There’s no doubt that Pete Maravich was an incredible ball player. The numbers that he put up were unheard of for a guard – plus he did it without the benefit of the three point shot. However, as good as he was, I don’t think anyone would ever call him the greatest ball player ever. His ability to score hid some deficiencies in his game.
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?