Now that Bryce Harper has officially signed with the Philadelphia Phillies on a 13 year, $330M megadeal, it’s interesting to conduct a retrospective look at the different offers he had on the table when making his decision. There has been a lot of publicity in recent hours about the amount of deferred money which the Nationals including in their “10 year, $300M offer”, especially compared to the Phillies deal which included no deferred money at all and also pays a $20M signing bonus. Furthermore, there’s even news that the Giants and Dodgers tried to splash the pot at the end with interesting offers of their own.

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One of my favorite posts from last year was about NBA Rim Protection. In that post, I created a statistic sitting on top of other rim defense statistics called RIMD. While you can check out the old post for additional detail on the statistic itself the bottom line is that RIMD is a weighted efficiency statistic that seeks to measure how effectively players can defend shots at the rim. The stat is designed to give preference to those who effectively contest a large volume of shots each game (DFGA) while holding shooters to a lower shooting percentage on those shots than their season average (DIFF%).

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If you haven’t heard of it before, the Big Mac Index is a heuristic invented by The Economist to estimate purchasing power parity across economies. Looking past the numbers-to-numbers layer of exchange rates, the Big Mac Index is focused on measuring the cost of a single, standardized item (voila, the Big Mac!) across countries, and examining where the burger is relatively expensive and inexpensive compared to the rest of the world.

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No real story here - just wanted to make some fun airline maps! The graphics you’ll see below were created by mapping hub airports for each major US air carrier and then showing flight traffic to and from all other major flight hubs. Cities are sized by the relative passenger volume of all connecting flights through that destination.

I’ve (tried to) follow each airline’s brand guides for color and styling on each map. Some, like American and Virgin, turned out great, while other color palettes like United and Southwest didn’t map as well to a two-color format… 🤷‍♂️

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One of the most enjoyable plotlines of the 2018-2019 NBA season has been James Harden’s transformation into a one man wrecking crew, capable of guiding a surging Rockets team up the standings in the West despite losing virtually every other “name brand” contributor on the Rockets roster.

Minus Chris Paul (out since 12/20/2018), Eric Gordon (12/29/2018), and Clint Capela (1/13/2018), Harden is putting up statistics not seen since Wilt Chamberlain - over the past week of play, Harden has put up a truly insane 58/6/8 line, and has averaged close to or over 40 points for more than a month of play. While the Rockets looked a bit washed out of the gate this season (Carmelo wasn’t exactly helping), they are surging up the tight Western Conference standings, mostly due to the excellence of one man. Let’s take a peek at some visuals that can help show just how special Harden has been over the last month or so of basketball!

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Vision

This fall I moved into a new house, which I quickly learned has an extremely unreliable thermostat. As someone who likes to be cool in the evening for bedtime, but also doesn’t love wearing sweaters indoors, I wondered if there might be a better way of monitoring my house’s temperature.

Fortunately for me, I had a surplus Raspberry Pi lying around, which I quickly determined could be leveraged into serving as the brains of my thermostat, given the right input sensors. Plus, the Pi easily connects to the AWS IoT interface, which would allow me to transmit data to AWS and then process and save that data in a variety of locations for analysis.

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Background

One of my favorite things in the world (except for one particular night this March) is watching my Virginia Cavaliers play basketball. I’m particularly excited about this year’s team, which I think is one of the deepest in recent memory and is going to be highly motivated all season coming off of last year’s disappointing finish against UMBC. I’ll leave the detailed analysis of their performance to the professionals over at Streaking the Lawn, but wanted to share a bit of work I put together on our most important returning players.

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Background

One of the most frustrating aspects of the Trump administration is the lack of honesty around simple things, from President Trump’s White House visitor log to his golf outings. However, thanks to the work of Factbase, there does exist a fairly comprehensive database of the President’s public schedule, which outlines his activities in the White House and his domestic and international travel.

To see what data and trends we might be able to glean from this information, I ingested the entirety of President Trump’s public calendar and press pool schedule, and built a series of visualizations highlighting what I felt were the notable trends. Note that exact while exact amounts may be imprecise due to how Factbase’s data is collected, many of the trends are clear and meaningful. Please see my key takeaways below!

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Now that we’re a few weeks into the NBA season, it’s fun to see who is having note-worthy starts to the year. The chart above shows the top twenty scores in the league by game and their gain/decline relative to last season. It’s fun to see players like Kemba Walker and Zach LaVine elevating their games amongst the league elite thus far this year, and will be intersting to see if they can continue to keep pace with the likes of Curry, Durant, and Lillard.

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Background

If you’re a fan of the National Football League, so far this season you’ve heard an uninterrupted string of commentary surrounding penalties, rule changes, and the role of violence in the game. This is a fascinating topic because a number of greater trends have coincided to cause this moment - particularly the NFL’s desire to protect quarterbacks, rule changes that have reduced the amount of practice time teams have during the offseason and between games, and game-calling decisions designed to encourage passing and free up downfield receivers. Put together, these factors have led to a slow inflation in the number of penalties called per NFL game, which is now reaching a tipping point.

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