This Thanksgiving, I ran the Commodore Hull Thanksgiving 5K in Shelton, CT while home for the holiday. My data from the race is found below. I placed 165/625 overall, and 38/75 in the Male 18-29 division with a time of 25:16.
TrialPay’s softball team, the Honey Badgers, began our season last Wednesday. In addition to playing, I’ve decided to make myself the team statistician. Drawing some inspiration from the JHU physics graduate student intramural softball team, I thought it would be fun to keep a running tabulation of players’ lifetime statistics. In order to keep it manageable and given that I’m also playing, I’ve limited myself to basic offensive and pitching statistics.
The box score from our first game can be found below the jump.
|TrialPay Honey Badgers||2||3||1||8||4||18||15||4|
Me and my coworkers recently had the draft for our fantasy football league. Although I’ve done many fantasy leagues in the past, this was my first time doing an auction draft. I left the draft room feeling pretty good about my team (the B-Sze Bees), but also excited about the possibilities for analysis. Given the finite bank roll of each player, the auction draft leaves a lot more room for someone to have a horrible (or amazing) draft, depending on how they allocate their resources.
Although its hard to decide who had a good or bad draft before the season is over, I did think it was worthwhile to look at the draft results and use them to determine what our league valued, based on spending habits. The first, and most obvious piece of analysis, was to look at how spending broke down by position, across all teams.