DSFL Pre-Season Power Rankings
TLDR: FINAL PRE-SEASON DSFL POWER RANKINGS
Minnesota 0.6546
Portland 0.6345
Myrtle Beach 0.6028
Tijuana 0.5921
Kansas City 0.5764
Norfolk 0.5091
Dallas 0.4971
London 0.4767
Confused? Read the method section.
Hey all, welcome to the first week of the Isidore94 DSFL Power Rankings. This power ranking was inspired by fellow DSFL member, Colabear, and his community power rankings http://nsfl.jcink.net/index.php?showtopic=20156. In my eyes, the community was nearly spot on, but something just wasn’t sitting right with me. Portland Pythons were ranked the worst team, worse than even the two new expansion teams, the Dallas Birddogs and the London Royals. My view of the draft was that the Pythons had a fantastic showing and addressed some critical needs early on. They set the pace for the draft and triggered the fire sale of DB’s early on. Now, I’m no python fan boy. As a member of the London Royals, I’m all for teams being ranked below my team. That being said, I felt the community was severely underrating the Pythons, so I sought to validate my suspicion with empirical data.
Method
I will begin this power ranking by explaining the basic method I use. I will refer to it from here on out in future posts, unless things change, in which case I will provide update method posts in that particular week’s power rankings. Firstly, I compiled a list of all 57 TPE and above players on every DSFL team, as the TPE tracker was not functioning at this time. As you can suspect, this took a metric assload of time. Once I had every player documented, and organized by team, position, and TPE, I began creating an excel page and writing some basic scripts to automate the rest of the process. I decided for the preseason, I will only use the team’s best possible lineup for a formation that uses 1 QB, 1 RB, 3 WR, 1 TE and 5 OL. I inserted the best players for each of those roles into the calculations. For positions exceeding 1 player, I averaged out their scores. After this was done I proceeded to weigh each position based on importance. QB and RB made up 30% of the score respectively. OL and TE made up 10% each and WR’s made up 20%. This weighting is of course up for debate, and will be tinkered with as the season progresses. For teams without OL I inserted 60 TPE bots into the calculations.
For defense, I utilized a nickel formation, and again selected the best players. I realize some teams will run heavy 4-3 formations. I will adjust the rankings mid-season to reflect each teams particular style of defense. As it stands now, Nickel will be the defacto formation, utilizing 2 DT, 2 DE, 2 LB, 3 CB and 2 S. After receiving some feedback, I settled on a weighting of DB’s (CB and S) at 25% each, LBs at 20%, and DT and DE at 15% each. Finally, I ignored kickers all together as I was unsure of how to balance them in regards to averaging out a score for a final score that I would use to compare the league with. Sorry kickers
Finally, I did some math to create a spectrum of scores ranging from 0.2-1, with scores closer to 1 being better and 0.2 being the bare minimum of what a team could achieve by fielding all 50 TPE players. I created the spreadsheet to calculate both offensive, defensive, and combined power rankings for each team. Each week I will update player TPE values as time goes on, in addition to finding ways to attribute coaching styles and play calling (i.e. averaging player weighting differently for each team.) In addition, in the future I will use the tool to explore the differences in skill in various position groups for each team if there is interest in media such as that. It should be noted that while this is a very objective process, the degree to which I weigh each position is up for debate. I will note any feedback in the comments and attempt to improve the tool with each passing week.
Results
Offensive Power Rankings
Minnesota: 0.7908
Tijuana: 0.7069
Myrtle Beach: 0.6827
Kansas City: 0.6795
Portland: 0.6707
Dallas: 0.5939
Norfolk: 0.5805
London: 0.5367
The first thing I want to note about this ranking is how much better the Grey Duck offense is to anyone else’s. Having such good RBs and QB’s is huge for the way the power rankings are developed here, and by far they have two of the best. It’s also important to understand how the numbers work. A score of 1 would infer a team of all 250 TPE players, which is the cap of the DSFL and the cap I used for sake of this power ranking (prevents letting 1 player sway the rankings too much). For reference, there are 3 WR’s taken account for here, which means a single 250 TPE WR would only increase the score of a team by 0.06. A 250 TPE QB on the other hand would contribute a whopping 0.3, which represents nearly half the score of a team like the Dallas Birddogs. RBs are every bit as important in the DSFL and also account for the same amount. This is why the Grey ducks are by far the best offensive team here. There is a sharp drop off to Tijuana, Myrtle Beach, Kansas City and Portland who all inhabit the second tier of offense. Another interesting thing to note is that Dallas, an expansion team, is actually rated higher than Norfolk, a team with a leg up in terms of time in the league. Finally, I would also like to point out that the Pythons are indeed NOT in last place here. But offense is only half the story, and it is in the defense that I make my case for the pythons
Defensive Power Rankings
Portland: 0.5983
Myrtle Beach: 0.523
Minnesota: 0.5183
Tijuana: 0.4772
Kansas City: 0.4732
Norfolk: 0.4376
London: 0.4166
Dallas: 0.4003
Portland, with a massive 0.075 lead on the next nearest defense, is by far the best defense in this league according to these power rankings. Slept on by nearly everyone, Portland managed to fix their weakness at CB and inject a lot of elite talent at DB. Due to the way I took DB’s into account, this has even more effect than drafting 3 strong pass rushers. I want to note that even when I originally had each position being weighed equally, Portland was still #1 or #2. This isn’t the case of be picking numbers to benefit them, they really are just that good. Now, is it possible that I messed up and missed a player somewhere? Definitely.
