Crashing the Crease: “Clutchness,” Revisited

Ilya Bryzgalov

Image courtesy of Bruce Bennett/Getty Images North America

About a month ago, we looked at a breakdown of Bryz’s save percentage in two minute buckets. The intent was to measure how “clutch” Bryz was by evaluating his save percentage at key points in the game through the first 41 Flyers’ games. What we saw was, at least at a high level, a stark difference between his performance in wins and losses.

Looking back on the previous season, though, there was an improvement in Bryz’s game once he was handed the reins after the Winter Classic. Thus, there was a necessity to complete the analysis and see what the final 41 games would do to the early season data. The effect, put simply, is pretty apparent. The negative issues noted in the previous analysis are smoothed out. Adding more data to a sample size can effectively account for the smoothing, but the data itself also shows some improvement in performance. I would say his increasing comfort level in both this city and his role led to some of these improvements. To highlight these differences, I’m going to recycle a few graphs of half-season data and contrast them with the full data set.  Let’s start with Bryz’s bucketed save percentage in Flyers wins.

This graph is nearly the same one as seen in the August 9th article, except the scale has been adjusted.  Notice some key aspects, including the slight upward trend in save percentage as the game went on, as well as the relatively high volatility in his performance (standard deviation of 8%).  The graph below is the same format, but for the entire season. It stands to simple reason that we should expect some reduction in variability in performance as Bryz better establishes his norms and we add more than a handful of data points to the analysis, but what’s interesting is that we also see a pretty solid uptick in performance, as mentioned earlier. First, the graph:

First period performance is still relatively up-and-down, showing a standard deviation of over 5%. The fluctuation for Bryz’s save percentage over the entire game is a little less and his third period performance in wins really improved over the whole year, especially in the waning minutes of the game. While not any sort of conclusive evidence, statistically, it does point to his being more reliable in tight situations where a lead needed to be held.

As noted above, Bryz’s overall performance did get better when the whole year is evaluated. The table below illustrates this:

Again, tracking the OT save percentage in wins is done for completeness, not utility, as you can’t win an OT game without saving all of the shots. Still, while his performance was somewhat inconsistent through 41 games, it really leveled out by the end of the season. His save percentage by period in wins was rather consistent.

Now to flip it and reverse it, let’s revisit his performance in losses.

Same graph as seen on August 9th, again with an adjusted scale. The key takeaways here for me were the erratic first period performance, the high variability (nearly 16% standard deviation) and the very poor end-of-game performance. Looking at the same graph over the whole year, though, shows a much more optimistic picture, at least when remembering that these were all losses.

While there’s still a good amount of fluctuation in performance, it’s nearly 5% less on a standard deviation basis. This reduced variability is, in my view, attributable to more consistent performance across the board, as his save percentage did increase in these games. The pronounced periods of poor performance, such as the end of the first and third periods, are not as pronounced with a full season’s worth of data.

Comparing the actual numbers from the first half and the full year, that aforementioned reduction in inconsistency is very apparent.

The late-game save percentage in both the third and overtime periods is much better. While an 85-88% won’t cut it, the trend was in the right direction even in losses: better, more consistent goaltending.

So, Bryz’s performance in wins is still statistically much better than in losses and he wasn’t able to completely eradicate the late-game issues, at least when looking at the season averages, but he was able to right the ship and show real, measurable improvement. This is good news, as is the fact that his ability to seal a game away late seemed to be a real thing when looking at the third period for the full-year data.

Circling all the way back to square one, though, I still feel like I haven’t fully addressed the question of how to measure “clutchness.” This evaluation is a nice visual tool for me, and it’s one that’s helped sparked some ideas. I think the next step is to step up the analysis and explicitly define the situations that make a clutch goaltender rather than looking for trends. For example, the idea of save percentage by two-minute buckets in wins and losses works at a high level, but if the Flyers are up by two or three or four goals, do I really consider that clutch? Probably not. It’s essential that it stay a two, three or four goal lead, no doubt, but my initial intent was to put some strong quantification to this idea.

