Official "John Hollinger is a Cunt" Thread

[Koolaid]

It's smart for every team to use advanced stats...

if the majority of the league is doing it and you're not you're at a disadvantage, regardless of how much stock you put in the data.

It will be interesting to see how far down the rabbit hole the Grizz will go now they have someone in the Advanced Stats department...

eh, i don't know that it wouldn't just be a waste of money for LA, NY and Miami.
Do you really need advanced numbers to tell you that signing LeBron, Wade and Bosh is a good idea?
If you don't give a fuck flying fuck about luxury tax does it really matter if the 9th man is just as productive for 2 million as someone who coulda been got with 1 million?

I mean, don't get me wrong, i don't think it'd hurt anybody. Yet for a team like the Grizzlies it definitely makes more sense to focus even more on that. Kinda like the Oakland Athletics (if you haven't seen Moneyball, I recommend it).

[Pharaoh]

Of course I've seen Moneyball

The point I was trying to make is that regardless of budget/location getting into advanced stats can't hurt. You want to be on a level playing field with everyone else and if the majority of teams have a reasonable advanced stats department you should too. At worse you are keeping up with the Jones'... at best you can un-earth some interesting data

The numbers IMO don't mean much - it's how you look at them. You have 5 guys on the floor at all times. How they mesh and gel and compliment each other can't really be shown by the numbers until after the fact. I believe 82games.com has a section where you can see the combined plus/minus for line-ups... but all that data is "discovered" after they've played together.

IF someone could take existing data from individual players and work out how they could work together in a certain offensive/defensive system BEFORE they've played a minute together then they'd have a huge advantage over other teams. IF that was possible to work out a team with that knowledge would be able to focus on players that DO fit, as opposed to signing/acquiring players they HOPE will fit.

The difference between KNOWING and HOPING is huge, especially when the vast majority of the league is spending between $60-70 million... if you're one of the teams that KNOWS who fits with who then ALL your budget is being spent on players that fit while your opposition are spending money on some players they HOPE will fit.

The difference might be $10 million in player salaries... but you're spending that on guys that fit while others are spending it on guys who don't! That could be huge

The dude Jordan hired for Charlotte (Cho?) is/was attemtping to come up with this kind of thing - a "predictor" if you will... a program that can take existing data and piece it together with other "known" data and come up with a team that works well together.

It all sounds very interesting - time will tell if it's even possible or if it's just a pipe dream of stat gurus that hope that their work can replace all the old fashioned basketball knowledge.

On Moneyball: The GM had been a player! The guy was told from a young age how great he was going to be... but (I thought) he always had some doubts... and then when he moved into management he always had that "splinter in his mind" that the scouts really didn't know shit.. they just thought they knew, thought they had a clue...

Stats don't lie. A guy shoots what he shoots, rebounds what he rebounds, blocks what he blocks. But numbers aren't everything either. Even on the worst team some dude is rebounding the ball, scoring, stealing, assisting etc.

This new business of having cameras above the court that track everything is amazing IMO. What they do with the data it produces will tell the tale though

[Uncle Mxy]

http://www.3sob.com/december-2012/da...ollinger/5515/

3) We’ll try to be delicate here but why is his system inferior in your opinion to your own?

These two questions are related — and I will try and be diplomatic.

When I started looking doing economic research with NBA statistics I needed a measure of player performance that connected what a player did on the court to team wins. Although measures like PER — and NBA Efficiency — are popular, these measures are not highly correlated with team wins (as I have shown in published research).

So, I set out build a model connecting a player’s box score statistics to team wins. The result of this effort is Wins Produced, a measure that translates all the numbers we see in the box score into each player’s production of wins.

The big difference between Wins Produced and PER is that the former is based on a model connecting each factor in the box score to team wins. In other words, the value of factors like offensive rebounds, steals, or turnovers is based on a statistical model connecting each of these variables to how many wins we observe.

When Hollinger describes how PER was constructed he doesn’t really argue that the weights he assigned reflects how that particular factor impacts outcomes (and he certainly doesn’t provide evidence that his weights reflect actual outcomes). What he does is choose weights that seem to make sense to him. And what seems to make sense to him leads to a measure that confirms what people tend to think about NBA players.

As a result, we see two clear problems with PER.
• A player who shoots better than 30% from two point range (and even less from three point range) can increase his PER by simply taking more shots. So PER rewards inefficient shooting.
• Consequently – because inefficient shooting does not translate into wins — measures like PER do a very poor job of explaining team wins.

As a result, it doesn’t appear that PER is a very good measure of a player’s actual contribution to outcomes.

PER is highly correlated with Game Score (Hollinger’s simple box score metric) and NBA Efficiency. Each of these measures overvalues inefficient scoring and does a poor job of explaining wins. But all three do a very good job of explaining a free agent’s salary (something also noted in published research).

This indicates that PER is a statistical measure that captures perceptions of value in the NBA. For example, PER tells us that players like Allen Iverson and Carmelo Anthony are really very good. And therefore both should get paid large sums of money (and Hollinger once thought that these two combined on the Nuggets would lead to a title contender). That's why John Hollinger is a cunt.