How soon do you know when an NBA game is done?

Looking at play-by-play data of every game of every season between 2004-05 to 2015-16, I was able to determine at every second whether the team that is currently winning will win the game. I averaged every second of every game (regular and post-season) to come up with the following visualization:

I then averaged each minute to come up with this visualization:

The data can be download here.

NBA Shooting while Winning versus Losing

It has been hypothesized that younger players may shoot threes better when their team is winning [1]. To see if this is true at the NBA level, I analyzed every shot of every game from the 2004-05 to the 2015-16 seasons. I found no statistical difference when shooting threes while losing or winning. I found the same to be true of free throws, but I did find a difference (p=0.037) when shooting twos. Interestingly, when the team is losing, the average player shoots 46.28%, but when winning the average goes down to 45.78%. However, the effect size is d=0.03, which is small.

Here is a density map of the three-point shots, along with the analysis:

t = -0.80358, df = 11738, p-value = 0.4217
alternative hypothesis: true difference in means is not equal to 0
95 percent confidence interval:
-0.009613867 0.004023235
sample estimates:
mean of losing mean of winning
0.2918484 0.2946437

Here is a density map of the two-point shots, along with the analysis:

t = 2.0842, df = 15112, p-value = 0.03716
alternative hypothesis: true difference in means is not equal to 0
95 percent confidence interval:
0.0002954158 0.0096292267
sample estimates:
mean of losing mean of winning
0.4627997 0.4578374

Here is a density map of the free throws, along with the analysis:

t = 0.38493, df = 13994, p-value = 0.7003
alternative hypothesis: true difference in means is not equal to 0
95 percent confidence interval:
-0.004826125 0.007184844
sample estimates:
mean of losing mean of winning
0.7277869 0.7266075

The raw data can be download here.

[1] A. Glockner, Chasing perfection: a behind-the-scenes look at the high-stakes game of creating an NBA champion, First DaCapo Press edition. Boston, MA: Da Capo Press, 2016. p. 85

2014-2015 NBA Regular Season Team-Level Data Parallel Coordinate System

The following D3 visualization demonstrates a parallel coordinate system, which is useful for high-dimensional data. Try dragging and dropping the axes to rearrange the visualization.

The following paper provides an introduction to parallel coordinate systems:
Inselberg, A. (1997), “Multidimensional detective”, Information Visualization, 1997. Proceedings., IEEE Symposium on, pp. 100–107