I found a great debate article on ESPN dealing with putting together the best team of all time.

Early this morning, a debate broke out among the SportsCenter staff in the show pod. The question was, “If you had to choose 5 players to start on an all-time NBA team, who would it be?” After about 15 minutes, we decided to do a draft. Four teams, and each picked a starting 5. The Team names are based on the order of the draft (Team A had the 1st pick, but in this “snake-style draft”, team A did not select again until pick number 8). For the record, Michel Jordan did NOT go with the first pick – here’s how the 1st round went: 1) Chamberlain, 2) Jordan, 3) Magic, 4) LeBron.

Well, this is right up my alley, so I had to put my own 2 cents into the argument. I went with each player’s highest APP+ value and then found which team had the highest average. Of course, I’d love to do a 10k sim (simulate the games 10,000 times), but I don’t have a system to do that … yet! Here’s the breakdown:

Chamberlain and Duncan would create perhaps the most fearsome offensive-defensive low post punch, but Oscar Robertson as a small forward? I wonder how effective he would be off the ball. Team A would lose size with Jerry West at the shooting guard position but Chamberlain’s production seems to more than make up for everyone else’s lapses.

Obviously this team won’t be lacking in terms of scoring with Barkley, Baylor, Maravich and especially Jordan. Also, they’re anchored by the winningest baller in the history of the sport. However, I’m concerned about ESPN’s selection of Pistol Pete. Sure, he was an electrifying player in both the NBA and college as well as a deeply interesting man, but he’s one of the league’s most famously overrated guys. As a result, Team B is dragged down a bit in terms of average APP+.

This is my favorite team. How can you beat these five in their prime? Still, I’m not so sure how Hakeem at the four would work. I would probably switch Kareem with him as Kareem was more of the finesse player while Hakeem was the better defender. Julius would be a big shooting guard, but at this early a stage in his career, he’s probably quick enough to keep up with even Jordan. With Hakeem and Kareem in the low post, Julius slashing, Bird shotting and Magic dishing, this is a solid, solid team.

Though comprised of unquestionably great players, I have the msot reservations about this team playing together. Look at who is playing each position … and then realize there’s only one ball to share between them!

Anyway, the APP+ has spoken and predicts Team A to be the winner. However, I’d still love to 10k sim this because I get the feeling Team C might edge everyone out.

Sometime ago I came across WhatIfSports, a truly awesome site that allows people to play fantasy sports using players throughout the history of the game. Being a rabid NBA fan, I immediately jumped into their pro basketball section (though I assume their baseball, football and college games are just as detailed and entertaining) to see how they were comparing stats of players from different eras of the sport. You know, kinda like what I’ve been obsessively doing here at NBA Sim for years!

WhatIfSport’s idea is a lot of fun. You’re given $42 million to build a team and can choose any player from any year to fill your roster. Thus, the price goes up for both the better player and better year you want. So, for example, absolutely dominant 1989 Michael Jordan is valued at $10,964,331 while his much older (though still great) 1998 counterpart is worth $8,555,181. They even do a fantastic job of estimating stats from seasons before 1974 (before steals, blocks, and many other stats weren’t officially recorded) by comparing similar players and playstyles. I really could go on and on about the great things they have set up, but you can read it all here at their site.

Unfortunatley, as great a job as WhatIfSports does, I do find a huge problem with one of their decisions in handling player comparisons. That is, they use non-flattened stats: for example, they just compare straight-up points per game, regardless of pace. So, Wilt Chamberlain’s absurd 50.4 PPG from 1962 stands when picking players and simulating games. This is exactly the same trap I fell into during my first year simulating the NBA Sim Tournament.

Since the sport has become more and more sophisticated, the pace of the game has decreased. Players have become more efficient and better shooters so there are less (and better) shots being taken which bring down the opportunities for everything: less rebounds, less blocks, less assists, etc. So comparing flat stats. This type of comparison devalues modern era players – penalyzing them simply for the progress of the sport they play in. Changes within the game should be considered if comparing players from different eras of the sport is the goal.

Alright, I’m off of my soap box. Anyone who’s even slightly interested in basketball statistics or the history of the NBA should definitely check out WhatIfSports and try their free league. Here’s how my self-selected team, The Gray Rangers, did in mine:

I probably could’ve made a better team … but I went with 2 of my top guys of all time (Abdul-Jabbar, Nowitzki) and just sort of built around them. Not well, I might add, as I ended up 4-6, good for 4th out of 6 players. Ah, well.

Earlier in the week my girlfriend made the claim that “no one really likes” baseball and that it is lame. Now, of the three most popular American sports, I would agree that baseball is my least favorite, but is it true that no one else likes it? Of course not … but it got my stats-obsessed juices flowing.

In fact, after a little research I discovered that baseball has the highest total attendance between it, basketball and football by a factor of four!

