RealGM

A lot of the basketball blogs seem to think that the world is lacking "proprietary statistical algorithms" that express basically the same thing that winscores (and efficiency, and holinger rating, etc) do. Maybe it enhances our percieved credibility if we're constantly pushing for the adaptation of our own formula.

So I think it's time I start annoyingly referring to points - turnovers squared per minute in each of my posts. For your information, the Bucks starters rank as follows:

Redd: .437 PMTO2MIN
Williams: .263 PMTO2MIN
Yi: .272 PMTO2MIN
Mason: .271 PMTO2MIN
Bogut: .269 PMTO2MIN

Turnovers + Fumbled Passes + Bad or Blown Shots

TO+FP+BBS = WTF

Redd 6.91 WTFs Per Game

Mo 5.76 WTFs Per Game

Bogut 6.21 WTFs Per Game

Yi 4.36 WTFs Per Game

CV 3.41 WTFs Per Game

Gadz 8.9 WTFs Per Game

We gotta cut down on our WTFs per game next season.

What about WTFs as a percentage of total touches? Yi is over 50%.

adamcz wrote:What about WTFs as a percentage of total touches? Yi is over 50%.

That's a great question and those numbers would be interesting across the roster.

Who makes us say WTF the most? Other than Gadz I mean. I'd still say Redd, despite his scoring, would lead the team at over 54.8%.

How about [(PPG per W) / (PPG per L)] X(W/L)?

Too lazy to do actual stats to see if there is any corrolations...but maybe I'll get to it later...

Obviously this would be heavily weighted on team play and records...but if you put up big numbers in W and low numbers in L....your team obviously needs you more that what would be vice versa a player killing other teams and putting up #s in mop up time in worthless games and eventual Ls.

I'm going with....

(Points + 0.5 Assists+ Steals + Charges Drawn + 0.5 Blocks + Offensive Rebounds + 0.75 Defensive Rebounds) / (FGA + (FTA/2.2) + TO)

For my stat:

Bogut: 1.654
Mo: 1.382
Redd: 1.267

My stat would be a guys Points per minute scored when the team is down by 10 points or more versus the guys PPM when the team within 10 points or ahead in a game.

Something tells me our team would have all-star PPM totals if using the "we're down by 10 or more" split.

paulpressey25 wrote:My stat would be a guys Points per minute scored when the team is down by 10 points or more versus the guys PPM when the team within 10 points or ahead in a game.

Something tells me our team would have all-star PPM totals if using the "we're down by 10 or more" split.

All you have to do is look at their PPG as it is. We played the entire year down 10 or more.

Length of arm - length of leg + length of dick / size of brain

As for my proprietary stat:

And 1's Allowed: Who fouled and still gave up the bucket.

The A1A.

(Points + Assists*2)*(team offensive possession minutes/individual offensive possession minutes) - 1.2*(turnovers + offensive fouls).

Of course a statistician would have to begin tracking how much each team and individual handled the basketball per game. The idea would to discover who truly are the most efficient offensive players in the game, and weed out players who are just over-handling stat-stuffers like Marbury and Fatoine. The more you handle the basketball yourself, and don't do anything, the more time you're taking away from a teammate who could generate a good shot. If you project to generating 120 points per game if you hypothetically could handle the ball the entire game, you're a fantastically efficient ball player, and team should look for more players like you. If you project to generating 70 points per game, you're a terrible offensive player in spite of what raw statistics may indicate, and teams should look to trade you to some sucker. Obviously some spot up shooters like a Szczerbiak would be over-valued, but you could compare players of similar type. Like a Chris Paul to Baron Davis, for example.

BTW, the 1.2 was guesstimating what the average team's points per possession is. I have no idea if it's near correct. But the idea is that every time you relinquish a possession, you're giving the opposing team approximately 1.2 points.

We can call my statistic PPGEI (points per game efficiency index) or the Bern Projection.

paulpressey25 wrote:My stat would be a guys Points per minute scored when the team is down by 10 points or more versus the guys PPM when the team within 10 points or ahead in a game.

Something tells me our team would have all-star PPM totals if using the "we're down by 10 or more" split.

Kind of what I was going after..I think...

DTribbs wrote:How about [(PPG per W) / (PPG per L)] X(W/L)?

Too lazy to do actual stats to see if there is any corrolations...but maybe I'll get to it later...

Obviously this would be heavily weighted on team play and records...but if you put up big numbers in W and low numbers in L....your team obviously needs you more that what would be vice versa a player killing other teams and putting up #s in mop up time in worthless games and eventual Ls.

Although I think Charlie would be better suited to figured this all out.


sidenote: I think that the numb3rs sig is one of my better ones. But I've been told otherwise.

I'd like to see a measure of forcing up heavily contested shots while ignoring open teammates as related to contract size, measured as:

FGA x #ofDefendersGuardingYou + (CurrentSalary/MLE)

Because it's often negatively correlated to Assists, I am calling it the Assisn't, or Ass for short. Any guess who has the biggest Ass on the Bucks?