- Alfred Pennyworth (if he was in the NSFL)
With my last article (yesterday) I didn't realize that someone had already written an article about it. Even though I did add some more stuff that wasnt in his thread, I just want to say sorry if I repeat anything that has already been said or discussed. I try to check all of the threads to see if my thoughts are new, but sometimes I miss a couple.
Anyways, today we will talk about Regression. We have 5-ish seasons remaining before we need to get it right, so might as well start early. Some of you have posted about regression before but being able to look at it compared to how different people earn TPE, it is really surprising. I started with everyone at 100 TPE since that seemed about the average for rookies in the s2 draft. That value might prove to be a little high as we move along though the seasons, but it is a starting point. When doing comparisons between players, that fixed amount is not really significant, so whether that number is 50 or 200, as long as it was the same between two players. Now I got to thinking that those who are committed throughout all of their seasons, they are probably committed early on, so that is why I game those who were more committed an extra boost prior to the start of their first season. There were obviously players who have more TPE than me as rookies, but the season has not started yet, and I am already at 144 TPE, probably going to be around 150 TPE by the time the season starts. This is just to give you evidence that starting at 100 TPE is not a far fetched Idea, and even though there may be quite a few people not at that level currently, its ok. they just have to make small adjustments to view this chart, but it should not have a big impact in the long run.
So for these tables I will post all of them together first just so you can get a good look at what they are like next to each other. I like looking at it this way to show the differences between the regression systems. by color coding it, we can see where the 'primes' are of each players career. the colors formatted for all 250 cells (25 years x 10 TPE/yr rates). if there were 250 players in the league and evenly distributed on how active they are by this chart, the green would be the superstars/probowlers. the red would be bench players. seeing this helps to compare how each system would reflect real life athletes, however, the only backfire would be how rookies would not be a great player right away in the league where as in the NFL some rookies have immediate impacts, but that is just my observations. Anyways, here are the tables.
Ok so now that we have seen them all, lets Break them down. I put 25 as the max amount of season because people need to stop at that point. no one is gonna sign a 47 year old man, even as a kicker. Also, I will use 22 as the base age for rookies. sorry if you have other opinions on that. Actually, not sorry. THIS IS MY ARTICLE! sit down and read boy.
Current System
The current system is really simplistic. not saying simplistic is bad, but I feel that this system is bad for other reasons. If you look closely, from S15-16 there is a drop, then the next year it rises, then drops, then rises, then drops, and after S20, it continues to rise. This does not reflect real life very well because not many people continue to improve after they turn 42. this brings me to my next table.
Linear System
This system is very similar to the current system, but it doesn't have pauses and continues to increase the percentage of used up TPE. This reflects the end of the career well, but it has the players primes maybe a little early for my taste. Maybe not, I dont know.
Ramp System
The ramp system modifies the Linear system by shifting the prime down about 1.5-2 years. I believe that this reflects real life a lot better than the linear system. It does have a sharp drop off that will help to have players retire before the proposed 25 year mark.
Step System
The step system is the other half of the current system that I have not discussed yet. even though I did not like it in the way it was used in the current system, it does not mean that it has no place in regression systems. Using NFL data and following patterns of where regression happens, I set different years as a place for a big hit. a side affect of these sudden drops may be that players retire early, which would follow some NFL patterns. if not, players are able to climb out of that drop, but there are more regression obstacles that will get in the way down teh line and only the best players will not feel the pain as much.
Gradual Step System
The Gradual step system helps to combat the problems of the step system and allows for a more 'gradual' drop, making the steps not as steep, but still forcing players to continue to grow or they will not succeed. It still follows the data from the NFL that I used in the steps system, but it makes the table flow a little bit better.
Wall System
Ok maybe wall wall is not the best word of choice here, but my idea behind this was using that same data, but shifting it down a year or 2 and having steeper drops. It allows for a better early game, with a steady mid game, and big fall for the late game. even though it seems to be broken up into those three parts, there really are 6 walls that help to balance out the years of high growth as well as replicate the last few years of those veteran stragglers.
---
now that you have seen all six regression systems, please ask any questions regarding this data or help in discussion of this data. I want the best for this league, and if you feel that the current system is the best regression system, I want to hear it, but I believe that the best system to use would be the ramp system.
