I truly, dearly, deeply try to avoid discussing Ondrej Pavelec… I have been successful in writing less about Winnipeg Jets goaltending here at Arctic Ice Hockey but this is not the case over on Twitter, where I tend to react before I think. Discussions yesterday lead to assessing how should we distribute blame for the Jets’ goals against…
So, let’s split the issues into segments and parse out the blame between shot quality, shot quantity, Ondrej Pavelec, and Al Montoya. Numbers can never explain everything; however, numbers are imperative when it comes to scaling. You can only quantitatively assess something using quantitative values.
Shot Quality
When number folks discuss shot quality, it is predominately as shot location, since that is what drives percentages. For this exercise, we will ignore all debates on how shot location has been show to be predominately chance driven at a single season level.
Over at Hockey-Graphs, shot location differences was used to show how little it effects teams over the scale of a season. The process here is the same in that article; the difference in Jets' percentage of shots against in the slot relative to league average can extrapolate how many goals against the Jets lose or gain from shot quality. While the data has bias, it does pull the high percentage shots with "scoring chances against" (~ScA) having a shooting percentage of 13.9% and non-chances with 2.7% for even strength.
| SA | ~ScA | ~ScA/SA | delScA/SA | delScA | expGAdiff | |
| Away | 829 | 395 | 47.6% | 2.03% | 16.8 | 2.3 |
| Home | 933 | 398 | 42.7% | -2.96% | -27.6 | -3.7 |
| Total | -1.5 |
Home scorers though have an infamous tendency to have biases for their team. To help diminish this, Home data can also be treated as if the ~ScA/SA% was the same as Away data, and then average out the results.
| SA | ~ScA | ~ScA/SA | delScA/SA | delScA | expGAdiff | |
| Away | 829 | 395 | 47.6% | 2.03% | 16.8 | 2.3 |
| Home | 933 | 445 | 47.6% | 2.03% | 18.9 | 2.6 |
| Total | 4.8 |
| Min | -1.5 |
| Average | 1.7 |
| Max | 4.8 |
Shot Quantity
The process here is simple. The Jets shots against per minute is compared to the league average. The difference when extrapolated to the amount of minutes the Jets have played can then be converted to goals using league average shooting percentage.
| Min | SA/60 | Lg Avg | Diff /60 | Diff | exGAdiff | ||
| Winnipeg Jets | 4643.1 | 29.9 | 29.6 | 0.3 | 23.4 | 2.1 | |
Goaltending
For here, each goaltender was compared to recent historical norms for starters and backups in stopping the puck.
| Sv% | SA | GA | exp SV% | expGA | expGAdiff | ||
| Ondrej Pavelec | 0.901 | 1569 | 156 | 0.914 | 135 | 21 | |
| Al Montoya | 0.924 | 736 | 59 | 0.904 | 71 | -12 | |
This is not the only way to look at a goaltenders contributions. Another way is through Goals Versus Threshold (GVT), a semi-anecdotal stat comparing how a player affects a team's goal differential. The average of GA contribution from GVT and and Sv% can then be calculated.
| Sv% GA | -GVT | Average | ||
| Ondrej Pavelec | 21 | 8.0 | 14.5 | |
| Al Montoya | -12 | -6.2 | -8.9 | |
Conclusion
The results end up similar to as expected.
| +/- GA | ||
| Shot Quality | 2 | |
| Shot Quantity | 2 | |
| Ondrej Pavelec | 15 | |
| Al Montoya | -9 | |
| Sum | 9 | |
Ondrej Pavelec’s essentially replacement level play has severely hurt the Jets goals against. Al Montoya has surpassed the expectations on how a backup should perform. Shot quality and quantity show the Jets to be a below average team defensively; however, not even remotely as bad as some defenders of Pavelec have made it out to be.
While these numbers are just rough estimates, the distribution is likely near real values. The Jets currently sit at 23rd at 219 goals against, and 15 goals below the 16th best Philadelphia Flyers.
One slight red herring that goes on when discussing Jets goaltending is that the Winnipeg Jets as a whole are imperfect beyond just their goaltending. First, this is poor logic; all teams are flawed and have their imperfections, even which ever team wins the Stanley Cup. You only really learn by comparing teams relative to their peers. Secondly, the existence of other issues does not excuse an issue of itself.
