The post “Kobe Makes Pau Gasol Unhappy” has apparently made fans of Kobe unhappy. Such fans are quite interesting. As many people have learned, any suggestion that Kobe is not the greatest basketball player in both this world and all future worlds is quickly met with a great deal of anger in the Internet. And this anger is often part of a package that includes misspelled words and poorly constructed arguments (which readers such as Simon, jbrett, ilikeflowers, and others are doing a great job of adddressing).

Unfortunately, I wish to tell another story today that involves Kobe. My story is actually focused on Clyde Drexler, but I think it’s a good idea to begin with a direct comparison of Clyde the Glide and Kobe.

Table One: Comparing the Career Performances of Kobe Bryant and Clyde Drexler

As Table One reports, Drexler’s career averages top Kobe’s marks with respect to shooting efficiency, rebounds, steals, blocked shots, and assists. And yet Kobe is considered by many to be the better player.

Why is Kobe Better?

There appear to be three explanations for why Kobe is thought to be the better player. First – as Table One notes – Kobe is the more prolific scorer. Of course, this is because Kobe leads Drexler in field goal attempts.

Another issue is that Kobe spent his career with the Lakers while Drexler played for Portland and Houston. In general, players for teams located in LA and New York tend to get more media exposure and therefore are thought of as better players.

And then there is the issue of championships won. People tend to think players on championship teams are better than those who toil for teams that tend to lose in the playoffs. It’s easy to point out the absurdity of such logic. Teams win championships and one can pick up a ring just because you happen to have the right teammates. After all, does anyone think Luc Longley (three titles) was a better center than Patrick Ewing (0 titles)? Or that Robert Horry (seven titles) was a better forward than Dominique Wilkins or Karl Malone (0 titles)? Despite such obvious arguments, people will note that Kobe’s four titles must mean he’s a better guard than Drexler (1 title).

Drexler Second Best

Drexler did appear in the NBA Finals four times. But his team came up “second-best” three times. And that appears to be the story of Drexler’s career. He often toiled for the “second-best” team.

Back in 1990, Drexler and the Portland Trail Blazers finished the season with league’s 4th best efficiency differential (offensive efficiency minus defensive efficiency). After defeating the Phoenix Suns – the team with the best differential – in the Western Conference Finals, the Blazers faced the Detroit Pistons in the NBA Finals. The Pistons differential of 6.2 was only slighly better than the Blazers mark of 5.9. But after seizing homecourt advantage in the series, Portland went on to lose three consecutive games at home.

The next season the Blazers were even better. When the regular season ended the Blazers differential of 8.3 was only bested by the 9.2 differential posted by the Chicago Bulls. But in the Western Conference Finals the Blazers were defeated by the LA Lakers.

In 1991-92 the Blazers again posted the best differential in the Western Conference. Their mark of 7.0, though, lagged far behind Chicago’s 10.6 differential. Hence it was not a surprise that the Blazers were defeated in the NBA Finals.

Across the next two seasons the Blazers slipped. Then in 1994-95, Drexler was traded to the Houston Rockets. And despite the fact the Rockets were underdogs in all four rounds in the playoffs, Houston managed to repeat as NBA champions.

The next season the Rockets were swept in the second round of the playoffs, while the Chicago Bulls won 72 games and the NBA Title. At this point it looked like Drexler was never going to contend for another NBA championship.

What Might Have Been in 1997

But then the Rockets made a move that looked to return this team to contending status. In August of 1996 the Rockets traded for Charles Barkley. This acquisition gave the Rockets an impressive trio of Hakeem Olajuwon, Drexler, and Barkley. These three produced 45.2 wins in 1995-96, so it wouldn’t take much more for the Rockets to contend in 1996-97.

When we look at what the Rockets did that season, though, it seems like the “much more” never arrived.

Table Two: The Houston Rockets in 1996-97

As Table Two indicates, the Rockets won 58 games in 1996-97. But the team’s efficiency differential – and corresponding Wins Produced – is more consistent with a 52 win team. After the aforementioned trio, the Wins Produced of the rest of the roster was only 14.1.

So there wasn’t much after Hakeem, Clyde the Glide, and Sir Charles. Plus, Hakeem – who was 34 years old, saw his production decline. Had he maintained what he did in 1995-96 the Rockets would have been five wins better.

Such an improvement, though, would not have been enough to catch the Chicago Bulls and the Utah Jazz. There was a move made, though, that should have made a difference. A month before the Rockets acquired Barkley, Houston signed Brent Price. In 1995-96, Price produced 9.8 wins and posted a 0.230 WP48 [Wins Produced per 48 minutes] for the Washington Bullets.

As Price’s bio at NBA.com reveals, his 1996-97 season went off the tracks before it began:

Price was expected to step in as Houston’s regular point guard after he joined the Rockets as a veteran free agent, but a broken left humerus suffered in a preseason game on Oct. 24 ruined those plans. He did not make his debut until Dec. 28, and just when he seemed to be playing his way back into top form he suffered a torn anterior cruciate ligament in his right knee in a game against the Los Angeles Lakers on Feb. 25. He was placed on the injured list on March 3, underwent surgery on March 15 and sat out the remainder of the regular season and postseason…Price was on a roll when he got hurt the second time. In the eight games prior to his torn ACL, Price had averaged 10.1 ppg and 4.9 apg while shooting .482 from the field and .462 from behind the arc…That spurt included a season-high 20 points on 8-for-11 shooting, plus a season-high six assists, in a 106-97 win over Vancouver on Feb. 11.

Because Price was hurt the Rockets had to turn to Matt Maloney. An undrafted rookie out of the University of Pennsylvania, Maloney started every game in 1996-97 and produced 2.7 wins with a 0.053 WP48. Had Maloney’s minutes gone to the Price we saw in 1995-96 (and Maloney took Price’s 1996-97 minutes), the Rockets would have been 11.3 wins better. Coupled with Olajuwon maintaining what we saw in 1995-96, the Rockets would then have been transformed into a team with 69.8 Wins Produced.

This mark might have allowed the Rockets to challenge the Chicago Bulls (who won 69 games in 1996-97). And it’s possible Drexler might have won a second title.

Of course, Drexler, Olajuwon, and Barkley would have still had to defeat Michael Jordan, Dennis Rodman, Scottie Pippen and company in the NBA Finals; and even with Price and Olajuwon performing as we saw in 1995-96 the Rockets were not really better than the Bulls. So Drexler might have still finished second best to Jordan.

So even this “what-if” tale is consistent with the story of Drexler’s career. Even if the breaks did go his way, he was still not as good as Jordan. But that really isn’t such a shame. Second to MJ is still pretty good.

After all, Kobe Bryant – how is also pretty good — is also second to Jordan. But Kobe is not – as the above table indicates – as good as Drexler (yes, I could have let it go but I didn’t).

– DJ

The WoW Journal Comments Policy

Our research on the NBA was summarized HERE.

The Technical Notes at wagesofwins.com provides substantially more information on the published research behind Wins Produced and Win Score

Wins Produced, Win Score, and PAWSmin are also discussed in the following posts:

Simple Models of Player Performance

Wins Produced vs. Win Score

What Wins Produced Says and What It Does Not Say

Introducing PAWSmin — and a Defense of Box Score Statistics

Finally, A Guide to Evaluating Models contains useful hints on how to interpret and evaluate statistical models.