GRADED
With my last article (yesterday) I didn't realize that someone had already written an article about it. Even though I did add some more stuff that wasnt in his thread, I just want to say sorry if I repeat anything that has already been said or discussed. I try to check all of the threads to see if my thoughts are new, but sometimes I miss a couple.
Anyways, today we will talk about Regression. We have 5-ish seasons remaining before we need to get it right, so might as well start early. Some of you have posted about regression before but being able to look at it compared to how different people earn TPE, it is really surprising. I started with everyone at 100 TPE since that seemed about the average for rookies in the s2 draft. That value might prove to be a little high as we move along though the seasons, but it is a starting point. When doing comparisons between players, that fixed amount is not really significant, so whether that number is 50 or 200, as long as it was the same between two players. Now I got to thinking that those who are committed throughout all of their seasons, they are probably committed early on, so that is why I game those who were more committed an extra boost prior to the start of their first season. There were obviously players who have more TPE than me as rookies, but the season has not started yet, and I am already at 144 TPE, probably going to be around 150 TPE by the time the season starts. This is just to give you evidence that starting at 100 TPE is not a far fetched Idea, and even though there may be quite a few people not at that level currently, its ok. they just have to make small adjustments to view this chart, but it should not have a big impact in the long run.
So for these tables I will post all of them together first just so you can get a good look at what they are like next to each other. I like looking at it this way to show the differences between the regression systems. by color coding it, we can see where the 'primes' are of each players career. the colors formatted for all 250 cells (25 years x 10 TPE/yr rates). if there were 250 players in the league and evenly distributed on how active they are by this chart, the green would be the superstars/probowlers. the red would be bench players. seeing this helps to compare how each system would reflect real life athletes, however, the only backfire would be how rookies would not be a great player right away in the league where as in the NFL some rookies have immediate impacts, but that is just my observations. Anyways, here are the tables.
Ok so now that we have seen them all, lets Break them down. I put 25 as the max amount of season because people need to stop at that point. no one is gonna sign a 47 year old man, even as a kicker. Also, I will use 22 as the base age for rookies. sorry if you have other opinions on that. Actually, not sorry. THIS IS MY ARTICLE! sit down and read boy.
Current System
The current system is really simplistic. not saying simplistic is bad, but I feel that this system is bad for other reasons. If you look closely, from S15-16 there is a drop, then the next year it rises, then drops, then rises, then drops, and after S20, it continues to rise. This does not reflect real life very well because not many people continue to improve after they turn 42. this brings me to my next table.
Linear System
This system is very similar to the current system, but it doesn't have pauses and continues to increase the percentage of used up TPE. This reflects the end of the career well, but it has the players primes maybe a little early for my taste. Maybe not, I dont know.
Ramp System
The ramp system modifies the Linear system by shifting the prime down about 1.5-2 years. I believe that this reflects real life a lot better than the linear system. It does have a sharp drop off that will help to have players retire before the proposed 25 year mark.
Step System
The step system is the other half of the current system that I have not discussed yet. even though I did not like it in the way it was used in the current system, it does not mean that it has no place in regression systems. Using NFL data and following patterns of where regression happens, I set different years as a place for a big hit. a side affect of these sudden drops may be that players retire early, which would follow some NFL patterns. if not, players are able to climb out of that drop, but there are more regression obstacles that will get in the way down teh line and only the best players will not feel the pain as much.
Gradual Step System
The Gradual step system helps to combat the problems of the step system and allows for a more 'gradual' drop, making the steps not as steep, but still forcing players to continue to grow or they will not succeed. It still follows the data from the NFL that I used in the steps system, but it makes the table flow a little bit better.
Wall System
Ok maybe wall wall is not the best word of choice here, but my idea behind this was using that same data, but shifting it down a year or 2 and having steeper drops. It allows for a better early game, with a steady mid game, and big fall for the late game. even though it seems to be broken up into those three parts, there really are 6 walls that help to balance out the years of high growth as well as replicate the last few years of those veteran stragglers.
---
now that you have seen all six regression systems, please ask any questions regarding this data or help in discussion of this data. I want the best for this league, and if you feel that the current system is the best regression system, I want to hear it, but I believe that the best system to use would be the ramp system.
GRADED