I guess what I”m getting at, is these stats reward guys who can create on offense, or stop on defense. It does not reward guys like Novak who do the intangibles. Novak doesn’t create on offense. He isn’t really a lock down defender. He sets up his teammates. Regardless of how well he sets up his teammates, his score is going to be heavily reflected on whether or not his teammates “cash in” when he gets them the ball.

On the flip side, you look at a guy like Manny or Peedi, they create their own offense. These numbers are highly indicative of their play and whether or not they are creating offense. For stu, it’s about whether or not he’s locking down his man on defense.

I can see for guys like Wright, Gibson, and to an extent Novak they are just role players who are used with the intent of setting up their teammates. Their scores are dependent upon other people more than the “stars” of the team.

I don’t think it means Novak or Vogrich or Gibby played poorly if their score is low necessarily. It could mean they played really well, gathered rebounds, forced turnovers, passed the ball well…but their team mates didn’t make the shots when they passed the ball.

I’m just offering one shortcoming of this method, not saying this is necessarily true. That’s why I wish there was a way to factor in turnovers and rebounds into the equation for a more complete metric.

“Teams rush floors when they do something phenomenal,” said Kansas State forward Curtis Kelly, who had 17 points and eight rebounds against one college basketball’s best front lines. “It’s flattering. They knew we were going to win. They didn’t have to rush the floor because they believed in us.”

(In response to KSU not rushing the court last night)

That is kind of what I was getting at, but after thinking about it in the shower this morning, that’s really the whole point. In reality, it doesn’t matter how much hustle, grit, steadiness, or whatever adejective we can come up with a player has. Scoring differential is the only stat that matters at the end of the day in basketball (or any sport for that matter). If on a consistent basis the team is doing better with you off the court as opposed to on, you shouldn’t play as much, end of story.

One interesting thing to add (way more work) would be to see how a players Roland Rating worked over different time frames in a game. Say a player has a great RR the first 3 minutes they’re in, but they fatigue and they end up moving back to about neutral, that would tell the coach to either play him in short spurts or get him in better shape. Or say someone has an overall solid RR, but their rating in the last three minutes of games is horrible, you’d keep him out of crunch time. Just some ideas on how it could be expanded.

The one thing I think people are a little hung up on with the whole Gibson/Vogrich thing is that this stat doesn’t measure how “good” a player is. It simply measures the score differential when the player is on the floor.

Novak gives intangibles, Gibson made a HUGE block…those are not necessarily reflected in this statistic, it doesn’t mean those plays or players are any “less good”.

I guess it’s semantics, but I think it’s important. Regardless of how we feel about Stu or Gibson as all around players and what they can bring to the table in hustle, rebounding, height, defense, etc…this stat only measure scoring differential, not the overall “goodness” of a player.

One thing I was wondering about for the statisticians out there is if there is a way to incorporate turnovers and steals into these formulas. For example, we know what the average point per posession was in a given game. So what if we took all of UofM’s defensive rebounds and multiplied it by UConn’s point per posession (in effect saying “What if they cleaned up all their rebounds, how many more points would it have resulted in”). Do the same for turnovers: “if they hadn’t turned the ball over at all, how many more points would it have resulted in”. Do that for both sides and see what the results show.

I’m guessing it will be skewed by fast break points since many rebounds (and especially turnovers) lead to fast break points at the other end. But I’m just thinking out loud if there is a way to feed rebounds and turnovers into an equation along with scoring to determine how well a team played.

Thoughts?

Douglass was off the court for 45 (played 195 of 240) minutes and Michigan outscored their opponents by 31 points. That’s .688 points per minute multiplied by 40 equals 26.55 “off per 40″.