Goaltenders are important, but volatile. How can statistical forecasts overcome considerable uncertainty in future performance? By embracing it. Why Project Performance? The first instinct upon seeing goaltending projections should be: why? Goaltending is a notoriously volatile position making little sense to those even with a deep understanding of the game. In any given season, both high-pedigree and also-rans goaltenders are seemingly as likely to deliver top performances. A perceived star having a poor season can sink a promising season. But that magnitude of impact makes it an interes ..read more

Are goaltender’s big-time playoff performances best explained by their regular season or historical playoff results? Can some goalies just turn it on when it counts more? Clutch Off the Bench The 2018 1st round series featuring the Columbus Blue Jackets and Washington Capitals was an interesting case study in playoff goaltending performance. Starring for Columbus was Sergei Bobrovsky. The reigning Vezina Trophy winner was coming off another very good season, hoping to continue rolling in the playoffs. However, despite Bobrovsky’s accolades he has never advanced past the 1st round and has ..read more

Goaltending tactics have evolved considerably in the last 30 years, confirmed by rising save percentages. The Reverse Vertical Horizontal (RVH) is a relatively new goaltender tactic, now widely-adopted. Is there a meaningful impact in the data? What is the RVH? Growing up almost every coach I had wanted me to stand-up ‘more’ – more being a relative term. Most made peace with the fact that I was going to try to make the same type of saves as Patrick Roy or Dominik Hasek but since I was still a kid, it would probably help if stood up once in a while. Still, they had to choose their battles wis ..read more

The Stanley Cup Playoffs magnifies all the frustrations people have with the goaltending position. Tough to predict and performances with an outsized impact on game outcomes, what can you expect over a playoff series? Playoffs, Pads, and Positional Paradoxes Goaltending is a volatile position. With so much out of the goaltender’s explicit control, it’s extremely difficult to consistently deliver positive results. This can be true over the course of a season, but it is especially true over the course of a playoff series. Generally starting goaltenders in the playoffs have had good seasons, so a ..read more

Expected Goals (xG) are a great tool for analyzing goaltender and skater performance, but it’s important to discuss limitations and opportunities for improvement. It’s Tough to Make Predictions, Especially About the Future When I projected goaltender performance for the 2017-18 season, Cam Talbot was probably going to have an above average season, even possibly a top 10 performance.  Comparing his ability to stop the puck relative to what we might expect his average peer (using expected goals), his track record has been good to very-good prior to this season, within a certain ..read more

Pictured: Dominik Hasek, who made 70 saves in a 1994 playoff game, beating the New Jersey Devils 1-0 in the 4th overtime. Hasek didn’t receive goal support for the equivalent of 2 full regulation games, but he won anyway. What is the probability of Hasek winning this game and what does it tell us about his contribution to winning? A Chance to Win I was lucky enough to attend (and later work at) the summer camps of Ian Clark, who went on to coach Luongo in Vancouver and most recently Bobrovsky in Columbus. Part of the instruction included diving into the mental side of the game. A simple mott ..read more

Pictured: Marc-Andre Fleury makes an amazing save at the end of game 7 to win the 2009 Stanley Cup, moments after giving up a rebound. Did he need to make this dramatic save? Should he be credited for it? Looking at the probability of a rebound on the original shot can help lend context. A few years ago I was a seasoned collegiate goaltender and a raw undergrad Economics major. This was a dangerous combination. When my save percentage fell from something that was frankly pretty good to below average, I turned to an overly theoretical model to help explain this slip in measured performan ..read more

Preamble: The following is a paper I wrote while in college about 6 years ago. It is very theoretical, without understanding the realities of data quality in the real world. However, it still reflects my general attitude toward how goaltending performance should be measured, manifesting itself in my current Expected Goals model.   How new metrics concerning hockey’s most important position can offer critical insights into goaltender performance, development, and value.   Introduction During the last 20 years, the goaltending position has changed more than any other position in h ..read more

All xG model code can be found on GitHub. Expected Goals (xG) Recipe If you’re reading this, you’re likely familiar with the idea behind expected goals (xG), whether from soccer analytics, early work done by Alan Ryder, Brian MacDonald, or current models by DTMAboutHeart and Asmean, Corsica, Moneypuck, or things I’ve put up on Twitter. Each model attempts to create a probability of each shot being a goal (xG) given the shot’s attributes like shot location, strength, shot type, preceding events, shooter skill, etc. There are also private companies supplementin ..read more

Preamble: The following is a paper I wrote while in college about 6 years ago. It is a slightly different approach and worse logic that I employ now, likely reflecting my attitude at the time – a collegiate goaltender with the illusion of control (hence goals were likely unpredictable events, else I would have stopped it). I have softened on this thinking, but still think the recommendation holds: goaltenders can outperform the average by mixing strategies and adding an element of unpredictability to their game.   How goaltender strategy and understanding randomness in hockey can len ..read more