Tag Archives: analysis

Data Analysis of USAToday’s NFL Arrest database: 15 Surprising Insights

As soon as I learned that USA Today had released on open database of NFL player arrests (2000 to present), the data scientist in me thought, “I imagine there are some interesting patterns in there.” Rather than wondering, I downloaded it and dived right in.

The arrest data is easily readable, but lacks some important items (such as the age of the player at the time of arrest). As such, I decided to mash-up the data with two other sources: DOB, Height and Weight data from NFL.com and the strength and speed data from the NFL Combine. This would let me explore some of the more interesting (and potentially controversial) claims I heard in many TV interviews about the effect of increases in player size and strength had on aggression and crime.

My findings

Here are my findings from analyzing the data:

  1. Arrest frequency is NOT increasing. It is actually down from a really bad spate from 2006-2008
  2. NFL players, in general, have a one-third less likelihood of being arrested than everyday US residents. They have 15x the median US income and 3x the college graduation rate.
  3. However, many of those who are arrested are arrested many times throughout their career. 124 people were arrested more than once. One player was arrested 9 times. Sixty-five arrests were for multiple counts, across multiple criminal charges.
  4. Guilty verdicts (conviction, plea, or plea agreement) are the most common legal outcome. They occur almost 7x more frequently than Acquittals
  5. Nevertheless the most common action taken by NFL teams in response to arrests is “No Response.” This occurs 84% of the time
  6. Two-thirds of arrests occur off-season. However over 99% are arrest of players under contract. Free agent arrests are rare (although all of them later signed onto teams)
  7. Three teams (Minnesota, Cincinnati and Denver) have seen double the “normal” number of arrests per team
  8. Four criminal charges (DUI, Drugs, Domestic Violence and Assault) represent 60% of all arrests.
  9. Six charges (DUI, Drugs, Domestic Violence, Assault, Gun Charges and Disorderly Conduct) represent 80% of all arrests. Each of these has a single team with more arrests than any other.
  10. Of the most frequent charges, conviction rate varied enormously. DUIs had the highest conviction rate; Domestic Violence the lowest. While Domestic Violence pleas + convictions outcomes outnumbered acquittals 10:1, the vast majority of these cases were dropped or resolved in Diversion Programs
  11. The median arrested NFL player is: 25 years, 6 months old; is 6’2” tall, weighs 230 lbs., can run the 40-yd dash in 4.61 seconds and can bench press 225 lbs. 21times.
  12. While 88% of the arrests were of players under 30, age was not a factor (in arrest or criminal charge). The distribution of age at time of arrest virtually matched the distribution of ages across the NFL.
  13. There has been much talk in the media about the size of players and the potential impact on aggression. However, contrary to the opinions, neither height nor weight was a factor in likelihood of arrest or type of criminal charge.
  14. Unsurprisingly,  player speed was not a factor as well.
  15. However, analysis of player strength did show a pattern–not one about the strongest players, but about the least-strong. players It turns out those arrested for Sexual Assault stood out as the group with the lowest distribution of strength scores in the NFL Combine.

The data

  • 730 arrests between 2000 and the present (the database actually expanded by one entry a few days after launch to account for the arrest of Jonathan Dwyer)
  • These 730 arrests spanned 544 players (more on that below). Of these 544 players, 330 had publicly-available NFL Combine results
  • The arrests spanned 51 separate criminal charges (with some interesting concentrations, see below)

Sankey NFL Arrest “Flow”

The diagram at the top of this post is called a Sankey Diagram. This allows exploration of which teams had players arrested for each type of criminal charge then what were the distribution of outcomes for these charges. You can explore this chart, for all teams and all criminal charges in full at this page.

Deeper Dive

Sankeys allow exploration of broad pattern (such as which teams have the most Domestic Violence arrests) and interesting outliers (e.g., which team had a player arrested for Pimping; and what was the result). However, they do not make it easy to explore other dimensions of this data. The rest of this post takes a deeper dive into the data, exploring each of the 15 findings with different summaries and visualizations.

   Next: Arrest Frequency (and who was arrested nine times)

Decisions, Decisions… Android, iOS, Windows 8 or HTML5?

Article first published as Decisions, Decisions… Android, iOS, Windows 8 or HTML5? on Technorati.

The last month has introduced much new food for thought if you are trying to decide which mobile platform to build on first:

It has definitely been an eventful pre-Holiday Season in mobile.

Which Platform To Build On First?

With all these different metrics and shifts in leadership, which platform do you pick? The market share leader (Android)? The eCommerce leader (iOS)? The one most familiar to enterprise (Windows)? The one most open of all (HTML5)?

If you are Fortune-500 company with a big mobile budget the decision is easy: build on several. If you are smaller, you probably can only build one or two at most (or at least one to start on first). Which one do pick? The answer is actually simple—if you ask two key questions about your intended user base.

Question 1: What is the (Intended) Usage Pattern of Your Customers?

Notice that this question does not ask, “What is the Intended Usage Pattern for Your App?” Why? Because sometimes building an app is the wrong thing to do.

Apps are really fun to build. However, they require a lot from your customers. First they have to find the app. Then they have download and install it. Then remember to open up and use it. That’s a long chain of dependencies required for success.

If your customers use your product regularly—and this use is transactional or highly interactive in nature—then build an app. Open Table is a great example: I book dinner reservations several times a month, on the spur of the moment. It is much easier to do from an app, especially one that needs to interact with other Apps on my device (i.e., calendar, telephone, maps).

However, if your customers only use your services intermittently, don’t waste (their and your) time and effort with an App. Instead, use HTML5 to make your site work really well on mobile. The same is true if your customers only consume content from one source. There is no need to download an App to read a news site. As the Financial Times has shown, HTML5 is much better for this.

Question 2: If You ARE Building an App, What Are Your Customer Demographics?

If an App is the right thing for your customers, then you are really lucky: you get to pick from a great set of mobile platforms. The question now is which platform best suits your needs.

Whereas back end technologies are hidden from customers (allowing the freedom to pick based purely on technical considerations), mobile platforms are virtually “joined to the hips” of your customers. Picking a platform that your customers do not widely use will not provide the results you want—no matter how great the platform and app is.

To avoid this problem, pick the platform that best fits the demographics of your customer base. If you are building for gamers, build on Android (do the same if you are building for users in Emerging Markets). If you are building for doctors, build on Apple (do the same if you are building for high-end commerce). If you are building for internal enterprise IT use, Windows 8 or BlackBerry 10 may be your answer.

There are many ways to find out what platform you customers use most: industry analyst reports, Xyologic stats, or even your website’s Traffic by Operating System in Google Analytics. As long as you pay more attention to these metrics than the latest attention-grabbing mass mobile headlines, you will be using the right technology for your customers.