A poorer than average, but not entirely out of the ordinary performance this week (given expected fluctuations): \(32/54 = 59.3%\). A slightly poorer performance might be expected on weeks like this - where a blockbuster deal completely changes part of the league: Apparently the Pistons are now unbeatable sans Josh Smith. Summary by point spread is at right. Week 10 predictions up.
This past week, we also finally managed to implement the automation of our dashboard data feed: Now, if you go to the dashboard after 6am PST, records will always be up to date, as will the upcoming games listings and predictions for these games. A caveat: As new data comes in , our daily-updated predictions on the dashboard can now differ slightly from those posted in our official, weekly listings — We put some by-hand effort into the weekly listings, so they’re “official”. Nevertheless, it’s the same algorithm being applied to obtain the Dashboard results. Automating our feed required using beautiful soup to do some scraping, as well as learning how to set up cron jobs — Thanks to J. Bergknoff for suggesting we look into the latter. Automation is a beautiful thing: With all the free time now opened up, we can start to consider other items on our wish list (eg, improving our predictions…)
Dustin got a B.S in Engineering Physics from the Colorado School of Mines (Golden, CO) before moving to UC Santa Barbara for graduate school. There he became interested in Soft Condensed Matter Physics and Polymer Physics, studying the interaction between single DNA molecules and salt ions. After a brief postdoc at UC San Diego studying the physics of bacterial growth, Dustin decided to move into the data science business for good - he is now a Quantitative Analyst at Google in Mountain View.