Ben Taylor on the Top-8 Greatest Players of All-Time
Dunc'd On Basketball NBA Podcast
Nate Duncan
4.5 • 2.9K Ratings
🗓️ 3 October 2018
⏱️ 69 minutes
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| 0:00.0 | All right, this is long overdue. In fact, the title of the email that I sent to this guest asking him to come on the show somewhat sheepishly was long overdue follow-up pod because lots of people have been asking for this at the time when he was doing his greatest fall time rankings. He only had done up until the top eight and we're gonna have him on again and then the playoffs started and it was a truncated off season for me with the wedding. |
| 0:28.1 | But he's been kind enough to wait until now. Ben Taylor. How are you doing? Good to be back. I'm worried I set the bar too high in the first go around. So yeah, a lot to live up to today, I think. |
| 0:39.2 | So you thought your pod was that good, huh? |
| 0:41.0 | No, I didn't. It was just the feedback. I was like, oh, man, what have I done? |
| 0:45.8 | Yeah, well, I mean, I think what you did was leaving them wanting more by not having done those top eight. So let me see here. Where do we want to start? |
| 0:57.3 | I think I want to before we get into those top eight and those who've read his series on backpicks.com know it already, but we will get to that to be sure. |
| 1:08.5 | But I wanted to start again. We talked about this a little bit the first time, but it might be good since it's been about six months now to just talk about what your methodology was. |
| 1:18.3 | And if you want to really get into it, we talked about it more the first time, but it, you know, he does a lot of plus minus work. |
| 1:25.7 | And so if that really had been available before, especially for the guys who were the pre-datable era as he calls it 1997 is the first year. |
| 1:34.6 | We have plus minus data, but then goes back and is able to estimate that from earlier on. |
| 1:40.2 | But what an accurate summary of kind of your criteria, maybe rather than your method, be if you started this guy's career the same year he came to the league, |
| 1:50.1 | but he had average teammates around him for his career. |
| 1:53.6 | How many championships would you expect him to win? And then basically you're ranking him on that criteria. |
| 1:58.5 | Is that a fair summary or is that too simple? |
| 2:02.1 | No, almost. I think the only thing to adjust there is that it's not just average teammates. |
| 2:08.9 | So, you know, interestingly, when I started the process years ago of like thinking about it from this perspective, the first calculations I did were with average teammates. |
| 2:17.6 | And at a certain point, I got around when I sort of developed the full like corp that is championships over replacement player. |
| 2:24.7 | I said, okay, you have to look at how guys affect different teams, right? |
| 2:28.0 | Because players aren't just being slotted on 500 clubs and then making them contenders or whatnot. |
| 2:32.9 | So you look at the whole distribution of teams and, you know, some guys that means they're going to be on really good teams. |
| 2:38.3 | Some guys are going to be on poor teams. |
| 2:39.8 | And from that, essentially, I say, what's the championship odds on a random team? |
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