Shooting and Save Percentages
Everything we've covered so far is shot-based, which is largely the direction hockey analytics has been going lately. Of course, not all shots go in at the same rate, which brings us to PDO.
PDO doesn't actually stand for anything, it's the internet handle of a blog commenter that first suggested the idea of adding together a team's shooting and save percentages together. As such, PDO should usually be pretty close to 1000. The Los Angeles Kings, for example, had a shooting percentage of 9.2%, and a save percentage of .907, which totals 999 when added together. More recently a variation called Shooting Percentage Differential has been used, which is the same thing, but uses the shooting percentage of both teams, with one being subtracted from the other.
These statistics are helpful because teams with PDOs that stray particularly far from 1000 tend to correct themselves in relatively short order. The Maple Leafs, for example, had a team PDO of 1036 last year, the highest in the league, while Florida was dead last with 969. This indicates the potential change in fortunes of these two teams in 2013-14.
Naturally PDO has also been used for individual players as well. It is measured by examining the team's PDO only when that player is on the ice, and generally only in five-on-five manpower situations. A player with an unusually high PDO, like Chris Kunitz (1074) or Nazem Kadri (1063), will generally exceptional scoring and plus/minus statistics, while those whose PDO is unusually low, like Drew Shore (938), Olli Jokinen (939) and Jeff Skinner (940) will likely be seen as disappointments. However, PDO still has somewhat of a corrective factor, even for players.
The unpredictability of shooting and save percentages is another reason why statistical hockey analysts lean towards shot-based data. Even in the case of a player's offensive production, there's a clear preference for looking at the number of shots and passes a player attempts, rather than goals and assists. Since passes (that result in shots) aren't official recorded by the NHL, they're usually just estimates based on a player's primary assists and team on-ice shooting percentage.
Other Statistics
Just to touch briefly on goal-based data, ESP/60 is one of the more popular such statistics. It is a player's even-strength scoring rate over 60 minutes. For top-line forwards, for instance, it should be at least 1.7.
Some analysts also like to use all-in-one, catch-all statistics to get a preliminary overview of a team or a player before diving in for a deeper analysis. Others analysts, on the other hand, get almost blind with rage when estimates of any kind are employed.
Of those that make use of such metrics, including ESPN and teams like the Edmonton Oilers, Goals Versus Threshold (GVT) is the most popular. It measures all of a player's contributions, whether they're offensive, defensive, or in the shoot-out, relative to what you'd expect from an AHL-level call-up. The very similar Goals Versus Salary (GVS) is essentially the same thing, but measured relative to a player's cap hit instead.
One additional goal-based estimate of note is NHLe, which is the NHL equivalent of scoring data from another league, like in Europe, U.S. College for the Canadian Major Juniors. It is calculated by multiplying a player's scoring totals from another league by a translation factor that's based on those who previously moved from that league to the NHL. Various factors, including age for example, can also be taken into account. It's a nifty way to get a good idea of what to expect from a player coming to the NHL.
Goaltending
What about goalies? We'll be covering goaltenders in more detail in an upcoming issue, but briefly they're typically judged exclusively by their even-strength save percentage. It's not entirely helpful to include special teams play, since how many penalties a team takes and how effectively they kill penalties is largely outside a goaltender's control. These are also awfully small sample sizes, relative to five-on-five situations.
The only other popular goalie statistic is Quality Starts. Borrowed from baseball, it's meant to replace wins as an estimate of when a goalie players well enough for his team to win, independent of their offense, or how many shots they allow. More on that next time.
Team CGF%
Los Angeles 57.4%
Chicago 55.8%
New Jersey 55.0%
Boston 54.4%
Detroit 53.9%
St. Louis 53.9%
NY Rangers 53.9%
Montreal 53.6%
San Jose 52.4%
Ottawa 52.1%
NY Islanders 52.0%
Vancouver 51.7%
Carolina 51.1%
Phoenix 50.2%
Pittsburgh 49.9%
Team CGF%
Winnipeg 49.7%
Florida 49.0%
Minnesota 48.7%
Philadelphia 48.5%
Calgary 48.2%
Anaheim 48.2%
Washington 47.7%
Dallas 47.3%
Colorado 46.7%
Nashville 45.9%
Columbus 45.4%
Tampa Bay 45.0%
Edmonton 44.5%
Toronto 44.0%
Buffalo 43.7%