4year Peaks Study using nbarapm.com
Posted: Sun Aug 10, 2025 8:59 pm
Hey y'all,
So, earlier in the summer I shared a project, Doc's RAPM VORP Career Leaderboards, which focused on longevity.
Recently I've made something of a counterpart spreadsheet based on players best 4-year RAPM numbers on nbarapm.com, which you can find here:
Doc's nbaprapm 4year Peaks Study
In this first post I'm going to mostly focus on pointing out some things to keep in mind when going through the day, but I will list those topping the leaderboard in spoilers for the time being. (Not trying to make you click into the spreadsheet, but also don't want the results to drive the first impression.)
So, things to keep in mind:
1. My prior study used Englemann's Career RAPM, rather than nbarapm.com's Career RAPM, yet here I"m using nbarapm.com. Why? Because Englemann's Career RAPM was easier to access, but nbarapm.com is the place that had the shorter increments. Don't take either source as a holy grail, and be careful about "crediting" one guy over another as "more impactful" based on a lead that may not be bigger than the potential differences between quality models.
2. RAPM on its own doesn't factor in minutes played, so keep that in mind when you see a lower minute guy doing well by this study, and you might want to click over to the VORP to have a sense for what the Peaks data does and does not add up to.
3. Why the 4 year study? Honestly, that's what it defaulted me to on the site. I'd be curious to see other studies done based on 2, 3, or 5 years. I don't believe those other durations are "better" than the 4-year generally, but where we see differences in how a player stacks up between these studies, it definitely tells a story.
4. I will say in general that when we go beyond a 1-year RAPM model, I like the idea specifically of going up to 3-year, so I'm generally less interested in 2-year models...but using the criteria I used here, doing the 2-year approach would mean we'd get Jordan in the study.
5. While Jordan technically has 4-year RAPM numbers here, it's only based on 2 years of play, and generally, if you allow players who only played a fraction of the total span you're regressing over, that's a recipe for noisy outliers.
6. What got me on this kick was specifically the fact that they had regressions for their 6Factors (think Dean Oliver's 4 factors, which are actually 8 when you factor in defense, but nbarapm is combining eFG & FTr into one TS factor.
7. The overall RAPM data goes back to '96-97, and so the earliest 4 year epoch is '96-97 to '99-00.
8. The 6Factor data only goes back to '99-00 for whatever reason, and so the earliest 4 year epoch is '99-00 to '02-03.
9. The 6Factor data only goes through '23-24 to this point, so if you see a player that peaked through '24-25, expect that an updated 6Factor study would probably help the player in those metrics.
10. Included in the spreadsheet are over 400 players, which includes all all-stars back to the 1984 draft regardless of whether they qualified by the full-4-year requirements, and beyond that every other player who played relatively long careers that I could think of and who had a Peak 4-year RAPM at least as big as +1.0
11. The Raw data was a manual process
, and so expect if you find errors, please let me know - or by all means, automate the process.
12. Always keep in mind that different RAPM studies might end up with different scaling, which is why I used so to have a spreadsheet that normalized the data across studies to give us more of an apples-to-apples set of data.
I have not made a normalization adjustment here, and that might prove to be a problem. However, the fact that these are 4-year studies should make scaling differences smaller, and the fact that all the studies came from the same place also helps. Just having eyeballed the data, I didn't see any glaring red flags of data being on drastically different scales, but if folks see something, they should say something.
In the spreadsheet, I think the Ranks tab is the one people will probably be most interested in first, and in spoilers here, I'll put the player(s) who lead each category:
So, earlier in the summer I shared a project, Doc's RAPM VORP Career Leaderboards, which focused on longevity.
Recently I've made something of a counterpart spreadsheet based on players best 4-year RAPM numbers on nbarapm.com, which you can find here:
Doc's nbaprapm 4year Peaks Study
In this first post I'm going to mostly focus on pointing out some things to keep in mind when going through the day, but I will list those topping the leaderboard in spoilers for the time being. (Not trying to make you click into the spreadsheet, but also don't want the results to drive the first impression.)
So, things to keep in mind:
1. My prior study used Englemann's Career RAPM, rather than nbarapm.com's Career RAPM, yet here I"m using nbarapm.com. Why? Because Englemann's Career RAPM was easier to access, but nbarapm.com is the place that had the shorter increments. Don't take either source as a holy grail, and be careful about "crediting" one guy over another as "more impactful" based on a lead that may not be bigger than the potential differences between quality models.
2. RAPM on its own doesn't factor in minutes played, so keep that in mind when you see a lower minute guy doing well by this study, and you might want to click over to the VORP to have a sense for what the Peaks data does and does not add up to.
3. Why the 4 year study? Honestly, that's what it defaulted me to on the site. I'd be curious to see other studies done based on 2, 3, or 5 years. I don't believe those other durations are "better" than the 4-year generally, but where we see differences in how a player stacks up between these studies, it definitely tells a story.
4. I will say in general that when we go beyond a 1-year RAPM model, I like the idea specifically of going up to 3-year, so I'm generally less interested in 2-year models...but using the criteria I used here, doing the 2-year approach would mean we'd get Jordan in the study.
5. While Jordan technically has 4-year RAPM numbers here, it's only based on 2 years of play, and generally, if you allow players who only played a fraction of the total span you're regressing over, that's a recipe for noisy outliers.
6. What got me on this kick was specifically the fact that they had regressions for their 6Factors (think Dean Oliver's 4 factors, which are actually 8 when you factor in defense, but nbarapm is combining eFG & FTr into one TS factor.
7. The overall RAPM data goes back to '96-97, and so the earliest 4 year epoch is '96-97 to '99-00.
8. The 6Factor data only goes back to '99-00 for whatever reason, and so the earliest 4 year epoch is '99-00 to '02-03.
9. The 6Factor data only goes through '23-24 to this point, so if you see a player that peaked through '24-25, expect that an updated 6Factor study would probably help the player in those metrics.
10. Included in the spreadsheet are over 400 players, which includes all all-stars back to the 1984 draft regardless of whether they qualified by the full-4-year requirements, and beyond that every other player who played relatively long careers that I could think of and who had a Peak 4-year RAPM at least as big as +1.0
11. The Raw data was a manual process

12. Always keep in mind that different RAPM studies might end up with different scaling, which is why I used so to have a spreadsheet that normalized the data across studies to give us more of an apples-to-apples set of data.
I have not made a normalization adjustment here, and that might prove to be a problem. However, the fact that these are 4-year studies should make scaling differences smaller, and the fact that all the studies came from the same place also helps. Just having eyeballed the data, I didn't see any glaring red flags of data being on drastically different scales, but if folks see something, they should say something.
In the spreadsheet, I think the Ranks tab is the one people will probably be most interested in first, and in spoilers here, I'll put the player(s) who lead each category:
Spoiler: