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Data Analytics: Sports, Tech and Race

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“Data is like garbage, you’d better know what you are going to do with it, before you collect it” – Mark Twain

At Silicon Jungle, our team members are huge sports fans. The recent NBA finals were no different, we were all tuning in to see two of the greatest basketball players of our generation going at it, especially in the epic Game 7, then followed by the NBA draft by the end of the week. Both of these events in sports were filled with data analytics spouted from news casters, tweeted by Sports nerds, and closely followed by team executives. Data is consuming the sports world and it’s kind of awesome. To some extent, especially in baseball, the most analytical sport of them all, has only been improved by better data analytics. But wait. I am a millennial, there are a number of “old-heads” a.k.a curmudgeons who completely and emphatically disagree. That at times the use of data could be damaging are beloved sports discussion and roundtables. AND that people of color, especially black people, aren’t engaging in this new data phenomenon.

So about a month ago, famous sports reporter and personality, Michael Wilbon wrote an article that essentially said that Black people and data analytics don’t mix (Mission Impossible: African-Americans & analytics ) . He highlighted black athletes and black people in general who love and consume sports are rarely talking about data analytics in their free time, in their barbershops, etc. His article was met with a great deal of push back that the average fan, of any race, rarely engages in discussion of data analytics which is probably true. But I walked away from the article a little frustrated, because to some degree Wilbon’s bias against data analytics was very apparent, which to some extent lacked a full analysis of race and the use of data analytics. So we will attempt to do just a little of that here, but from our perspective in the tech world.

Let’s go over a few points that we know:

  • Data is good.
  • Monitoring metrics can improve processes and increase efficiency.
  • And more importantly, analytics never hurt anyone. (Well, except maybe the person who focused on them too much)

The point remains that regardless of whether there are a ton of sport fans using or discussing data.




(and if most sports fans don’t care) – the front offices do.

The front office, in the sports world, is increasingly turning to data, and if people don’t embrace it, then they will be left out of the front offices more likely than not, and with African Americans already struggling to fill coaching and executive positions, there is not really a reason to not embrace the shift. One person Wilbon did interview indicated that there are more than enough African Americans with the data analytics skill set or the love of numbers to fill spots in the front offices. And this is the point that brought me to the tech world, because there continues to be discussions about the lack of diversity in tech as well. Many tech executives like to blame it on the pipeline. That there aren’t enough black people coming through the pipeline which is why there is a lack of diversity in tech. But that’s not what they really mean, what they want to say is:

There aren’t enough black people with the right skills coming through the pipeline which is why there is a lack of diversity in tech.

Yes, I said it. No one says that exactly, but you cannot help but know that this is a huge contributor. There is a clear bias that the reason we are struggling to increase diversity people in certain places is a lack of skill, whether in the tech world, front offices in sports, or on Wall Street.

A former senior employee at Twitter, wrote a very telling piece about diversity called, “Thoughts on Diversity Part 2. Why Diversity is Difficult.” He said one of the lowest moments while at Twitter occurred when the Sr. VP of Engineering said, “diversity is important, but we can’t lower the bar.”


He goes on into more detail about some of his experiences when trying to hire qualified candidates:

“There were also the Hiring Committee meetings that became contentious when I advocated for diverse candidates. Candidates who were dinged for not being fast enough to solve problems, not having internships at ‘strong’ companies and who took too long to finish their degree. Only after hours of lobbying would they be hired. Needless to say, the majority of them performed well.”

Now see, THIS is why black people don’t like data. Twitter was obviously using a “data” set to rank candidates, and based on the blind metrics – supposedly race neutral, they were scoring people of color lower based on the criteria of a few things, yet, when selected they performed well. But see if there wasn’t a person of color at the table advocating for the persons of color then the few that were hired wouldn’t have been, all because of “data”.

I will say it again.

THIS is why people of color don’t like data . It has been used against us more than it has helped us (more evidence here) because data can completely ignore certain factors that affect a person of color or forget attributes such as emotion, instinct and tenacity which cannot be measured necessarily by the numbers. This doesn’t mean, however, that we can ignore data. This is the point that Wilbon fails to understand. We must use data to our advantage: applaud when it is useful and point out when it is being used to discriminate. We must be able to be at the table and willing and able to tell the story with data, and that story that is missing in between the lines. We must remind people that data doesn’t tell the whole story.

We cannot ignore data and we cannot ignore emotion, instinct and tenacity. And it does no use to anyone to have a discussion of one without the other in tech or in sports.

Share your thoughts below.


You can read more from Jackie-Monroe at

Also published on Medium.