# Behind the Numbers: Where analytics and scouts get the draft wrong

Every once-in-a-while I will rant on the concepts and ideas behind what numbers suggest in a series called Behind the Numbers, as a tip of the hat to the website that brought me into hockey analytics: Behind the Net. My ramblings will look at the theory and philosophy behind analytics and their applications given what is already publicly known.

Hello everyone; I am back! I was in the process of writing an article on NHL prospect development for after the draft (teaser!) when a Twitter thread sparked my interest and made me want to do a bit of a ranty, very pseudo-Editorial or Literature Review on analytics and the draft while combing over that thread.

# Applied Prospect PipeLinE (APPLE): Assisting the analysis of hockey prospects using Recurrent Neural Networks

The NHL Draft acts as the proverbial reset of the NHL calendar. Teams re-evaluate the direction of their organizations, make roster decisions, and welcome a new crop of drafted prospect into the fold. Irrespective of pick position, each teamâ€™s goal is to select players most likely to play in the NHL and to sustain success. Most players arrive to the NHL in their early 20s, which leaves teams having to interpolate what a player will be 4-5 years out. This project attempts to address this difficult task of non-linear player projections. The goal is to build a model for NHL success/value using a playerâ€™s development â€” specifically using all current/historical scoring data to estimate the performance of a player in subsequent seasons and the possible leagues the player is expected to be in.

# Hockey Graphs Podcast Episode 17: Dump Trucks of Money

This week, Rhys and Garret ask if Mike Babcock is really worth his \$6+ million annual salary, look at Canada’s dominance on the world hockey stage, examine Tyler Johnson’s unlikely ascension from marginal junior player to NHL playoff hero, and of course do some good ol’ fashioned prospecting.

# Hockey Graphs Podcast Episode 15: Of Course We’re Talking Prospects (and Ep 14 too)

On this week’s episode, Rhys and GarretÂ go over some highlights of Corey Pronman’s Top 100 Prospects for the 2015 NHL Entry Draft.

# When the Trade Market and Draft Market intersect and how to exploit them

Image Courtesy of WikiMedia Commons

The biggest incentive for teams to employ analytics is exploiting market inefficiencies. Whenever you can exploit an inefficiency in a market it gives your team a comparative advantage over the others. In other words, you raise your team’s chances ofÂ being a successful club.

I took a look at previous work from Eric Tulsky and Michael Schuckers on draft pick value and used them to show how one may use statistical analysis to take advantage of market inefficiencies.

Let’s take a look.

# HOCKEY GRAPHS PODCAST EPISODE 12: SBISA MONEY

On this week’s episode, Rhys and Garret talk about the final playoff stretch drive, the Vancouver Canucks signing Derek Dorsett and Luca Sbisa, and the Central Scouting final rankings.

# HOCKEY GRAPHS PODCAST EPISODE 10: GOALIES ARE VOODOO

On this week’s episode, Rhys and Garret talk about Michael Hutchinson’s recent struggles, Jacob Markstrom’s inability to make the NHL transition, the Canucks signing of prospect Ben Hutton, Corey Pronman’s trolling of Rhys, and some Alberta Major Bantam talk to top it all off. Join us on the other side of the break to listen!

# The Hockey Graphs Podcast: Episode 1

Welcome to the inauguralÂ episode of the Hockey Graphs podcast, where Rhys Jessop (of Canucks Army and That’s Offside)Â and Garret Hohl navigate the wonderful world of podcasting for the first time ever. Join us as we discuss Vancouver Canucks and Winnipeg Jets prospects, what the hell is up with the Anaheim Ducks, and, of course, a healthy dose of fancystats. Continue reading

# Draft & Develop: How analytics can be combined with qualitative scouting

The graph above represents how some mayÂ look at and use hockey statistics; the better a player performs in a statistic equates to more skill. This practiceÂ can be found in league equivalencies -now more commonly known as NHL equivalencies (or NHLe)- originally contrived hereÂ by Gabriel Desjardins.

In truth, almost all of us can be guilty of this at one point or another, like whenÂ using evidence like “Player A has a better Corsi%; therefore, he is pushes the play better”. Most reasonably understand that this is not how it works, but it is not discussed often enough. These tools are used to show average expected outcomes. The output is not the only possible outcome.Â  Continue reading