There’s also no doubt that Eric Gordon is an incredible talent. He topped all others using the three proficiency models that I used in my analysis of the Big Ten’s top players. But his scoring proficiency is so much greater than anyone else in the conference (he leads second place Geary Claxton by almost six points per game) that it’s quite possible there might be a little of the Pete Maravich effect, albeit at a much smaller level, at work here.

That thought led me to see if I could come up with an alternate way of determining the top guys. I chose to base my approach on Dean Oliver’s Four Factors. Basically, Oliver says the four keys to winning basketball are scoring, turnovers, rebounding, and free throw shooting. My approach was to analyze the Big Ten’s top players using those four factors.

For scoring, I looked at the points that a player scored plus how he assists of other players. However, I didn’t simply add assists to points. In the Wages of Wins, the authors determined that an assist was worth approximates .7 of a point, so I used that as my adjustment factor for adding assists to a player point totals.

I followed a similar strategy with turnovers. Looking to calculate a players net turnovers, I took a players steals and subtracted turnovers from them. But once again I followed the lead of the Wages of Wins authors by adding in .7 blocks and subtracting .4 times a players personal fouls.

For my rebounding number, I again used the Wages’ analysis. They say that offensive rebounds are more important that defensive rebounds, so I used .7 and .3 as their respective weighting factors.

From a free throw shooting perspective, it doesn’t do a player any good to shoot 1.000 if he never gets to the line, so the standard measure for evaluating a player’s effectiveness it to look at how many free throws he makes relative to the number of field goal (not free throw) attempts. You improve that number by getting to the line often and making your shots when you do.

So those are the formulas that are the basis for evaluating the four factors. But, so far, what I’ve done doesn’t vary much from the Win Score calculation. Here’s where the twist comes in. What I want to evaluate is how a player stacks up among a select group. Specifically, I start with the top 30 players in the league in terms of minutes played per game, under the theory that if a guy isn’t on the floor for most of the minutes that his team is playing then he’s not very likely to be one of the top guys in the league (as an aside, it also makes my data collection one heckuva lot easier). Then I rank each of the players in each of the four categories. The score that a player gets in each category is based on his rank, not his raw score (the best player of the 30 players in any category gets 10 points, the worst gets .33). All of a sudden the big scoring lead that Gordon has over second place Geary Claxton doesn’t mean quite so much.

But I’m not quite done yet. Dean Oliver says his four factors are not created equal. They each have a relative weight. The specific weighting factors that Oliver suggests are 10 for scoring, 5-6 for turnovers, 4-5 for rebounding, and 2-3 for free throw shooting. I simply take the midpoint for his suggested ranges and apply it to each of the factors. Then as a final step I normalize all the scores to 10.0 (I’m a firm believer in the Bo Derek rating system – no 158.3 perfect quarterback rating for me – a perfect score is 10.0).

So to score well under this system, a player will need to have a complete game. He’ll have a hard time overcoming any deficiency simply by racking up a huge lead in any one factor.

So what does this mean for Eric Gordon? How will his game stand up?

Answer tomorrow.

In his groundbreaking book “Basketball on Paper”, Dean Oliver hypothesized that there were four elements to basketball success, shooting, turnovers, rebounding, and free throws. He referred to them as the “Four Factors”, a name which has been pretty much universally accepted by the APBRmetrics community. These factors can be thought of as applying both offensive and defensively, so it is reasonable to think of them as eight measures of a teams performance. Much of APBRmetrics theory and analysis consists of developing formulas for measuring both team and individual performance across these four factors.

Most of the reporting and analysis that I do on this site is based on Oliver’s original formulas for studying the four factors. Here’s a rundown of the basics of each.

Shooting

The most important measure of all is how well does a team shoot the ball. Getting the ball in the basket remains the objective of the game and how well you do that does a long way toward determining whether you are going to win or not. Appropriately, preventing your opponent from scoring is the most important defensive measure.

The generally accepted measure of a team’s shooting ability is effective field goal percentage, or eFG% for short, which combines 2pt and 3pt shots by weighting a made three point shot with an extra 50%. The specific formula is:

eFG% = (FGM + 0.5*FG3M)/FGA

Turnovers

The second most important factor is protecting the ball or avoiding turnovers. Empty possessions are the bane of every coach. As has been often said, “100% of your shots not taken don’t go in”. A turnover results in a shot not taken. However, not all turnovers are equal. The fewer possessions that a team has, the more important it is to avoid turnovers, since the opportunities to score for teams that play slow are fewer than teams that play at a high pace.

Thus, the appropriate measure for how well a team protects that ball is not total turnovers. Rather it is what percentage of their total possessions result in turnovers. Specifically, it’s turnovers divided by possessions where possessions are defined as:

Poss. = FGA – OR + TO + 0.44 * FTA

Note: Oliver’s weighting factor for free throw attempts is 0.4 which is the number that continues to be used for NBA analysis. Work by John Hollinger and others suggest that the proper factor for college teams is 0.44.

Rebounding

The key here is, specifically, offensive rebounding. If a team is a strong offensive rebounding team they can partially make up for a poor first factor. An offensive rebound gives a team a second chance at scoring. You still have to put the ball in the basket but if you get multiple opportunities to try it during a possession than you can go a long way toward making up for poor shooting. Conversely, limiting your opponent to one and only one opportunity during their possessions is important on the defensive side of the ball.

The proper measure for this isn’t to compare your offensive rebounds with your opponents, it’s to measure what percentage of the rebounding opportunites that presented themselves while you were on offense resulted in your keeping the ball, i.e. it compares your offensive rebounds with your opponents defensive rebounds. The specifics:

OR% = OR / (OR + Opponents Def Reb)

Free Throws

The last measure of offensive performance is getting to the foul line. But it’s not just how well do you shoot free throws while you are on the line, it’s how successful are you at getting to the line AND making them. What you would like to see is a high number of free throws made per shot attempt, so the proper stat becomes:

FTM/FGA

Relative Value

In his original work, which primarily studied NBA teams, Oliver says that relative importance of each of these factors is:

• Shooting (10)
• Turnovers (5-6)
• Offensive Rebounding (4-5)
• Free Throws (2-3)

One thing that shouldn’t be overlooked is that these relative weights will differ by team based on the style of game that they play.

Game Analysis

When I do any game analysis, I will always try to base it on Oliver’s Four Factors. Breaking each team down offensive and defensively across these four factors can provide substantial insight into any game.