rosters I calculated the % of players from different states, and USA hometowns will select the state first, and then a weighted selection of cities from that state.

I also put together a list of US colleges, breaking them down into 5 levels of talent from top tier schools down to division 2. When a US player is generated, there is a greater chance that higher ability players will have attended higher tier schools.

I'm trying to think of a good way to handle non-US players with college experience. Some nations (like Australia) send a lot of kids to US colleges, and the pro league is largely national players who attended US colleges. This is not the norm internationally though, as most European countries in particular have stronger youth systems and there is not as much drive to play in the US college system when they can earn decent money as teens.