Data Analytics and The 1995-1996 Chicago Bulls

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:

  1.  Ensure Ron Harper had a FG% less than 44.95% in a game,
  2. Ensure Dennis Rodman would have less than 17 total rebounds in a game,
  3. Ensure Luc Longley had less than 2 blocks in a game,
  4. 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:

We see that a key feature of the Bulls’ quality of play depends on how efficient Ron Harper in terms of his FG%.

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.

Data Analytics and The Raptors 2015 Loss

          Based on several internal statistical models that my colleagues and I developed, we all have concluded that the Raptors losing the way they did in the first round was somewhat of a statistical anomaly. Through an extensive analysis, I present evidence below that shows it was due to several coaching breakdowns in strategy that lead to the Raptors’ collapse. 

Optimal preparedness would have been to prepare and utilize an extensive analysis of the Washington Wizards’ style of play. Using advanced machine learning techniques, we generated two results, first based on tree boosting, and the other based on classification trees that found the weak points in the Wizards’ system that would have greatly helped the Raptors in this series. 

First, one should be interested in the most important commonalities and characteristics in the Wizards’ play. This result is as follows:

  
One can immediately see that out of several factors, the two most important factors in determining whether the Wizards will win or lose a game is their team FG% and the number of points their opponent score in a game. From this analysis, we obtain that to beat the Wizards, the Raptors should have focused on particularly strong interior defense, and in particular, stopping penetration. From an offensive point of view, the Raptors should have played a strong and slow half-court game focused on getting close-to-the-basket, high-percentage shots, instead of “high-octane” running up and down the court as they seemed to do very frequently. 

Going deeper in this analysis, one also has as a result the following classification tree:

  
In this tree, “W” and “L” denote whether the Wizards will win or lose a game, “FG.” denotes the Wizards’ FG%,  “OFG.%” denotes the Raptors’ field goal percentage, and “OPTS” denotes the number of points in a game the Raptors should score. One sees that for the Wizards to lose games, the coaching strategy should have been designed to ensure that the Wizards would shoot below 45.25%, while the Raptors should have shot at least 40.3% each game. Complementary to the above analysis, one notes that since three point shots are not fundamental to the Wizards’ offense, to accomplish this, the Raptors should have had strong half-court defensive schemes (including traps and trapping zones), combined with slow-paced, interior offensive schemes. 

In conclusion, it is important to note that these analytical results and ideas were available well in advance of the NBA playoffs, and the Raptors would have tremendously benefited from using these ideas. I would also like to point out that I have only offered a preview of the results I obtained. I have also developed several results pertaining to optimal offensive and defensive schemes that would not only change the way the Raptors play, but would make them significantly better.