It is without question that the greatest team in NBA history was the 1995-1996 Chicago Bulls. They went 72-10 that year and went on to win the NBA Championship against a top-notch Seattle Supersonics team.
Phil Jackson’s system and first-class coaching were the major reasons why the Bulls were so good, but I wanted to analyze their reason for winning using data science methodologies.
The results that I found were very interesting. First, I mined through each individual game’s data to obtain patterns in the Bulls wins and losses, and this is what I found:
One sees that the Bulls were a defensive nightmare, and if you look at these results in detail, it makes sense that the Sonics were really the only team that ever posed a threat to them. This shows that to beat the Bulls, the opposing team would have to simultaneously:
- Ensure Ron Harper had a FG% less than 44.95% in a game,
- Ensure Dennis Rodman would have less than 17 total rebounds in a game,
- Ensure Luc Longley had less than 2 blocks in a game,
- Ensure Michael Jordan had a FG% less than 46.55% in a game.
If any one of these conditions were not met, the Bulls would win!
This analysis on some level also dispels the notion espoused by several sports analysts like Skip Bayless of ESPN who continually claim that the Bulls’ sole reason for success was Michael Jordan. Ron Harper’s contributions although of paramount importance are rarely mentioned nowadays.
This analysis also shows that the key to the success of the Bulls was not necessarily the number of points that Jordan scored, but the incredible efficiency with which he scored them.
A boosting algorithm also allows us to deduce the most important characteristics in the Bulls’ quality of play and whether they would win or lose a game. The results are as follows:
It is quite interesting that this analysis shows that winning a championship is not about one player, sure, every team needs great players, but the Bulls were a great team, consisting of many great components working together.