Houston Rockets: Four reasons why Moreyball analytics work for this team

Reason #1: The role of statistics in the world of analytics

Houston Rockets fans, let me lay some knowledge on you.  Inferential Statistics is the use of data from a population to make possible inferences or to evaluate that data over possibly a larger population. In Inferential Statistics, you tend to determine to fail or fail to reject a null hypothesis.

Wait..what?

A null hypothesis is basically a possible statement and one does a bunch of mathematics with numerical values called hypothesis testing to determine whether to reject the null (imply that the statement is not true) or to fail to reject the null (imply that the statement is neither true nor false).

But why never have a statement that is true?   In reality, hypothesis testing can only test whether a statement is ridiculously off target. If not ridiculously off, the statement can’t be disregarded, therefore it can’t be rejected.

Put in the simplest way possible, it’s the real world and anything can happen. Even if it’s missing 27 straight threes in Game 7 of the Western Conference Finals. I know for damn sure I didn’t see that coming. So once again, the only reason for this outcome is…

Because crap happens.

In statistics overall, you are taking numerical values simply to analyze and interpret a possible conclusion. And as you can tell, some conclusions can be highly inconclusive.

This is nowhere near the same function as analytics.

*Gasp*

Analytics is defined as the following…

“studying past historical data to research potential trends, to analyze the effects of certain decisions or events, or to evaluate the performance of a given tool or scenario. The goal of analytics is to improve the business by gaining knowledge which can be used to make improvements or changes.”- BusinessDictionary

While statistics makes an attempt to conclude a possible phenomenon, analytics does a statistical analysis to determine what needs to be done to improve whatever it is they’re testing.

Then they actually might take action.

Now from what I have explained to you, analytics seems much more impactful than statistics. That is not necessarily the case as they both have their pros and cons. But if there’s one common thing between analytics and statistics, it’s numbers.

Ironically, a number can also be hurtful in either field.

Don’t worry my dawgs. This article isn’t a complete math lesson. I’ll get to the interesting stuff sooner or later.