Bootstrapping QoT/QoC and the Sedin Paradox

EP: Throughout this post, I’ll use “qualcomp” to describe both QoC and QoT because “QoC/QoT” is tiresome. 

Though we may not like to admit it, the hockey analytics collective has yet to crack the qualcomp code. The public sphere has yet to produce an agreed-upon method of weighing the impacts of QoT and QoC and the latter is sometimes dismissed outright. Traditionally, TOI-weighted averages are employed to determine the mean talent of teammates and opponents. The talent component may differ – 5v5 TOI% and Corsi being among the most common. On Corsica, three brands of qualcomp are offered: TOI%, CF% and xGF%. A wrinkle is that each teammate’s CF% or xGF% is calculated from the time they spent playing without the player in question. This ensures that the measured quality of a teammate is independent of the impact a player has on them. Despite this advantage, the methodology is imperfect. Namely, it introduces what I’ve come to label the Sedin paradox. Continue reading “Bootstrapping QoT/QoC and the Sedin Paradox”

The CoRsica Package for Hockey Analysis in R (0.2: Fundamentals)

EP: This is the third part in what I hope will become a lengthy and informative tutorial series on a pseudo-package I am building for R called coRsica. In this instalment, I’ll discuss some fundamentals of the R language and apply them to our Hello World script.

Review and More
In section 0.1 you were introduced to object classes, syntax rules, functions and some basic mathematical operators. There is still much more ground to cover when it comes to these fundamental concepts, so let’s do it right this time. Continue reading “The CoRsica Package for Hockey Analysis in R (0.2: Fundamentals)”

The CoRsica Package for Hockey Analysis in R (0.1: Hello World)

EP: This is the second part in what I hope will become a lengthy and informative tutorial series on a pseudo-package I am building for R called coRsica. In this instalment, I’ll discuss the RStudio console and some R basics, and show you how to write your first script.

Inside RStudio
In section 0.0 you installed R and RStudio onto your computer. Now, I’ll quickly show you around the RStudio interface so you can make sense of it! Continue reading “The CoRsica Package for Hockey Analysis in R (0.1: Hello World)”

The CoRsica Package for Hockey Analysis in R (0.0: An Introduction)

EP: This is the first part in what I hope will become a lengthy and informative tutorial series on a pseudo-package I am building for R called coRsica. In this instalment, I’ll discuss my intentions and teach you how to install R and RStudio on your machine.

I think hockey analytics is an endlessly interesting field. It pleases me to see and hear from so many others who’ve discovered the same sense of enjoyment from crunching hockey data that I have. My purpose in sharing this R package and tutorial series is to enhance people’s ability to conduct the research and analysis they want to, while learning a little about R in the process. Continue reading “The CoRsica Package for Hockey Analysis in R (0.0: An Introduction)”

Shot Quality and Expected Goals: Part 1.5

EP: This is the 1.5th instalment of the Shot Quality and Expected Goals series. Read the first part here.

I finished the first part of this series with a promise of certain things to follow in the next. Those things were delayed and eventually superseded by a pressing request I’ve heard echoed since the launch of the site. When WAR On Ice closed its doors, implementing scoring chance data became a top priority. Continue reading “Shot Quality and Expected Goals: Part 1.5”