2026-05-19, 04:05 AM - Word count:
Over the past two days, I have been working on a small side project leveraging the SSL APIs to try and answer something I’ve always found really interesting as a sim league and specifically an SSL enthusiast:
And when this idea came to my mind, it did not leave and boy did I find the perfect material for my first ever data/analytics styled article across all the sim leagues! I have always loved reading anything of that sorts and looks like it's my turn to give something to this community through this project (hopefully?).
Introducing Team TPE Analytics to you wonderful folks here!
I was going through the SSL Budget Sheet (It is used for Managerial purposes to check out the pending wage budgets, contracts draft capital available for the upcoming seasons etc.) and I paused at the very starting of the said sheet to see this:
![[Image: image-2026-05-19-144254373.png]](https://i.postimg.cc/s2k5KnVP/image-2026-05-19-144254373.png)
I noticed that the Major XI Average of USP (my team) was close to crossing the 1900 mark (It has crossed now at the time of writing this) and I was curious as to how many other teams at their peak have had their TPE close to the 1900 mark. But unfortunately for me, neither the index nor this page showed me historical data with regards to TPE peaks of the individual organizations. So I set about using many of the SSL APIs to help me find that out and this article is the culmination of all the efforts put in.
I thought it would be interesting to try and reconstruct historical team strength (TPE wise) season-by-season and compare the different SSL eras properly. So here through my findings I was able to collect all the information with regards to TPE from Season 16 onwards (Since the API Call I used only has data from then on). So I ended up building this and the results turned out way more interesting than I expected.
I am making the assumption here that the applicable Regression takes place on the first day of the next season, and hence on the last day of every season selected here, we get to see the Peak TPE of every player in every team. Thereby getting the strongest version of each roster (TPE wise) before regression hits. While it might not match the league recorded data, I feel like it is very close to the actual number nonetheless.
Quote:Which SSL teams were/are actually the strongest at their peak in terms of TPE?
And when this idea came to my mind, it did not leave and boy did I find the perfect material for my first ever data/analytics styled article across all the sim leagues! I have always loved reading anything of that sorts and looks like it's my turn to give something to this community through this project (hopefully?).
Introducing Team TPE Analytics to you wonderful folks here!
I was going through the SSL Budget Sheet (It is used for Managerial purposes to check out the pending wage budgets, contracts draft capital available for the upcoming seasons etc.) and I paused at the very starting of the said sheet to see this:
![[Image: image-2026-05-19-144254373.png]](https://i.postimg.cc/s2k5KnVP/image-2026-05-19-144254373.png)
I noticed that the Major XI Average of USP (my team) was close to crossing the 1900 mark (It has crossed now at the time of writing this) and I was curious as to how many other teams at their peak have had their TPE close to the 1900 mark. But unfortunately for me, neither the index nor this page showed me historical data with regards to TPE peaks of the individual organizations. So I set about using many of the SSL APIs to help me find that out and this article is the culmination of all the efforts put in.
I thought it would be interesting to try and reconstruct historical team strength (TPE wise) season-by-season and compare the different SSL eras properly. So here through my findings I was able to collect all the information with regards to TPE from Season 16 onwards (Since the API Call I used only has data from then on). So I ended up building this and the results turned out way more interesting than I expected.
What this Project Actually Measures:
As part of this Team TPE Analytics, I focused my attention on two key calculations --
1. Peak Top XI Average (PTA) TPE - Essentially the same thing shown as above i.e. the average of the 11 strongest players in a roster TPE wise.
2. Peak Average Team (PAT) TPE - The average of all the players in a roster TPE wise.
How the calculation works:
To calculate the peak TPE of a player for a particular season :
As part of this Team TPE Analytics, I focused my attention on two key calculations --
1. Peak Top XI Average (PTA) TPE - Essentially the same thing shown as above i.e. the average of the 11 strongest players in a roster TPE wise.
2. Peak Average Team (PAT) TPE - The average of all the players in a roster TPE wise.
How the calculation works:
To calculate the peak TPE of a player for a particular season :
- All TPE earned up until the end of that particular season is counted.
- Regression (if applicable) for the season in question is excluded from the count.
I am making the assumption here that the applicable Regression takes place on the first day of the next season, and hence on the last day of every season selected here, we get to see the Peak TPE of every player in every team. Thereby getting the strongest version of each roster (TPE wise) before regression hits. While it might not match the league recorded data, I feel like it is very close to the actual number nonetheless.
