Baby Analytics

For those that have been missing my posts, you probably don't know that my wife and I welcomed a son into our family earlier this year. Unfortunately, sleep deprivation kept me from being able to code (and think) effectively. I did end up with some new data though. For those without newborns, you might not be aware that parents are recommended to keep track of their baby in a notebook (or phone app) for the first few months of their life. This data comprises how much our son eats, when he has a diaper change, what his temperature is, etc.

Using this data, I thought it might be interesting to see if we could perform some analytics. Here's a list of problems I'm looking to tackle:

• Can you predict growth spurts with this data?
• Can you detect abnormal or just a change in behavior from this data?

It's going to take me a month or so to enter the data into a spreadsheet, but once it's up I'll put together another post with some visualization of that data.

ThinkUp: Personal Twitter Analytics

As a fan of various TWiT.TV shows, I learned about a website that will analyze your Twitter account. Given my curiosity around social media analytics, I figured I'd give it a shot. Although I'm not the most active Twitter user, I was curious what it could tell me and what they thought other people would be interested in.

Their analysis seems to be split into a few categories:

• Analysis of your tweet contents
• Analysis of responses to your tweet
• Analysis of your friends and followers profiles

Overall, it's pretty interesting. It helps me manage my "brand" as it comes across on Twitter. For example, I can make sure I vary the content of my tweets and not just talk about myself in the majority of tweets. I also enjoy knowing what times I should tweet in order to get the best response.

Being the curious analytics person I am, there are a few other facts / insights I would like to see:

• When are my followers most active?
• Who else should I follow? 
• What is the general sentiment of my tweets?

You can view my ThinkUp page for a nice example, although there are some better ones out there.  

Similar Players in MLB

It's a common question to compare baseball players against each other. The question is what do you actually compare? Their playing styles? Positions they played? Teams they played for? Eras they played in? There are several dimensions to which this problem's complexity increases dramatically. In fact, several people now try to compare Yasiel Puig against Mike Trout (like Mark Saxon). However, how would you compare them?

I'm interested in developing an analytical technique that will remove the manual labor of looking at statistics. By removing that tedious task, it would be interesting to see how player's careers compare against other player careers. I'm hoping that in the end, I can use this as a significant factor in being able to predict whether a player will end up in the Hall of Fame.

More to come on this topic, but here's a little tease:

• Data sourced from Sean Lahman
• Techniques include: 
• Dynamic Programming 
• Social Network Analysis 
• Logistic Regression 
• Programmed entirely in R and RStudio