If anybody sees a giant error, please let me know. But, if all this is accurate, then the Portland Pythons are the #1 most slept on team in the league. I also want to note that defensive scores are indeed lower than offensive ones. This is because there’s no position with just 1 player that can dominate the averages. Defense requires a whole team effort and 1 player alone cannot pull up a bad defense, the way an elite QB can for an offence. It’s just the nature of sim, hence why the expansion teams took QB’s with their first picks. Therefore, these rankings can’t be used to determine if a defense or an offence is going to be better than each other. It’s only used to rank defenses against other defenses.
In terms of the other teams, there’s a clear tier 2 with the Grey Ducks and the Buccs. The 3rd tier is inhabited by the Luchadores and the Coyotes. Finally, the Norfolk SeaWolves, Royals, and Birddogs all occupy the 4th tier.
FINAL PRE-SEASON DSFL POWER RANKINGS
Minesotta 0.6546
Portand 0.6345
Myrtle Beach 0.6028
Tijuana 0.5921
Kansas City 0.5764
Norfolk 0.5091
Dallas 0.4971
London 0.4767
So there you have it. The community rankings are the exact same as my rankings with the exception of the Pythons being in 2nd and not dead last. I found it funny reading the community power rankings to see even the Pythons think they suck. Portland, ya’ll are good. Ya’ll are really good and you have a chance to make some noise. I’d say Minnesota is still a clear favorite as the #1 but Portland does make a case for tier 1 and at least high tier 2 status. The Bucs, Luchadores and Coyotes are all tier 2-3 talent. Finally, the SeaWolves, Royals and Birddogs all are 4th tier talent. It’s worth nothing that Dallas does have a significantly higher score than the Royals.
Please leave feedback below! Cheers
1484 words
TLDR: FINAL PRE-SEASON DSFL POWER RANKINGS
Minnesota 0.6546
Portland 0.6345
Myrtle Beach 0.6028
Tijuana 0.5921
Kansas City 0.5764
Norfolk 0.5091
Dallas 0.4971
London 0.4767
Confused? Read the method section.
Hey all, welcome to the first week of the Isidore94 DSFL Power Rankings. This power ranking was inspired by fellow DSFL member, Colabear, and his community power rankings http://nsfl.jcink.net/index.php?showtopic=20156. In my eyes, the community was nearly spot on, but something just wasn’t sitting right with me. Portland Pythons were ranked the worst team, worse than even the two new expansion teams, the Dallas Birddogs and the London Royals. My view of the draft was that the Pythons had a fantastic showing and addressed some critical needs early on. They set the pace for the draft and triggered the fire sale of DB’s early on. Now, I’m no python fan boy. As a member of the London Royals, I’m all for teams being ranked below my team. That being said, I felt the community was severely underrating the Pythons, so I sought to validate my suspicion with empirical data.
Method
I will begin this power ranking by explaining the basic method I use. I will refer to it from here on out in future posts, unless things change, in which case I will provide update method posts in that particular week’s power rankings. Firstly, I compiled a list of all 57 TPE and above players on every DSFL team, as the TPE tracker was not functioning at this time. As you can suspect, this took a metric assload of time. Once I had every player documented, and organized by team, position, and TPE, I began creating an excel page and writing some basic scripts to automate the rest of the process. I decided for the preseason, I will only use the team’s best possible lineup for a formation that uses 1 QB, 1 RB, 3 WR, 1 TE and 5 OL. I inserted the best players for each of those roles into the calculations. For positions exceeding 1 player, I averaged out their scores. After this was done I proceeded to weigh each position based on importance. QB and RB made up 30% of the score respectively. OL and TE made up 10% each and WR’s made up 20%. This weighting is of course up for debate, and will be tinkered with as the season progresses. For teams without OL I inserted 60 TPE bots into the calculations.
