Two years ago I placed third in the TrueHoop Stat Geek Smackdown. As I noted when the final results were announced, Justin Kubatko and I based our picks solely on the numbers. The difference was that I only considered the quality of the teams (as measured by efficiency differential). Kubatko considered both team quality and home-court advantage. The different approaches did not matter most of the time. But in one playoff series it proved decisive.
Last year I was in the midst of my move from California to Utah. So I had to sit on the sidelines as Kubatko took his second title. Now that my family and I are settled into our new home in Utah I can once again participate in this contest (Kubatko, though, will not be participating).
Once again, here is my methodology. For the most part I am considering two pieces of information:
- Efficiency Differential or Offensive Efficiency minus Defensive Efficiency.
- Home-court advantage.
In general, efficiency differential is all you need to know in choosing the favorite. But if the teams are close, home-court advantage can make a difference.
With my approach outlined, let me briefly comment on each series in the first round.
We will start with the Eastern Conference.
Cleveland Cavaliers vs. Detroit Pistons
Cleveland’s Efficiency Differential: 9.74
Detroit’s Efficiency Differential: -0.54
Comments: I was born in Detroit so I will be rooting for the Pistons. But the numbers say the Pistons have no chance. The loss of Chauncey Billups at the beginning of the season essentially doomed the Pistons.
Pick: Cleveland over Detroit (4-0)
Boston Celtics vs. Chicago Bulls
Boston’s Efficiency Differential: 8.02
Chicago’s Efficiency Differential: -0.29
Comments: The loss of Kevin Garnett makes it unlikely the Celtics will repeat as NBA champions. But Rajon Rondo, Ray Allen, Paul Pierce, Kendrick Perkins, and Leon Powe should be enough to defeat the Chicago Bulls. Although I would note, the addition of Brad Miller does make Chicago more competitive.
Pick: Boston over Chicago (4-1)
Orlando Magic vs. Philadelphia 76ers
Orlando’s Efficiency Differential: 7.08
Philadelphia’s Efficiency Differential: 0.08
Comments: With KG hurt, Orlando is now the primary threat to the LeBron’s drive to return to the NBA Finals. Philadelphia does not look like a team that is going to stop Orlando from advancing.
Pick: Orlando over Philadelphia (4-0)
Atlanta Hawks vs. Miami Heat
Atlanta’s Efficiency Differential: 1.70
Miami’s Efficiency Differential: 0.27
Comments: This is the closest match-up in the first round in the Eastern Conference. The best player in the series is Dwyane Wade (21.3 Wins Produced). But Wade doesn’t have much help. So the Hawks – led by Al Horford and Mike Bibby – should take the series.
Pick: Atlanta over Miami (4-3)
LA Lakers vs. Utah Jazz
LA Lakers’ Efficiency Differential: 7.83
Utah’s Efficiency Differential: 2.71
Comments: The Jazz finished the season very poorly. Playoff picks, though, are based on the entire season. Unfortunately, even when you look at the entire season — and take into account Utah’s injury problems — the Lakers are still the favorites in this series.
Pick: Lakers over Utah (4-1)
Denver Nuggets vs. New Orleans Hornets
Denver’s Efficiency Differential: 3.51
New Orleans’ Efficiency Differential: 1.71
Comments: New Orleans actually had the 9th best differential in the Western Conference. So if efficiency differential was used to pick the playoff teams, Phoenix would be in and New Orleans would be at home. The Hornets do have the most productive player in the game. Chris Paul produced 29.5 wins and posted a 0.471 WP48 [Wins Produced per 48 minutes]. As noted last January, Paul’s numbers remind us of Magic Johnson. Paul, though, doesn’t have the help Magic had with the Lakers in the 1980s. In fact, with Tyson Chandler’s decline this year, there really is no other outstanding player on this team once you get past Paul. Consequently, Denver should be favored.
Pick: Denver over New Orleans (4-3)
San Antonio Spurs vs. Dallas Mavericks
San Antonio’s Efficiency Differential: 4.10
Dallas’ Efficiency Differential: 2.09
Comments: This is the hardest series to call. The Spurs lost Manu Ginobili towards the end of the season. So San Antonio’s efficiency differential is misleading. Without Ginobili I am not sure San Antonio would have made the playoffs. Furthermore, when we look at Dallas we see a team that underachieved. More specifically, Dirk Nowitzki and Josh Howard underachieved. Had Nowitzki and Howard played as they did last year the Mavericks would have challenged the Lakers this year. Although I should ignore what a team did recently (I think the entire season is more important), I am going to use what Dallas did across the last few games of the season to add further justification for my pick.
Dallas over San Antonio (4-2)
Portland Trail Blazers vs. Houston Rockets
Portland’s Efficiency Differential: 5.93
Houston’s Efficiency Differential: 4.27
Comments: In terms of efficiency differential, the Rockets finished as the sixth best team in the NBA and the third best team in the Western Conference. Normally this means a team should at least advance to the second round. But the Rockets have drawn the fifth best team in the NBA and the second best team in the Western Conference. This means the Rockets are once again unlikely to make it out of the first round (the same story we have seen since 1997).
Pick: Portland over Houston (4-3)
So those are my picks. If my picks are correct, then the second round should go as follows:
- Cleveland over Atlanta
- Orlando over Boston
- LA Lakers over Portland
- Denver over Dallas (well, maybe not)
The conference finals should be won by the Cavaliers and Lakers. And then the NBA champion should be….well, I am not sure. At least I don’t have to be sure right now.
In other words, I am only committed to my first round picks for the Smackdown. Once the first round is over I will be back to officially pick the winners in round two (and eventually offer a pick for NBA champion).
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Our research on the NBA was summarized HERE.
Wins Produced, Win Score, and PAWSmin are also discussed in the following posts:
Finally, A Guide to Evaluating Models contains useful hints on how to interpret and evaluate statistical models.