It is obvious that this year's team is better than the previous years. What is interesting though are reasons that the media, "Cyclone Insiders", etc., are attributing to the results. Mostly, they are qualitative, which are OK, but I'm more of a hard stats type of a guy. I want to be able to measure changes, and use qualitative observations to explain the results, more-so than being the conclusions.

I wanted to take a look at some of the statistics to see how we can explain not only the team's improvement, but the players improvement as well.

Before I jump into the numbers, I wanted to give a little bit of background regarding basketball statistics. In short, most of the traditional ones in box scores do not tell us everything we need to know, but with putting together some of these stats, along with using research done by prominent basketball statisticians, we can put together some thoughtful numbers that explain the whole picture.

Traditionally, stats are used in terms of averages/game or averages/minute. While I use these from time to time it doesn't necessarily give the whole picture. A much better way to looking at this is per possession. The main reason being that the number of possessions can vary from game to game. In a slow tempo game, it might be great to score 75 points in a game where there are less possessions. In a more uptempo game, there will be more possessions, so perhaps 75 points is not enough as perhaps the other team is scoring 85-90.

As far as players go, we often times talk about a player scoring a certain number of points/game. But again, the amount of possessions a player is on the court for, really varies. Instead of taking what he does on a per game basis, it's better to look at what he's doing when he's on the floor.

When looking at team stats, there are 6 that I like to look at: Offensive Efficiency, Defensive Efficiency, and each of the "Four Factors". Below is an explanation of each stat:

Offensive Efficiency: Points scored per 100 possessions.

Defensive Efficiency: Points allowed per 100 possessions

The efficiency stats are tricky to calculate, but luckily Ken Pomeroy calculates this for all of the teams, on a daily basis. Below is a table that summarizes the efficiencies in 2008-2009 vs. The First 5 Games thus far:

When looking at the offensive numbers, it may be surprising that the change is relatively small, compared to the previous year. I think there are a few of factors going on. First is free throw shooting. Second is that a lot of the reserves are getting more minutes early on, and our offense definitley slows down when Brackins, DG, and Gilstrap are out of the game. The third is that possessions aren't actually charted but instead approximated from the box scores. There's a formula that uses field goal attempts, offensive rebounds, turnovers, and free throw attempts to approximate possessions.

When looking at the defense, the numbers may be a bit suprising. From looking at the team, I don't think we are all that great defensively. What's helping the numbers it the fact we're playing teams that do not shoot the ball well. I would expect us to allow more points/100 possessions than last year. That isn't necessarily a bad thing, as long as we're scoring more than giving up. I'd rather have a good offensive team that is OK at times defensively, than a great defensive team that's OK at times offensively.

Four Factors

Basically a guy named Dean Oliver did some research that's widely accepted across basketball statisticians. He determined the Four Factors that lead to wins in the game of basketball. They are shooting, turnovers, rebounding , and free throws. Makes sense right? Nothing too groundbreaking here.

The main difference lies in how to measure the shooting, turnovers, rebounding, and free throws. Below is a quick explanation of each:

eFG% (40% Weighting): Effective Field Goal Percentage. It adjusts for 3 pointers, as it's worth more points. Whoever has the better eFG% at the end of the game, wins the "Shooting" Component.

TOV% (25% Weighting): Turnover Percentage. Percentage of possessions that are turnovers. Whoever has the lower TOV% wins the "Turnover" Component.

ORB% (20% Weighting): Offensive Rebound Percentage. It's the percentage of rebounds that are offensive rebounds. Whoever has the higher, wins the "Rebound" Component.

FT Rate (15% Weighting): Measures the amount of free throws attempted vs. field goals attempted. The idea here is that whoever gets to the line more, is going to have a better chance at scoring more easy baskets. Whoever has the higher FT Rate, wins the "Free Throw" Component.

Hopefully that's all straightforward. I know I've seen my fair share of Cyclones games where we did almost everything better than the other team except for shooting. Now one can understand why it's hard to overcome superior shooting.

Let's take a look at how the Cyclones have done in this areas compared to last year:

I think the TOV% will go down as the season goes on. Diante Garrett has done a pretty good job managing turnovers in my opinion, and we've given a lot of playing time to Colvin who's making some freshmen mistakes. As DG plays more, and Colvin improves, the TOV% will get better.

It's amazing to see how bad we were last year. I really am amazed that we won as often as we did, but as you can see, we were only mediocre at shooting last year, as opposed to bad at everything else.

So far our numbers and ranks are obviously a small sample size, but it explains how we're rolling the competition at this point... Remember at this point last year, we were coming off a loss against a horrible Hawaii team, and opened the season with a nail-biter against UC-Davis.

Pomeroy and Sagarin Ratings:

I feel like I should say something about these as well. Both Ken Pomeroy and Jeff Sagarin are respected statisticians. Both rank the teams throughout the season, based on different factors. I would say that Pomeroy is intended to show what teams have already done. It isn't a predictive model. With Sagarin, I only look at the predictor column. Sagarin takes into account other factors and aims to not only rank the teams, but also to give a user an idea of what margin of victory would be against another team.

Pomeroy Rating (as of 11/25): 41st

Sagarin Rating (as of 11/26): 48th - remember I'm looking only at the predictor. Iowa State would beat Saint Louis by 3.5, Northwestern by 8, and Notre Dame by 3.5 as well, in case you were curious of our chances this weekend regardless of opponent.

I know that's a lot of info, but I find this stuff interesting. Of course, all of this changes throughout the season, and I will be referencing these stats and rating systems throughout the year.

In my next installment, we'll shift the attention from the team as a whole, to the individual players.