2026-05-04, 06:32 AM - Word count:
(This post was last modified: 2026-05-04, 07:09 AM by AustinP0027. Edited 1 time in total.)
Coming over from the ISFL, one of the regular articles that I do over there is a fantasy experts rating. The ISFL has a fantasy league inside its simulation league, and from what I can tell, that hasn’t officially made it to SSL yet. Given it’s something I write about every season over there, I figured it would make an interesting series here to explore what fantasy might look like in the SSL.
To start, I found a rather basic fantasy scoring system.
Now, there were actually a couple other stats in here, mostly around Goalkeepers, but a quick look through the API showed they weren’t an immediate pull directly from the index easily, so I’m leaving them off intentionally (next article!)
Using this scoring, I applied to to all players this season in the majors.
Example:
![[Image: P91hyyp.png]](https://i.imgur.com/P91hyyp.png)
It’s a good start!
There is a wide array of scoring. Given this is just the intro article, I’ll summarize by position.
![[Image: Jx7w6hX.png]](https://i.imgur.com/Jx7w6hX.png)
Immediately you can see two problems. First, just a general data collection issue of multiple positions needing to be parsed independently. Second, and more importantly, there is a HUGE imbalance in positional scoring. Your top position has double the points of your 5th place position.
Looking a little deeper, the top position contains 8 players. The third place position contains 9 players. So your top position averages 100 points per player, while the position two spots behind them average 69.25 points per player.
I’m sure by now you’ve identified what is missing in all of this. Roster spots! Without limiting your roster, total points really don’t mean an imbalance because if you can only roster 1 of the top position, while important, it’s not such a huge imbalance.
But, this is the intro article, so, you’ll have to wait for the next article to see the potential of roster spots and how it impacts potential scoring.
To start, I found a rather basic fantasy scoring system.
| Stat | Points |
|---|---|
| Goal | 10 |
| Assist | 6 |
| Shot | 1 |
| Shot On Goal | 1 |
| Crosses | 0.75 |
| Fouled | 1 |
| Fouls | -0.5 |
| Tackles Won | 1 |
| Interceptions | 0.5 |
| Yellow Cards | -1.5 |
| Red Cards | -3 |
| Penalty Kick Misses | -5 |
Now, there were actually a couple other stats in here, mostly around Goalkeepers, but a quick look through the API showed they weren’t an immediate pull directly from the index easily, so I’m leaving them off intentionally (next article!)
Using this scoring, I applied to to all players this season in the majors.
Example:
It’s a good start!
There is a wide array of scoring. Given this is just the intro article, I’ll summarize by position.
Immediately you can see two problems. First, just a general data collection issue of multiple positions needing to be parsed independently. Second, and more importantly, there is a HUGE imbalance in positional scoring. Your top position has double the points of your 5th place position.
Looking a little deeper, the top position contains 8 players. The third place position contains 9 players. So your top position averages 100 points per player, while the position two spots behind them average 69.25 points per player.
I’m sure by now you’ve identified what is missing in all of this. Roster spots! Without limiting your roster, total points really don’t mean an imbalance because if you can only roster 1 of the top position, while important, it’s not such a huge imbalance.
But, this is the intro article, so, you’ll have to wait for the next article to see the potential of roster spots and how it impacts potential scoring.
![[Image: 6J2WgCi.png]](https://i.imgur.com/6J2WgCi.png)
