Tag: Quantitative Analysis
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Please refer to the related article which has been published before.
Continue here to get the regular season afternoon games vs. night games statistical comparison.
It's the same "old" story. They said he couldn't run, they said the Suns couldn't even make it to playoffs with him.
Here is briefly what changed after Shaq has come to Phoenix:
| EFFICIENCY | ||
| PACE | OFFENSE | DEFENSE |
| × | √ | × |
He slightly (0.29 more points per 100 possessions) helps Suns' offense but the team has allowed 1.67 more points per 100 possessions. That points out worse defense since he has arrived.
| SHOOTING | |
| eFG% | OPP eFG% |
| √ | × |
The Suns are shooting with a better effective field goal percentage while opposing teams are also shooting better to Suns' rim.
| REBOUNDING | |
| OR% | DR% |
| √ | √ |
This is what Shaq significantly changed. Better offensive (2.52% increase) and defensive (3.19% increase) rebounding percentage!
| FREE THROWS | |
| FTM/FGA | OPP FTM/FGA |
| √ | × |
The Suns are getting to foul line more and also allowing opponents to take more free throws.
| TURNOVERS | |
| TO/POSS | OPP TO/POSS |
| × | × |
Turnovers per possession (1.7% more) are hurting! Opponent turnovers forced (-1.67%) has also decreased.
What you will get in this article is kind of simple and easily comparable stuff. Don't expect me to make judgements about how smart the player movements were. This study should be considered as a comparison tool which helps us have some insight whether the trades, on the paper, seem to help out teams or not! It was just a matter of me listing traded players one under the other and putting stats (for the same player) together.
B2B
| OFFENSIVE EFFICIENCY | DEFENSIVE EFFICIENCY | |||
| TOP 5 | ∆* | TOP 5 | ∆* | |
| New Orleans | 9.4 | Toronto | -12.4 | |
| San Antonio | 8.0 | Seattle | -9.0 | |
| New Jersey | 5.1 | Portland | -4.9 | |
| Charlotte | 4.2 | Washington | -3.6 | |
| Minnesota | 3.6 | Dallas | -3.2 | |
| BOTTOM 5 | ∆* | BOTTOM 5 | ∆* | |
| Seattle | -10.3 | New Orleans | 12.9 | |
| New York | -5.6 | Boston | 7.3 | |
| Chicago | -2.9 | Charlotte | 7.1 | |
| Dallas | -2.7 | Denver | 7.1 | |
| Memphis | -2.5 | Utah | 6.6 |
*: Efficiency change under the given rest day situation
3rdIN4
| OFFENSIVE EFFICIENCY | DEFENSIVE EFFICIENCY | |||
| TOP 5 | ∆* | TOP 5 | ∆* | |
| Dallas | 3.9 | New Jersey | -12.4 | |
| Golden State | 3.1 | Milwaukee | -9.0 | |
| Utah | 3.0 | Boston | -4.9 | |
| Memphis | 2.6 | Indiana | -3.6 | |
| Phoenix | 1.8 | Denver | -3.2 | |
| BOTTOM 5 | ∆* | BOTTOM 5 | ∆* | |
| Boston | -3.7 | Sacramento | 12.9 | |
| Chicago | -3.4 | Atlanta | 7.3 | |
| Minnesota | -3.0 | New York | 7.1 | |
| Detroit | -2.6 | LA Lakers | 7.1 | |
| New Jersey | -2.3 | Dallas | 6.6 |
*: Efficiency change under the given rest day situation
4thIN5
| OFFENSIVE EFFICIENCY | DEFENSIVE EFFICIENCY | |||
| TOP 5 | ∆* | TOP 5 | ∆* | |
| LA Clippers | 15.7 | LA Clippers | -10.6 | |
| Portland | 9.7 | Boston | -8.4 | |
| Chicago | 8.8 | New York | -7.3 | |
| Indiana | 8.4 | Detroit | -7.3 | |
| San Antonio | 7.3 | Philadelphia | -6.5 | |
| BOTTOM 5 | ∆* | BOTTOM 5 | ∆* | |
| Seattle | -19.1 | Milwaukee | 20.3 | |
| Detroit | -13.1 | Cleveland | 18.1 | |
| New York | -10.1 | San Antonio | 17.0 | |
| Golden State | -8.4 | Dallas | 16.3 | |
| Phoenix | -7.3 | Houston | 14.5 |
*: Efficiency change under the given rest day situation
1 DAY REST
| OFFENSIVE EFFICIENCY | DEFENSIVE EFFICIENCY | |||
| TOP 5 | ∆* | TOP 5 | ∆* | |
| Detroit | 4.3 | Dallas | -3.4 | |
| New York | 3.7 | Boston | -3.3 | |
| Boston | 2.7 | New York | -3.1 | |
| Seattle | 2.7 | Detroit | -2.9 | |
| Minnesota | 2.3 | Philadelphia | -2.1 | |
| BOTTOM 5 | ∆* | BOTTOM 5 | ∆* | |
| Philadelphia | -2.0 | Philadelphia | 1.9 | |
| Toronto | -1.9 | Cleveland | 1.5 | |
| Milwaukee | -1.8 | San Antonio | 1.0 | |
| Cleveland | -1.6 | Dallas | 1.0 | |
| Phoenix | -1.2 | Houston | 0.9 |