For defense, I utilized a nickel formation, and again selected the best players. I realize some teams will run heavy 4-3 formations. I will adjust the rankings mid-season to reflect each teams particular style of defense. As it stands now, Nickel will be the defacto formation, utilizing 2 DT, 2 DE, 2 LB, 3 CB and 2 S. After receiving some feedback, I settled on a weighting of DB’s (CB and S) at 25% each, LBs at 20%, and DT and DE at 15% each. Finally, I ignored kickers all together as I was unsure of how to balance them in regards to averaging out a score for a final score that I would use to compare the league with. Sorry kickers
Finally, I did some math to create a spectrum of scores ranging from 0.2-1, with scores closer to 1 being better and 0.2 being the bare minimum of what a team could achieve by fielding all 50 TPE players. I created the spreadsheet to calculate both offensive, defensive, and combined power rankings for each team. Each week I will update player TPE values as time goes on, in addition to finding ways to attribute coaching styles and play calling (i.e. averaging player weighting differently for each team.) In addition, in the future I will use the tool to explore the differences in skill in various position groups for each team if there is interest in media such as that. It should be noted that while this is a very objective process, the degree to which I weigh each position is up for debate. I will note any feedback in the comments and attempt to improve the tool with each passing week.
Results
Offensive Power Rankings
Minnesota: 0.7908
Tijuana: 0.7069
Myrtle Beach: 0.6827
Kansas City: 0.6795
Portland: 0.6707
Dallas: 0.5939
Norfolk: 0.5805
London: 0.5367
The first thing I want to note about this ranking is how much better the Grey Duck offense is to anyone else’s. Having such good RBs and QB’s is huge for the way the power rankings are developed here, and by far they have two of the best. It’s also important to understand how the numbers work. A score of 1 would infer a team of all 250 TPE players, which is the cap of the DSFL and the cap I used for sake of this power ranking (prevents letting 1 player sway the rankings too much). For reference, there are 3 WR’s taken account for here, which means a single 250 TPE WR would only increase the score of a team by 0.06. A 250 TPE QB on the other hand would contribute a whopping 0.3, which represents nearly half the score of a team like the Dallas Birddogs. RBs are every bit as important in the DSFL and also account for the same amount. This is why the Grey ducks are by far the best offensive team here. There is a sharp drop off to Tijuana, Myrtle Beach, Kansas City and Portland who all inhabit the second tier of offense. Another interesting thing to note is that Dallas, an expansion team, is actually rated higher than Norfolk, a team with a leg up in terms of time in the league. Finally, I would also like to point out that the Pythons are indeed NOT in last place here. But offense is only half the story, and it is in the defense that I make my case for the pythons
Defensive Power Rankings
Portland: 0.5983
Myrtle Beach: 0.523
Minnesota: 0.5183
Tijuana: 0.4772
Kansas City: 0.4732
Norfolk: 0.4376
London: 0.4166
Dallas: 0.4003
Portland, with a massive 0.075 lead on the next nearest defense, is by far the best defense in this league according to these power rankings. Slept on by nearly everyone, Portland managed to fix their weakness at CB and inject a lot of elite talent at DB. Due to the way I took DB’s into account, this has even more effect than drafting 3 strong pass rushers. I want to note that even when I originally had each position being weighed equally, Portland was still #1 or #2. This isn’t the case of be picking numbers to benefit them, they really are just that good. Now, is it possible that I messed up and missed a player somewhere? Definitely.
If anybody sees a giant error, please let me know. But, if all this is accurate, then the Portland Pythons are the #1 most slept on team in the league. I also want to note that defensive scores are indeed lower than offensive ones. This is because there’s no position with just 1 player that can dominate the averages. Defense requires a whole team effort and 1 player alone cannot pull up a bad defense, the way an elite QB can for an offence. It’s just the nature of sim, hence why the expansion teams took QB’s with their first picks. Therefore, these rankings can’t be used to determine if a defense or an offence is going to be better than each other. It’s only used to rank defenses against other defenses.
In terms of the other teams, there’s a clear tier 2 with the Grey Ducks and the Buccs. The 3rd tier is inhabited by the Luchadores and the Coyotes. Finally, the Norfolk SeaWolves, Royals, and Birddogs all occupy the 4th tier.
FINAL PRE-SEASON DSFL POWER RANKINGS
Minesotta 0.6546
Portand 0.6345
Myrtle Beach 0.6028
Tijuana 0.5921
Kansas City 0.5764
Norfolk 0.5091
Dallas 0.4971
London 0.4767
So there you have it. The community rankings are the exact same as my rankings with the exception of the Pythons being in 2nd and not dead last. I found it funny reading the community power rankings to see even the Pythons think they suck. Portland, ya’ll are good. Ya’ll are really good and you have a chance to make some noise. I’d say Minnesota is still a clear favorite as the #1 but Portland does make a case for tier 1 and at least high tier 2 status. The Bucs, Luchadores and Coyotes are all tier 2-3 talent. Finally, the SeaWolves, Royals and Birddogs all are 4th tier talent. It’s worth nothing that Dallas does have a significantly higher score than the Royals.
Please leave feedback below! Cheers
1484 words
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