Does acquiring NBA stars lead to winning?

nba_stars

The 2017 offseason will go down as one of the most entertaining ever, mostly because of several NBA stars being traded to other teams. Some could argue that, altogether, 7 stars were traded: Chris Paul, Paul George, Carmelo Anthony, Jimmy Butler, Kyrie Irving, Isaiah Thomas and Dwight Howard. In addition to those, there was another maximum salary player who changed teams, Gordon Hayward. It seems that a lot of teams decided to make significant changes, partially because of Golden State Warriors and Cleveland Cavaliers being so dominant, and this lead to a lot of discussions, negotiations and transactions. There is a general consensus among general managers, coaches, journalists, fans, even NBA players, that you cannot win without the best talent, which in practice means having at least two NBA stars on your team. Consequently, we started thinking about to what extend trading for or signing NBA stars actually leads to winning in practice.

In order to answer the question, we combined data from different tables and carried out statistical analysis. There were some important methodological aspects which need to be explained. Firstly, we had to define who NBA stars were. Were they All-Star players? Were they maximum salary players? Were they only All-NBA First Team players? In the end, we decided to include in the analysis all players who were named to any All-NBA 1st, 2nd or 3rd Teams since the 1999-2000 season (up to 2016). There were 78 players who made an All-NBA team since then. Secondly, we had define conditions under which those players would still be considered NBA stars at the time of a trade or an FA signing, i.e. at least one of the following conditions would have had to be met:

  1. Player was traded in an offseason straight after he was named to the All-NBA Team.
  2. Player was traded during the following season after he was named to the All-NBA Team.
  3. Player’s Win Shares (WS, WS/48) and PER remained at a similar level in the season before the trade as in his (last) All-NBA-Team season.
  4. Player was still among the best players in the NBA in Win Shares (WS, WS/48) in the season before the trade. (WS and WS/48 are generally the best indicators for being named to All-NBA Teams).

Out of those 78 All-NBA players, we selected, based on the conditions defined above, 32 NBA stars who changed teams between 2000 and 2016. There were 24 players who didn’t change teams after being named to All-NBA teams – most of them were current players who were still with the team which drafted them (e.g. Blake Griffin, Russell Westbrook), but some of them were players who played for one team only (e.g. Kobe Bryant, Yao Ming). The other 22 players did not qualify as star players at the time of a trade or an FA signing. Those were players such as David Lee, Rajon Rondo, Derrick Rose or Dwayne Wade.

Out of the “qualified” 32 players, 7 of them changed teams twice while still playing at an All-NBA Team level – Baron Davis, Dwight Howard, Jason Kidd, LeBron James, Ray Allen, Stephon Marbury and Steve Nash. This gave us a sample of 39 times when star players changed teams. While there were no star signings or trades in 2009, the most “popular” year for acquiring stars was 2004 (O’Neal, McGrady, Carter, Nash, and Marbury). Now we will show how adding stars to new teams affected their performance, measured in regular season Win% and playoff performance, before and after the addition.

team_winning_percentage_individual

The graph reveals that there are no clear and immediately observable trends, expect for the fact that variability of Win% is much higher in the fourth season compared to the season before trading for or signing a star player. We can argue that signing a star can lead to some good performances, but could as well go terribly wrong. For example, Boston Celtics’ Win% was on average 0.421 higher in the four seasons after trading for Kevin Garnett and Ray Allen, while LA Lakers’ Win% was on average 0.286 lower in the four seasons after trading for Dwight Howard and signing Steve Nash, also because of Howard’s departure and Nash’s injuries and early retirement.

average_winning_percentage

The next chart shows that, on average, stars generally tend to join better teams in free agency then they are traded to. We can also see that there is an increase in winning percentage in the first season after acquiring a star player, no matter how that star joined the team, either in free agency, being traded for in the offseason or during the season. In the second season, Win% tend to decrease for teams which signed free agents or traded for star players in the offseason, but actually increases for teams who traded for a star player during the season. The reason for that could be that a full season, including a training camp, is required for a team to start playing well together. In the last two seasons there is a notable decrease in Win%, which generally reaches the level of the season before a star player joined the team. That should come to no suprize since only two thirds of acquired players are still with their teams in the third season and only half of them in the fourth season. However, if stars remain with teams for at least 4 seasons, winning percentage is on average just about +0.03 higher, which is almost negligible.

Now we will focus on performance of teams in playoffs, not on winning in regular seasons only. Using our data with 32 players and 39 transactions we will calculate probabilities that a team qualifies for the playoffs, reaches the 2nd round, conference finals, finals and wins NBA Championship after acquiring a player. We will also show theoretical “random” probabilities, which are based on the fact that every year 16 teams qualify for the playoffs, 8 of them reach the 2nd round, 4 of them conference finals etc.

chances_playoffs_qualify

The charts reveal that performance in playoffs after acquiring an NBA stars improves significantly. In the season before acquiring a star, teams performed slightly worse than the rest of the league on average. In season one, their performance improved significantly – only 23.1% didn’t qualify for the playoffs and 45.9% reached conference semifinals.

chances_playoffs_deeper

The season two results are quite comparable to the season one results, however the most, 13.5% of teams, win NBA championship in the second season after acquiring a star. In seasons 3 and 4, teams tend to be less successful. In the last season, the chances of success are actually comparable to the theoretical ones.

To answer our “research” question, we analyzed both performances of teams in regular seasons and playoffs. The performance improvements were less significant in regular seasons – on average, if we transform WIN% into nr. of wins, teams would improve their regular season record from 41-41 to 48-34 in the first season, to 46-36 in the second season and to 44-38 in the third season. We should note that 36% of teams actually had worse average records after acquiring a star in the four-season period. However, there was quite a significant difference in playoff success. The chance of winning the title in four seasons after acquiring a star was 2.24 times higher than theoretical, the chance of getting to the finals 2.17 times higher and the chance of advancing to conference finals 1.79 times higher. We can consequently conclude that acquiring NBA stars generally does lead to winning, but not for all teams. A portion of teams does not perform that well and can be, four years after FA star signings or trades, in a significantly worse situation than before. Some star players end up being one year “rentals” (Dwight Howard), some players get injured (Grant Hill), some soon retire (Steve Nash) and others are not as good fit as expected. In those cases, giving up assets and large chunks of salary cap can lead to losing and possibly to rebuild. But all in all, acquiring the best talent seems worth the risk!

Leave a Reply

Fill in your details below or click an icon to log in:

WordPress.com Logo

You are commenting using your WordPress.com account. Log Out /  Change )

Facebook photo

You are commenting using your Facebook account. Log Out /  Change )

Connecting to %s