Where this will be going in my next article is to look at Bryz’s bucketed save percentage as a direct function of goal differential, broken down into five categories:

  • Leading by more than 1 (Lead > 1)
  • Leading by 1 (Lead = 1)
  • Tied (Tied)
  • Losing by 1 (Trail = 1)
  • Losing by more than 1 (Trail > 1)

My expectation is that, when bucketed save percentage is separated into these five categories, we’ll get a lot more direct insight that will help to make more sense of the potential trends seen above. Until that article gets posted, though, I think it is fair to reiterate that there are effectively two Bryzes in the same body. The losses aren’t all Bryz’s fault, but he’s not posting numbers that I would consider close to his winning numbers in losing efforts. While there’s certainly a team effect, I find it hard to believe that the same roster could consistently perform so vastly different between wins and losses that Bryz’s save percentage would regularly be about 5% lower in the losses. Hopefully, as the data is more usefully sliced and diced, we’ll be able to garner a little bit more each time around.

For now, thanks for reading, and please feel free to comment with any questions, issues or errors!

  • Joe Cesarini

    Someone commented in the last article that the other team throws the farm at you when trailing and takes lousy shots, causing an increase in save percentage. I realize now that the same is true for your own team. If you are losing, your offense is starting to squeeze the stick a bit more and dropping an extra attacker, pinching a defenseman, etc. So, Bryz will be left to stop more odd-man breaks and possibly short be a defenseman and have to take the shooter, leaving an opening.

    But, in defense of your data, there are two really alarming things: his variability is all over the place. There are huge zig-zags. Also, if he’s having a good warm-up, he’s probably going to win. Every single game Marty Brodeur starts, you’re going to win. Maybe something goes wrong (bad hop, down a top player injured, other team really hot), but he’s not going to cost you a game, ever. You really need your backstop to come to the rink believing he’s going to win every game. Roy did. Hasek did. Belfour did. Even a Mike Vernon, Kirk McLean, Ron Hextall, Grant Fuhr. Bryz needs to go out there and stop every shot, and if he doesn’t, at least kick your ass for getting in his crease. Show heart every day and let the stops come. Be confident. We really need that with our possibly leaky defense, coming up…

    • Justin Brennan

      Joe, thanks for the comment.

      I remember the comment, because it was good insight into why I was seeing what I was seeing. I spent a good amount of time looking at this effect, and was going to incorporate the analysis here, but I couldn’t figure out a good way to incorporate it without spiraling off into another direction.

      Below you’ll find one of the graphs I put together evaluating the impact of shots against Bryz based on the five categories outlined in this article (Lead > 1, Lead = 1, etc.). It does reinforce that as the Flyers take a lead, the shot intensity against Bryz increases. On the other side of the coin is the fact that the shot intensity drops as they’re trailing, presumably due to greater desperation to get attempts down the other end of the ice. Interestingly, the tied game shows a decreasing shot intensity, likely due to a more cautious, puck possession attack approach.


      Aside from that, you’re right on. I think I brought it up in another article, but G has mentioned that they know when Bryz will be on. Something about his pre-game and warmup. It’s clear that his overall game performance really can be discerned from the early performance in a majority of the cases. If he has a rough first, you can hope for a barely-average performance, at best. If he’s lights out early, you can expect that to continue, barring external influences like injury or drastically different team performance.

      He must learn how to corral this and become more consistently effective. If he can find that magic switch, he really could be the goalie they’re paying for. It isn’t easy, though, and in a lot of ways, that level of consistency is the Holy Grail of goaltending.

    • Geoff Detweiler

      I’m not sure it naturally follows that increased shot attempts when trailing leads to odd man rushes against.

      It may be true, but it is hardly intuitive. One would assume that the trailing team would be able to maintain possession in the offensive zone better since they are less likely to give up the blue line. This increased pressure would lead to increased time in the offensive zone.

      Isn’t it likely that this pressure would also cause more dump and change, countering any potential risk of odd-man rushes? I think it would be.