Current Historical Highs and Lows:
As of we have a total of100 team averages (in both Peak Top XI Average TPE and Peak Average Team TPE) and as it stands today, here are the top 5 highest and lowest in the rankings:
Top 5 Peak Average Team TPE (since S16)
TPE based Observations:
| Rank | Team | Season | Avg TPE |
|---|---|---|---|
| 1 | União São Paulo | 25 | 1901*(Current Season) |
| 2 | União São Paulo | 24 | 1867 |
| 3 | Schwarzwälder Fußballverein | 17 | 1820 |
| 4 | Hollywood Football Club | 23 | 1807 |
| 5 | Schwarzwälder Fußballverein | 18 | 1786 |
Bottom 5 Peak Average Team TPE (since S16)
Funny how USP dominates at both the ends isn't it?
| Rank | Team | Season | Avg TPE |
|---|---|---|---|
| 96 | Club Deportivo Tenochtitlan | 21 | 934 |
| 97 | Shanghai Dragons | 20 | 921 |
| 98 | União São Paulo | 18 | 895 |
| 99 | União São Paulo | 17 | 694 |
| 100 | União São Paulo | 16 | 623 |
TPE based Observations:
After going through the sheet in its entirety, here are some of the major observations:
1. Schwarzwälder's Pre S20 Expansion Dominance -- While many of the current and new players (myself included) were not present during the SfV domination era before the S20 Expansion drafts, we were just told that it was one of the most dominant teams in SSL. It is only after looking at the data that we see how dominant they were.
If you exclude all the data after S20, the top 4 in highest peak average TPE (both PTA and PAT) is SfV, SfV, SfV and SfV in that order. In an era where the average PTA TPE across the league was in the 1200s range, they had theirs in the 1700-1800 range. They clearly went ahead with a solid game plan in roster construction and executed them perfectly.
If you exclude all the data after S20, the top 4 in highest peak average TPE (both PTA and PAT) is SfV, SfV, SfV and SfV in that order. In an era where the average PTA TPE across the league was in the 1200s range, they had theirs in the 1700-1800 range. They clearly went ahead with a solid game plan in roster construction and executed them perfectly.
2. Consistency? Thy name is Reykjavik -- Reykjavik United is THE most consistently high performing team in this period of SSL. Period. From Season 16 till this current season never once have they dropped their PTA or PAT below the 1500 range. That is roster building masterclass at its finest. Even when not necessarily posting single highest peaks, Reykjavik have always repeated shown up in the upper part of the rankings and thanks to this, they have always stayed near to the title contention as well.
![[Image: image-2026-05-19-160153189.png]](https://i.postimg.cc/J7vLtB5B/image-2026-05-19-160153189.png)
![[Image: image-2026-05-19-160153189.png]](https://i.postimg.cc/J7vLtB5B/image-2026-05-19-160153189.png)
3. União São Paulo, The perfect rebuild blueprint -- As you might have already seen in the table above, USP were the weakest in terms of TPE in Season 16. They were so bad that I can't see any team performing worse than USP wrt the above TPE metrics in the future. So what happened next? A rebuild for the ages. While slowly improving their squad with good users who bought into the system, USP were not that well off in Seasons 17 and 18 as well seeing how in terms of Average TPE, they were just better than themselves from the seasons gone. But through optimizing their builds and keeping an active locker room, now in Season 25, they are the only team to have a PAT and PTA TPE over the 1900 mark. If that's not the culmination of a perfect rebuild, then I don't know what is.
![[Image: image-2026-05-19-161909677.png]](https://i.postimg.cc/wTB1YrQw/image-2026-05-19-161909677.png)
![[Image: image-2026-05-19-161909677.png]](https://i.postimg.cc/wTB1YrQw/image-2026-05-19-161909677.png)
4. More even parity across the league post the S20 Expansion Draft -- I firmly believe that the S20 Draft is what kickstarted SSL into the league what it is today. (And no, it is certainly not because I too am a S20 Class player) From that class on, the league saw an influx of players it did not see before. And more crucially? These players were active - In both the Locker Rooms and in their TPE earning. Because of that, both the PTA and PAT Metrics rose from the 1200s range in the pre S20 era to nearly 1500 right now at the time of writing. The matches certainly have become more interesting to watch, there have been more number of upsets taking place right now and the league itself is in a better place right now. And long may it continue.
![[Image: image-2026-05-19-162421136.png]](https://i.postimg.cc/xdmRy8kL/image-2026-05-19-162421136.png)
![[Image: image-2026-05-19-162421136.png]](https://i.postimg.cc/xdmRy8kL/image-2026-05-19-162421136.png)
So.. These are my two cents on this matter. You can see the entire sheet covering all the Major League teams here. Feel free to use info info in any way shape or form in case anyone here is trying work out on something using this. A very big thanks to all the OMs, AMs and Canadice who responded back consistently when I was asking them questions after questions.. And so concludes my first long form content in Sim Leagues. Thoughts?




