Minnesota Wild: Dissecting Their Goaltending Catastrophe

So far through the 2014-2015 season, the Minnesota Wild have been struggling to move up the Western Conference standings. As many have noted, this is because of their atrocious goaltending thus far. As the 2014 calendar year comes to a close, and over a third of the season has been played, I felt it was a good time to dive deeper into the Wild’s goaltending problems. Being a Wild supporter since my early childhood, I really wanted to look at a specific team in my analyses. So look for more Wild-based posts in the future, but for now, let me take a look at their current issue: goaltending.

Throughout the season, the Wild have been a very “analytics-saavy” team, posting surprisingly high possession numbers (Corsi and Fenwick) compared to their past seasons. The table here shows their Corsi number thus far at all manpower situations:


For the remainder of the post, I am referring to numbers during all situations (EV, PP, SH, etc.), giving a larger pool of data to work with, while also revealing some possible special teams issues that can be looked at in the future. These numbers here show that the Wild have been a very good possession team thus far; top 5 in the league in fact. However, they are struggling to win games, and becoming Corsi’s biggest nightmare. Those who support Corsi will have to look elsewhere to determine why they are struggling so much. For me, I think it can be shown by a single number: PDO. A team’s PDO is the sum of their shooting percentage and their save percentage. Throughout the “analytics era,” it has been shown that the PDO often regresses towards 100 over the long-term and “high” (102 and greater) and “low” (less than 98) are unsustainable and often times can be attributed to puck luck.


The PDO for the Wild is awful. They rank in the bottom 5 in the league in PDO, but this is only one number and the underlying cause is not always so clear. A PDO number can be explained by a few different factors. One could be luck (or “unluck”), but that is not very measurable, for me anyways. Seeing that their shooting percentage is not too bad (14th ranked), there is one other explanation that seems reasonable here: bad goaltending. The Wild rank 27th in the league in save percentage in all situations, which is terrible if they want to compete in the West. What makes this situation even worse is that the Wild allow the fewest shots on goal in the league! This means that they are constantly outshooting their opponents and limiting shots against, yet are receiving bad goaltending in the last line of defence. Here are Minnesota’s shooting numbers for the season thus far (in all situations):


By constantly outshooting opponents while getting terrible goaltending, the Wild are not as bad when it comes to goals for, ranking 16th in the league as they get 51.1% of goals. Now I know that straight up save percentage is not a perfect indicator of goalie performance or strength, especially in all situations, which is why measures of “shot quality” must be examined in order to get a better idea of how the goalies are truly performing.

The following chart compares the Wild’s save percentage to the league average based on shot distance. This data is broken down into four blocks, as seen. The Wild are below the league average in each of these categories. This means they allow more goals, on average, than the league from any spot on the ice. We knew that, based on their save percentage, but what is revealing here is that they come in at least 3 percentage points below the league average from the closer ranges (<10 feet, 10-20 feet, and 20-30 feet). The Wild goalies are struggling with shots of “higher” quality and this is definitely a telling point.


Some of these numbers can be a little skewed, as distance only measures one aspect of the shot. It does not necessarily consider the location relative to the net, and therefore may not be a totally dangerous shot. That is why scoring chances must be evaluated as well. However, the numbers for Minnesota do not get much better. Their save percentage on “scoring chance” shots, those in the area shown in the picture below, is over 4% lower than the league average as you can see. This goaltending problem just keeps take more turns for the worse, revealing that the Wild net-minders are simply not getting it done compared to the league average and what it takes to win (especially in the potent Western Conference).

Minnesota Wild Shots Against- Scoring Chances
Minnesota Wild Shots Against- Scoring Chances


However, what may be a good sign for the Wild is that they typically do not allow as many shots from the scoring chance area, or from closest proximity for that matter, than the league average. Looking in the scoring chance table above, 39.41% of all shots against Minnesota are scoring chances, while for the entire league that number equates to 44.43%. This is also present in the table below, where about 42% of shots against the Wild come from within 30 feet, while for the entire league about 47% of shots come from within this distance. For the Wild, as a team, this can be a boost as it shows that they are limiting the “high-quality” shots, forcing teams into lower quality shots that should come with an associated higher save percentage. However, their save percentage is not lower and this has shown to be a problem for the Wild thus far.

Looking at a goaltending situation can be tough; a low save percentage can come as a result of poor goaltending, a bad defensive system, or simply luck. Trying to decipher the numbers can only get you so far in your analysis, and watching the games will lead to a better understanding of what is going on. For the future, I may look at analyzing the Wild’s individual goalies and their numbers to try to determine the root of the problem. Another area to consider is the idea of shot quality. One method is never truly “perfect,” especially when looking at shot quality. I have recently learned this after reading Rob Vollman’s Hockey Abstract chapter on the matter; there are simply too many factors that go into shot quality, such as location, rebounds, manpower situation, and game score, that it is difficult to determine one “good” measure.”

Also, Hockey Analysis has looked at rush shots and their effect on save percentage over time. You can read their article here to look at how they define rush shots and possibilities about how to use this data. They also have more recent articles that apply the concept and look to compare numbers across teams and seasons.

Stats retrieved from war-on-ice.com, stats.hockeyanalysis.com, and the Super Shot Search feature on somekindofninja.com


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