Digging into the World of Advanced Statistics
Now that we’ve covered the basics of hockey and some common lineup construction philosophies, it’s time to dig into the new world of advanced hockey stats. The goal of these advanced stats is to more accurately predict future performance, and that just so happens to be the exact goal of all DFS hockey players.
Goals are rare. Players may get robbed by an incredible save. A forward could weave through the defense with precision, deke the goaltender out of position, feed the puck to his open teammate and inevitably receive zero fantasy points when his teammate misses a wide-open net. These are just examples, but it does highlight the fact that there’s underlying factors that could have major effects on a player’s end-of-season stats.
Sabermetrics have become commonplace in baseball research, but the same type of advanced stats for the NHL are still in their infancy. While they may be new and evolving, they are also proving do exactly what they were created for; act as better indicators of future performance. Below, I will touch on several key advanced stats that you should incorporate into your research.
Corsi/Fenwick
Advanced analytics seemingly began with the introduction of both Corsi and Fenwick systems. While slightly different, these two advanced metrics are very similar and can be treated equally (Fenwick does not count blocked shots). The premise of these two metrics is to determine how many shot ATTEMPTS a player is responsible in creating (or surrendering).
The premise here is that a shot that misses just inches wide or rings off of the goal post won’t show up anywhere in the box score, but it should be considered when predicting a player’s future offensive potential. While there are tons of different stats to consider related to Fenwick/Corsi, my favorite one is CF/60 and it can be analyzed both at the team and individual levels. The higher the CF/60 (Corsi For per 60 minutes) for a player or team, the more offensively aggressive they’ve been in the past.
Pace of Play
Just like NBA DFS players like to target games that figure to be up-tempo in pace, the same principal can be applied to hockey. Some teams love to push the pace and get up-and-down the ice, while others do their best to slow the game down and clog up the neutral zone. Luckily, using some corsi stats listed above, we can easily see which teams fall into which categories.
The first stat to be familiar with is CP60. This is simply the number of Corsi events (a shot attempt) a team both creates and allows in 60 minutes. The higher this number, the more the team is pushing the action. The other relevant stat is CF60. Unlike CP60, CF60 is simply calculating how many Corsi events a team is creating per 60 minutes.
PDO
The most easily quantifiable of all the advanced metrics, PDO is designed to determine if a player has been either lucky or unlucky in previous contests. If you’re familiar with sabermetrics, PDO likely most accurately correlates to BABIP. Simply put, PDO is just the sum of a players shooting percentage as well as his team’s save percentage while he’s on the ice. Therefore, 100% is the baseline. A player with a PDO greater than 100 has presumably been a bit lucky, while a player with a PDO under 100 has been a victim of poor “puck luck”.
High-Danger
Not all shots are created equally, and high-danger stats incorporate this philosophy. When a player (or team) unloads a shot from within the face-off circles, it has a significantly higher chance of finding the back of the net than a wrist shot from the point. A player receiving an abundance of high-danger scoring chances is, at the very least, consistently putting himself in advantageous positions. The two most relevant metrics to analyze here are high-danger scoring chances and high-danger shooting percentage. Obviously, the more scoring chances the better and a low shooting percentage is typically signaling some misfortune rather than a poor skill set.