What’s up y’all! Been a while but it’s time for the second inaugural post, so fasten your seatbelts people – it’s gonna be bumpier than the Lakers from 2011 to 2017. Just kidding. That’s obviously impossible. So yeah, I guess just fasten your seatbelts for peace of mind sake cuz we all know how wild we can get looking at data.

In this post we’re going to attempt to determine whether or not fouls strongly affect a team’s wins or losses. In other words, do teams that foul more win MORE games, or rather, do more wins come to teams with fewer fouls over the course of the game?

To start, I had to choose a dataset that fit the purpose of my investigation. I chose to start with the 2014 NBA season as this was the season that marked the rise of the Golden State Warriors to prominence with them winning their first title since 1975. Our data ends with the last finished NBA season, 2017-18.

Why did I choose this year, you ask? I wanted to draw my correlations from the “modern” era of basketball, where 3-pointers reign and the game had drastically moved to pick-and-rolls, perimeter drives, and interchangeable positions, rather than post-ups, inside game, and 3-point specialists. In the future, however, I would love to do analysis on how the value of fouls have changed over time, so stay tuned.

The Process (Trust it):

Initially, I had a dataset that contained team stats from every single game played over the course of the 2014-2018 seasons. What I was looking for in the end was something that compared the total number of fouls of a team over those years to the total number of wins.


  1. Group the data by team
  2. Take the total team fouls per game and sum them to find the total number of team fouls over the chosen time period
  3. W-L was in the dataset as a string that contained “W” or “L” so perform a count of the “W” string to determine the total number of wins for a particular team
  4. Take our total wins and total fouls and plot them against each other

So here you go, let’s take a look at what we got!

As you can see, the points are fairly scattered, however there is a slight downward trend, which is actually what I expected to see. I figured teams with more wins would stray toward fouling less, but the correlation would not be strong and here’s why:

-Starting base level – in most games, yes it is better to foul as little as possible. Fouling in a basketball game not only gives your opponent free points, but also creates situations on defense in which your team cannot be as aggressive later in the game. This makes it harder to play defense and makes you lose more.

Why isn’t it steeper?

-We have to remember that we are correlating WINS with fouls, rather than DEFENSE with fouls. Essentially, we have eliminated half of the input that goes into a win or a loss.

-If you look at the outliers, the teams that win more AND foul more have terrific offenses. If you look at the graph, two teams that stand out are the Warriors and Rockets – both of them lie just above the trend line for fouling yet have the 1st and 3rd most wins over our timespan.

-The teams that win more and foul LESS, for example the Spurs and Cavaliers – are more defensive minded teams. They lie below the trend line for fouling but have the 2nd and 5th most wins over our timespan.

-If these teams all had the same offensive efficiency, I would be willing to bet that they would sit much more firmly on that trend line.

Conclusion: It is hard to tell if fouling more or less will definitively garner a team more wins or losses simply because we are omitting the offensive side of the ball. My assumption is that defensive efficiency increases when teams foul less, thus resulting in more wins – however there are still teams out there that get ‘carried’ by their offense, or dragged down by it in the W-L column. The next step is to determine whether defensive efficiency is strongly affected by total fouls, and then how much wins and losses are affected by defensive efficiency. This, and more to come in the next post!

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