Missing and Missing and Missing in Minnesota

Posted on April 15, 2008 by


In 2005-06 and 2006-07, Kevin Garnett produced wins in large quantities for Minnesota.  But his teammates, as Tables One and Two note, did very little. Consequently, KG did not often receive the acclaim his production deserved.

Table One: Stars and Everyone Else in 2005-06

Table Two: Stars and Everyone Else in 2006-07

This past off-season, Kevin McHale – the T-Wolves GM — freed KG, sending Garnett to the Boston Celtics for Al Jefferson and a collection of additional players.  If we focus solely on KG and Jefferson, the T-Wolves lost on this deal.  Jefferson is a very productive player – 0.252 WP48 [Wins Produced per 48 minutes] last season – but he’s not as productive as Garnett.

Of course, despite this move, the T-Wolves could have improved if the team simply upgraded its very weak supporting cast.  In other words, Jefferson with better teammates could do better than Garnett and really bad teammates.

The Continuation of the Story in Minnesota

When we look at what the T-Wolves did after 80 games this season, though, it appears the “weak supporting cast” problem persists in Minnesota.

Table Three: The Minnesota Timberwolves after 80 games

Al Jefferson posted a 0.222 WP48 this season.  In other words, he was about as good as advertised.  Unfortunately, his teammates were also as bad as we expected.  Heading into this season we would have expected Jefferson and company to win 22 of its first 80 games (if we assumed each player performed as he did last year).  When we look at the 2007-08 season we see numbers that are consistent with a team that should win 21.6 of its first 80 games.  Yes, the T-wolves have managed to match our expectations almost perfectly.

When we look at the performance of individual players we see a remarkable level of consistency.  The biggest leap was made by Sebastian Telfair.  Last year he posted a (-0.052) WP48 (which is really, really bad).  This year his mark is (-0.001) (which is just really bad). 

The consistency of this team means it was possible for us to know that Jefferson was not going to get much help before the season started.  Looking at last year’s numbers, we would have expected Jefferson’s supporting cast to post a 0.021 WP48.  Through 80 games this season the cast has a WP48 of 0.025.

Looking back at Tables One and Two we see that both the expected and actual levels of productivity for the T-wolves supporting cast are the worst we have seen the past two years.  And just to highlight how bad it has been in Minnesota the past three seasons, let’s note – as Table Two indicates — that the average supporting cast posted a 0.074 WP48 in 2006-07.  With this average in mind, here are the marks posted by the supporting cast in Minnesota the past three seasons.

2005-06: 0.027

2006-07: 0.031

2007-08: 0.025 (after 80 games)

It’s important to note that these are not the same cast of characters in Minnesota.  Only three players – Marko Jaric, Mark Madsen, and Rashard McCants – have played all three seasons for the T-wolves.  In all, 30 different players have suited up along side KG and Jefferson.  And of all these players, here are the only players to post a WP48 in excess of average (average WP48 in the league is 0.100).

2005-06: Wally Szczerbiak (0.130) and Eddie Griffin (0.119)

2006-07: Craig Smith (0.113)

2007-08: Kirk Snyder (0.133)

Every other player employed by Minnesota the past three seasons (not named Garnett or Jefferson), has been below average.

Some Lessons

Here are the lessons all this teaches (I think):

1. Kevin McHale – the team’s general manager – is able to identify extremely productive power forwards (see Garnett and Jefferson).  But he can only see one at a time (see all the other power forwards).

2. McHale knows that the supporting cast is bad, hence he keeps bringing in new players.

3. McHale doesn’t seem able to find “good” players consistently.  And this track record has persisted since he was given this team more than a decade ago.

Point #3 might be off the mark.  Let me offer another explanation (one that is less than serious).

McHale was a power forward for the great Boston teams in the 1980s.  Although McHale was a productive power forward, he did take a back seat to Larry Bird (and maybe Robert Parish).  Maybe McHale is constructing teams where clearly the power forward is the best player.  To make this clear, he has to choose really bad players at every other position.

The Kirk Snyder Story

Okay, this column is descending into the silly.  Let me close by offering a quick comment on the new number two man in Minnesota: Kirk Snyder.

Snyder was drafted by the Utah Jazz with the 16th pick of the 2005 draft.  He was then traded to New Orleans in 2006.  The next year he was traded to Houston.  And then last February he was traded to Minnesota.

When we look at Snyder’s career performance, we see a player that has gradually improved.

Table Four: The Number Two Man in Minnesota

As Table Four indicates, Snyder’s first year was quite bad.  He was below average at everything except rebounding and blocked shots his rookie season.  In New Orleans his shooting efficiency improved and turnovers were reduced.  His progress continued in Houston.  And in Minnesota he is playing his best basketball ever.

Generally when a player has four employers in four seasons, his game has problems.  In Snyder’s case, despite bouncing around the league, he has still managed to get better.  In fact, he is now a rare commodity in Minnesota.  Snyder is actually an above average player.

If Snyder can continue to produce, then Minnesota will have one productive player to pair with Jefferson next year.  And if McHale can find just two or three more above average players, Minnesota might actually be competitive.  Of course, as fans of the T-Wolves know, the “if” in the previous sentence is one giant IF. 

– DJ

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.