*: Efficiency change under the given rest day situation
2 DAYS REST
| OFFENSIVE EFFICIENCY | DEFENSIVE EFFICIENCY | |||
| TOP 5 | ∆* | TOP 5 | ∆* | |
| Toronto | 6.5 | Sacramento | -5.8 | |
| Cleveland | 6.3 | Orlando | -5.3 | |
| Houston | 5.9 | New York | -4.6 | |
| Charlotte | 5.8 | Detroit | -3.6 | |
| New Orleans | 5.2 | Washington | -3.5 | |
| BOTTOM 5 | ∆* | BOTTOM 5 | ∆* | |
| San Antonio | -7.3 | Philadelphia | 7.2 | |
| New York | -6.4 | Dallas | 5.4 | |
| Seattle | -3.4 | Cleveland | 4.6 | |
| Utah | -3.3 | Utah | 4.1 | |
| Dallas | -2.9 | Minnesota | 3.8 |
*: Efficiency change under the given rest day situation
3+ DAYS REST
| OFFENSIVE EFFICIENCY | DEFENSIVE EFFICIENCY | |||
| TOP 5 | ∆* | TOP 5 | ∆* | |
| New York | 4.1 | Utah | -9.8 | |
| Cleveland | 2.7 | Minnesota | -8.3 | |
| Philadelphia | 2.3 | Sacramento | -6.6 | |
| Toronto | 2.1 | LA Clippers | -6.0 | |
| Phoenix | 1.1 | Philadelphia | -5.3 | |
| BOTTOM 5 | ∆* | BOTTOM 5 | ∆* | |
| Detroit | -6.8 | Detroit | 6.1 | |
| Charlotte | -6.6 | Boston | 5.9 | |
| Sacramento | -6.2 | Miami | 4.2 | |
| Golden State | -4.1 | Indiana | 2.5 | |
| Indiana | -3.9 | New York | 2.4 |
*: Efficiency change under the given rest day situation
ABBREVIATIONS
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B2B: teams playing second leg of back to back game sets
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3rdIN4: teams playing third game in four nights
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4thIN5: teams playing fourth game in 5 nights
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1: teams coming up the game w/ one day rest
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2: teams coming up the game w/ two days rest
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3+: teams coming up the game w/ at least three days rest
(1) by making a shot; (2) by missing a shot and not getting the offensive rebound; (3) by turning the ball over; and (4) by going to the line for two or three shots and either making the last shot or not getting the rebound of a missed last shot. POSSESSION =(Field Goal Attempts)+(Turnovers)+0.4*(Free Throw Attempts) - 1.07*(Offensive Rebounding Percentage)*(Missed Shots) PACE is the number of possessions a team uses per game. OFFENSIVE EFFICIENCY is the number of points a team scores per 100 possessions. DEFENSIVE EFFICIENCY is the number of points a team allows per 100 possessions. CORRELATION is a value between -1 and +1 that describes the degree of relationship between two variables. Defensive correlations are negative because lower defensive efficiency means better defense.
READ ME
Basics of modern basketball statistics lies behind the possession fact which must be considered as the key element to calculate team efficiency. The ball can only change hands four different ways:
DEFINITIONS
SEASON
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ON THE ROAD
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AT HOME
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LAST 5 GAMES
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Want to have the tables in MS Excel? Download the data
Basically; if the team is located at:
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right side of the black vertical line: The team has better offense than the NBA league average
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left side of the black vertical line: The team has worse offense than the NBA league average
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upper side of the black horizontal line: The team has better defense than the NBA league average
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lower side of the black horizontal line: The team has worse defense than the NBA league average
PLAYOFFS 2008
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| PLAYER EFFICIENCY RATING (PER) | ||||
| RANK | PLAYER | PER | ||
| 1 | C.Paul - Nor | 37.426 | ||
| 2 | D.Nowitzki - Dal | 32.572 | ||
| 3 | K.Bryant - Lal | |||