Now, these attendance figures are based upon countless, different variables – variables that are completely different between the three sports. First, I isolated what I thought were the most important factors, and ones that could easily be qunatifiable: number of stadiums, number of games in a season, total seats in all stadiums, and ticket price. Here are the figures from the 2007 NFL, 2007 MLB and 2007 NBA seasons:

In order to fairly compare the attendance figures I next had to make sure they were all translated into the same language. Essentially, what I was trying to do with my math was answer the question “with the same amount of games, the same amount of teams, the same size of stadiums, and for the same price, which of the three sports would be more popular?” Then, for each variable I decided whether a lower or higher number was more impressive and added that to the end of the row (+ = higher number more impressive, – = lower number more impressive). I decided to translate all of the attendance figures into “football numbers” since it is undoubtedly the most popular American sport and it produced the smallest figures for the next step.

Formula: (Sport X’s Figure / Football’s Figure)
Example: (Baseball Teams / Football Teams) = (30/32) = 0.938

It didn’t matter, ultimately, which sport I chose to use for the base. Sure, this would affect the figures calculated above, but the end results would still be the same (I checked to make sure). Now, I multiplied the original attendance figures by these newly formulated coefficients. Thus, here are the attendance figures of Football, Baseball and Basketball if all three had the same amount of teams, games, seats, and prices that Football has in a regular season (obviously, Football’s attendance remains the same):

And, finally, to answer my question, I calculated the Popularity Strength. This was just basically comparing all of the attendance figures to the highest one.

Now, of course, I realize this conclusion is only based on attendance. Many fans of these sports participate by watching them on tv. I considered getting the nielsen ratings for each, but I found that too cumbersome and just plain difficult to track down. With that said, however, for all you baseball fans out there, I hate to say it but: my girlfriend may be right.

Total Stadium Seats thanks to Wikipedia
Ticket prices thanks to Team Marketing Report

So it’s Heritage Week in the NBA. In the obligatory, preceding press release, Heritage Week is touted as “an opportunity to recognize the achievements of so many players, coaches and teams who have helped shape today’s game, while also providing fans an opportunity to celebrate previous eras of basketball.” While this may very well be the case, it’s also a fantastic public relations idea to draw in an older fanbase that doesn’t see a lot of what they enjoyed in today’s game.

The heart of this disconnect is the age old debate of purists vs progressives in the world of sports. Will the game never be the same as the good old days? Or will the game never be as good as it could be? It’s a strange conversation because the assumption for both arguments begin with saying there’s something wrong with the sport. Sure, basketball isn’t perfect, but it could be worse. A lot worse.

I’m not here to discuss this issue though (for the record, as much as I love the history of the NBA, I guess I’d put myself directly in the middle with a slight progressive lean as I love small tweaks to make the sport just a little better). Nay! I’m here to show some much-deserved love to the mainstream thinkers at NBA.com. For once. Along with the Heritage Week merchandising tie ins, they actually have some great, new resources and cool ideas.

First of all, kudos for the Historical Player Search. Sure, it’s still in beta version, and it only semi-duplicates existing online databases such as databaseBasketball and Basketball-Reference.com (both sites provide much more advanced analytical statistics) but it was something NBA.com should have had years ago. NBA.com also projected some of their present day features into the past: like Race to the MVP for the 1962 season, Team Power Rankings for the 1970 season, and Rookie Rankings for the 1985 season.

Anyway, this basketball historian/statistician/fan is happy about this unveiling on the NBA’s official site. Now people can get acquainted with some of the older players since NBA Sim incorporates many pre-Magic/Bird era basketball legends.

I completed my first of two Yahoo! Fantasy Basketball live drafts today and … I have mixed feelings for the result. First of all, I was in 11th place (out of 12) so I didn’t get any of the top 5 studs. Still, I think I got a steal with Wade. The league I’m playing in is based on the TENDEX formula, and Wade led the league in that formula per game. Still, he and Yao’s injury concerns are a bit daunting. We’ll see how my first custom fantasy scoring league outing goes!

The values below reflect each player’s modified TENDEX value – both total and per game. TENDEX is a formula based on weighted stats, but some seasons rebounds come pretty cheaply (like in the 1960′s) and in some leagues it’s harder to score (late 1990′s). So, to help comparisons from era to era, I’ve devised the modified TENDEX which balances all stats based on year (it’s a complicated process that I’ll go into more depth in a later post). It’s a little more accurate description of a player than the regular TENDEX.

UPDATE: Attack of the injury bug! Wade was out 31 games, Yao sat for 27, and Caron was out for 24! Ford was hurt for 31 games and Devin Harris was out for 18. Absolutely devastating. I ended up 7 of 12. (10/27/08)

The Wages of Win Journal: pretty much what I want to become within a year’s time. This blog is written by three professors of economics who use their super business-science powers to analyze and investigate interesting ideas about the NBA (and sometimes other sports). Basically, they have established a holy grail formula (a formula that boils down everything a player does on the court into one number for easy comparing to other players) and run with it. I love this approach, and it’s exactly what I want to do myself one day, but I don’t fully support their holy grail. My biggest gripe with it is that it ignores historical differences (rule changes, strategy patterns, pace, etc.) but it’s an excellent start and never a dull read.

I’m working on researching my own holy grail formula … and it seems that one of the most important aspects of this process is to come up with a name. The Wages of Win uses “wins produced.” Just doesn’t have enough pizzazz for me. We’ll see what I can come up with for my own formula.

Also … I just accidentally fucked up and deleted my information for the Suns-Mavs series I just simmed. I could kick myself, but at least I have all the player data to re-sim it. Still, this will cost me at least 2 days!