Stats 102: The 'Hive Five'

Let's tackle the 'Hive Five' first, the five things I normally look at after a game. In plain English, they're shooting, rebounding, ball-handling, foul drawing, and game speed. The first four are commonly referred to as the "Four Factors," a concept pioneered by Dean Oliver. Oliver has shown that the result of any single game can be explained through those factors alone (order of importance being 1. shooting, 2. turnovers, 3. rebounding, 4. fouls). I like to look at pace as well, because pace can throw a huge wrench into even the best laid plans.

Now, on to the stats themselves. I've put down the old stats the new ones are meant to replace, my understanding of each of them, and how they're calculated.

eFG% || Effective Field Goal Percentage || Replaces FG%

Field goal percentage is one of the easiest stats to understand. Just add up all the shots a player made and divide that by all the shots a player attempted. It's simple to calculate and gives a decent estimation of a player's shooting ability. However, FG% misses one thing: all shots are not created equal. Specifically, some shots are worth 3 points, and others 2. If you cruise through the FG% leaders from year to year, you'll see that the top shooters are always big men- Andrew Bynum, Tyson Chandler, etc. But these aren't the guys you'd associate with the word "shooter." What's missing?

Take this very simple example: Shaquille O'Neal takes 2 field goal attempts, both two pointers. He makes one of them. In 2 possessions, he has scored 2 points (or 1 point per possession). Steve Nash takes 3 field goal attempts, all three pointers. He makes one of them. In 3 possessions, he has scored 3 points (also 1 point per possession). According to FG%, Shaq has shot 50% while Nash has shot just 33%. But according to scoring efficiency, both players were effectively the same (1 point per possession). Effective Field Goal % (eFG%) corrects for this issue by weighting three pointers more than twos. It adjusts for the fact that threes are inherently more difficult to make.

Calculation: eFG% = (FGM + 0.5 * 3FGM)/FGA

Lg. Average: 49.7%, Best: 54.4% (PHO), Worst: 45.4% (LAC)

Hornets 08-09: 50.6% (9th), Hornets 07-08: 51.2% (6th) [Offense]

Hornets 08-09: 49.5% (17th), Hornets 07-08: 50.1% (16th) [Defense]

OREB%, DREB% || Offensive, Defensive Rebounding Percentage || Replaces Rebounds

"Win the rebounding battle" is the average commentator's favorite cliche. It's true though; it's an essential part of the game. The raw rebounds stat does a pretty good job telling who did the better job on the boards. But what happens when one team catches on fire from the field? The defensive team would be unable to get defensive rebounds, regardless of how well they box out. Ditto for the offensive players crashing the offensive glass. Therefore, a better way to measure rebounding is to count all possible rebounding opportunities (i.e., missed shots) and express as a percentage how many of those were rebounded. This can be done on a team and individual level, both offensively and defensively. By definition, the offensive rebound rate of one team plus the defensive rebound rate of the other team should equal 100%. So if we know the opposition's offensive rebound rate, we must know our own defensive rebounding rate (and vice versa).

Calculation: OREB% = Off. Rebounds / (Off. Rebounds + Opp. Def. Rebounds)

Lg. Average: 26.7%, Best: 33.0% (POR), Worst: 20.9% (SAS)

Hornets 08-09: 25.5% (23rd), Hornets 07-08: 27.0% (13th) [OREB%]

Hornets 08-09: 75.5% (4th), Hornets 07-08: 75.4% (3rd) [DREB%]

TOr || Turnover Rate || Replaces Turnovers

This is the simplest to understand: take raw turnovers, and find turnovers per possession. Turnover Rate (TOr) is sometimes referred to as TOV% (self explanatory) and tells how many times a team turns the ball over per 100 possessions. The trickier part is establishing what a "possession" actually is. The beginning and end of a possession is defined as the moment when the ball switches teams. Thus, a team can miss a shot, get an offensive rebound, miss again, get another offensive rebound, miss again, get another offensive rebound, etc, and it would all be part of the same possession. A possession can only end in a defensive rebound, a turnover, or free throw. By defining it in this way, each team essentially has the same amount of possessions per game.

Calculation: Possessions = FGA - Off. Rebounds + Turnovers + 0.4 * FTA

TOr (TOV%) = Turnovers / Posessions * 100

Lg. Average: 13.6%, Best: 12.1% (SAS), Worst: 15.6% (BOS)

Hornets 08-09: 13.3% (13th), Hornets 07-08: 11.4% (1st) [Offense]

Hornets 08-09: 14.5% (10th), Hornets 07-08: 13.5% (12th) [Defense]

FT/FG || Free Throw Rate || Replaces Free Throws

This is another example of expressing a raw stat as a rate statistic. However, instead of expressing it as free throws / possession, it's expressed instead as free throws/ field goal attempted. Add up free throws and divide by FGA... it's that simple. Generally, I use Free Throws Made and not Free Throws Attempted. This is a lot more annoying to do, but I like to go through shot charts after the game and count up shots attempted 5 ft. or closer. It can give a good idea of which team was more aggressive, and whether FT/FG reflected that.

Calculation: FT/FG = Free Throws Made / Field Goals Attempted

Lg. Average: 23.1%, Best: 28.9% (BOS), Worst: 20.9% (SAS)

Hornets 08-09: 23.4% (16th), Hornets 07-08: 19.3% (29th) [Offense]

Hornets 08-09: 24.1% (16th), Hornets 07-08: 18.4% (1st) [Defense]

Pace || Pace || Replaces... Random guessing of game speed, based on the score?

The formula for calculating pace is already hinted at above, in the discussion of possessions. In a single game, the above calculation is the same for finding pace. If you have raw stats, it's slightly more complicated to calculate and probably not worth mentioning here. If a game goes to OT, just normalize it back to 48 minutes.

Calculation: Pace = Possessions.

Lg. Average: 92.4, "Best": 98.3 (NYK), "Worst": 86.1 (POR)

Hornets 08-09: 87.2 (29th), Hornets 07-08: 89.9 (26th) 

Obviously, a high pace isn't necessarily a good thing, nor is a low one. I've been crunching numbers on this for a while now, and basically, my theory is that the top teams have little variance in their pace. Top teams should be able to impose their pace upon their opponents more often than not. On the flip side, a poor team's pace should theoretically bounce around from game to game. There should be an extended Stats 10[x] story on pace in the near future. "Near" will be a highly variable term though, since my wading through pace figures game-by-game, team-by-team closely resembles an elephant running a marathon in drying cement.

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