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In the NBA you're seeded strictly by record there is no committee making judgement calls in the NBA. Apples to Oranges.

(03-19-2015 05:01 PM)ODUChm Wrote:  No, you have the regular season which consist of 30 some of games to justify where a team is seeded or whether or not their in the tourney.

If Cleveland (lets say theyll be the second seed) makes a first round exit in may, does that mean they werent justified in being in the second seed in the East? Of course not, because their seed was based off of the 82 game regular season.

There's a huge difference though. Cleveland compiled whatever that record is by playing the same teams Atlanta played, the same teams Chicago played, etc.

It's easier to compare teams when they play the same basic schedule.

(03-19-2015 07:25 PM)djnva Wrote:  

(03-19-2015 05:01 PM)ODUChm Wrote:  No, you have the regular season which consist of 30 some of games to justify where a team is seeded or whether or not their in the tourney.

If Cleveland (lets say theyll be the second seed) makes a first round exit in may, does that mean they werent justified in being in the second seed in the East? Of course not, because their seed was based off of the 82 game regular season.

There's a huge difference though. Cleveland compiled whatever that record is by playing the same teams Atlanta played, the same teams Chicago played, etc.

It's easier to compare teams when they play the same basic schedule.

No they didnt, there is no balanced schedule in the NBA, thus no two teams have the same schedule.

But lets just say they do, then your point becomes valid: its easier to evaluate NBA teams based on their similar schedules, then it is with college teams with dissimilar schedules. Heck even with their unbalanced schedules its easier to compare 30 teams over the course of an 82 game season, then it is do the same with 351 teams over ~30 games.

Now what would be an empirical method we could use to evaluate college team? hmm. Obviously we need to take into account that some schedules are much easier then others (I think we would agree that 25-5 isnt neccearily better than 20-10), and we would also want to know how a team won and lost its games against their opponents (Because team A winning by 20 against team B is much better than team C winning by 1 against team B, all other things equal). What could we use that might help us take factors like those into account?

Why do we need an empirical method. Can't we just have experts evaluate teams by watching them. I watch a lot of basketball, and among the teams I watch, I can tell who is better.

You can't use the NBA as a comparison. The teams don't play the same schedule, obviously, but it's not like the Cavs can avoid going on the road to play the Grizzlies. The SOS differences in the college game are inherent due to the power leagues controlling the scheduling. Why should the good mid-majors be punished for none of the big teams (particularly those with whom they are going to be compared with for at-large purposes) not wanting to play them?

NBA also has a lot more moving parts with personnel changes within the season, a lot more games and thus injuries, and they are professionals with no other job so they get a lot more practice and film time where something can finally click. You could have an 8 seed that played much of the season without key players due to injury that come back and click right in time for the playoffs.

(03-19-2015 08:17 PM)ODUChm Wrote:  There's a
No they didnt, there is no balanced schedule in the NBA, thus no two teams have the same schedule.

Sigh.

I didn't say the same exact schedule. I said the same basic schedule--as in the same number of home and road games, no "ducking" teams that could beat you.

If you don't think that the schedules of the Heat and Bulls have a lot more in common than the schedules of UCLA and ODU I don't know what to tell you.

(03-19-2015 09:35 PM)Monarchblue Wrote:  Why do we need an empirical method. Can't we just have experts evaluate teams by watching them. I watch a lot of basketball, and among the teams I watch, I can tell who is better.

Because experts and fans a like have personal bias, and will see what they want to see. Thus analytics helps us remove our bias. Theres a reason why physical evidence is of a higher value than eye witness accounts. If its just about experts being able to evaluate teams by watching them, then why can't you accept the committee, who watched way more basketball than you did, was able to tell who was better?

Watch all the basketball you want, and use analytics to help process what you see as some of the leading coaches and teams in this country do:
http://bleacherreport.com/articles/15568...basketball

I also found it funny how people used Baylors and ISU loses as vindication against kenpom.

Heres kenpoms predictions via simulation:

http://bleacherreport.com/articles/15568...basketball

Looking at ISU chances they had a 87% chance of advancing to the round of 32.
The person who apparently didnt pay attention in stat class will look at that and say "Hah! See they had an 87% of winning and they lost, shows how much kenpom knows."

The person who paid attention in stat class will look at that as if there is a bag with a 100 balls with 87 being red, and 13 being green. They stick there hand and pull out a ball and its not red. What happened? Well what happened is despite having an 87 percent chance of pulling out a red ball, the chances of pulling out any one ball is the same as the other 99 balls, and it just happened the specific ball he pulled out was one of the 13 green ones. And thats how you can view the infinite amount of outcomes to a basketball games, they all have an equal chance of happening, it just happens that 87 percent of those outcomes had ISU winning.

Its even lower for Baylor: 77 balls
Texas even lower: 52 balls

(03-20-2015 02:06 PM)ODUChm Wrote:  

(03-19-2015 09:35 PM)Monarchblue Wrote:  Why do we need an empirical method. Can't we just have experts evaluate teams by watching them. I watch a lot of basketball, and among the teams I watch, I can tell who is better.

Because experts and fans a like have personal bias

What you don't understand is that the people who create the analytics have personal biases as well, and theirs are hidden in some string of decimals under the guise of scientific analysis. That is just not the case. These formulae turn out the way the person creating them wants them to turn out. Whether that is fair and objective, or in a manner that drives clicks, who knows. But nothing in the business of big time college sports is "empirical".