NWHL – Ben Howell

Measuring Faceoff Skill in the PHF: Elo Ratings

Ben Howell — Wed, 17 Nov 2021 05:34:41 +0000

Coming from a non-hockey background, faceoffs are an aspect of hockey that I haven’t thought much about. However, a recent Mike Murphy (@DigDeepBSB) tweet inspired me to look at faceoffs a little closer.

Jillian Dempsey went 23-6 on faceoffs on Sunday against the Minnesota Whitecaps. Seems good.
— Mike Murphy (@DigDeepBSB) November 12, 2021

I don’t want to spoil my article on measuring faceoffs, but it turns out that Jillian Dempsey is really fricking good. You can check out the article below to read about my process and find the results from my methods. (You can also view the results in a more interactive visual format on this Shiny app).

PHF-Elo-Ratings

You can share your thoughts with me on Twitter @benhowell71 and let me know if you have questions about the project or the 2022 projections.

Aging Curves in Women’s Hockey: NWHL Edition

Ben Howell — Sun, 18 Jul 2021 21:49:14 +0000

At the 2021 WHKYHAC Conference, I presented research on exploring the aging curve in the NWHL. In addition, I put together a write-up of my analysis and work process, which you can find below. The code and data for this project can be found on my GitHub page.

If you’re just looking for the 2022 NWHL Game Score per Game projections that I talked about in my presentation, they are at the bottom of the below work.

NWHL-Aging-Curves

You can share your thoughts with me on Twitter @benhowell71 and let me know if you have questions about the project or the 2022 projections.

Measuring Passing Skill in the NWHL

Ben Howell — Sat, 05 Jun 2021 21:41:15 +0000

Using the data from the 2021 NWHL season that was made public for the Big Data Cup, I took at stab at quantifying passing skill in the NWHL using two types of measures. You can find the code for this project on my GitHub page and check out the the article below by clicking on the link below.

Measuring-Passing-Skill-in-the-NWHL

You can share your thoughts with me on Twitter @benhowell71 or you can reach out if you want to see different players featured in a CPOE distribution graphic!

How Do We Get There: Quantifying Pass Types and Their Value

Ben Howell — Fri, 05 Mar 2021 04:38:33 +0000

Below is my submission for the 2021 Big Data Cup, hosted by Stathletes. I focused on developing a framework for measuring the value of player shots and movements, including the actions that occur before a potential assist. I outline my process for developing Expected Attack Value (xAV) below and explore some trends among common pass types.

My submission placed second in the College Division of the Big Data Cup in 2021; you can find my video presentation on YouTube from when I presented it at the Ottawa Hockey Analytics Conference in March 2021.

You can find an accompanying R Shiny App (for an Interactive Movement% Plot and full xAV Leaderboard) here. The code and paper for this project are also located on my GitHub page.

Ben-Howell-Big-Data-Cup-Paper