The Pittsburgh Penguins season came to a sudden halt last week as they were eliminated from the 2013-14 NHL Playoffs by the new Metropolis Division Champion New York Rangers. It should come as no surprise, considering Superman, the mascot of the Metropolis Division, wears the same colors as the Rangers...
It was a hard fought series, with both teams battling hard, but in the end only one was able to advance. It sucks that our season came to an abrupt end, but there are some positives to be found amidst the crushing sense of loss and disappointment. I had finished inputting the data a few days ago, but there was a lot going on the past few days, speculations on what the team plans to do going forward and announcements of changes already being made. So I held off on the usual weekly features, and now that the dust has settled we can get back to our regularly scheduled programming.
Goaltending and Team Effort
There was only one goaltender used throughout the entire post-season, so his 5-on-5 numbers reflect that of the entire team. Considering Fleury was a big question mark going into the playoffs, and one of the fan bases biggest concerns, it is encouraging to see how well he played, his ability to bounce back after a bad goal or a big loss, and his overall growth as a player.
Against the Rangers, Fleury went 3-3-1 with 2 shutouts, and set a franchise record for fewest goals allowed in a 7 game series. At 5-on-5 he had a 2.04 GAA and .917 Sv%, not elite, but still numbers that should have been good enough to win.
However, the team itself wasn't getting things done, as they were only able to match the 2.04 GF60 for an even 50.0 GF%. This is partly due to the fact that they had an abysmal 6.7 Sh%, which is below league average, let alone the Penguins own usual level of dominant excellence, resulting in a 984 PDO, well below their norm.
On the plus side, however, they were doing an excellent job controlling the flow of play, generating 30.3 SF60 while limiting the Rangers chances with a 24.5 SA60, giving them a 55.3 SF%. So the Pens were getting chances and limiting the Rangers ability to get the puck on net fairly well, but they just couldn't find the back of the net. Chalk this up to luck, bad bounces, hot goaltending, star players disappearing, or whatever else you want to use to explain it. The fact remains that the Pens and Rangers were evenly matched at even strength, and despite controlling the flow of play the Pens just couldn't get the job done.
Of course, considering they broke even at 5-on-5, then the biggest issue is that the usually stellar special teams just failed completely. They were solid on the PK, stopping 23 of 26 Rangers opportunities for an 88.5 PK%, however the issue is that the 3 goals that were scored all came in the key losses over the final 3 games of the series. Even more damning was the fact that the top PP in the regular season was held to just 1 goal in 20 chances, a 5.0 PP%. So the teams were evenly matched in 5-on-5 play, but the Pens got beat by special teams.
5-on-5 Goals For Relative
As per our usual, we are going to look at the player performance by visualizing the data on bubble charts. The X-axis is Relative Goals For per 60, so players with positive numbers on the right of the chart see the team score goals more often while they are on the ice, whereas those with negative numbers on the left f the chart see the team score less often when they are on the ice. The Y-axis is Relative Goals Against per 60, so player with negative values on the bottom of the chart see the opponent score less often while they are on the ice, whereas those with positive values on the top of the chart see the opponent score more often when they are on the ice. The bubble size is Relative GF%, with yellow bubbles representing positive results whereas white bubble are negative.
Players in the bottom right quadrant had solid two-way performances, scoring more often and keeping the opponent off the board. Players in the top right quadrant were able to contribute to the offensive side of the puck, but were a bit of a defensive liability in their own end. Players in the bottom left quadrant were more or less solid defensively, but were ineffective when it came to offensive contributions. And players in the top left quadrant were those that struggled at both ends of the ice, neither chipping in offensively nor helping keep the opponent off the board.
The tiny speck of Sutter is the only player that somehow managed to come out at a dead even 0 in Relative GF%, completely mirroring the team average. Up in the top right we have Crosby and Niskanen right on top of one another, so it is a little difficult to read those names. And lastly, being that they barely played I allowed the chart to cut off the extreme outliers Glass and Orpik. Both managed to be the only two players that had absolutely no 5-on-5 Goals Against scored while they were on the ice, with Orpik being on for 1 Goal For and as such would be in the extreme lower right quadrant, whereas Glass was on for none and as such would be in the lower left quadrant, a little to the rigth and far below Vitale and Adams.
5-on-5 Shots For Relative
Next we have our possession bubbles, looking at how well players controlled the flow of play. The X-axis is Relative Shots For per 60, so players with positive numbers on the right side of the chart see the team generate more chances while they are on the ice, whereas those with negative numbers on the left side of the chart see the team generating fewer shot attempts when they are on the ice. The Y-axis is Relative Shots Against per 60, so the players with negative values on the bottom of the chart allow the opponents to generate fewer scoring chances while they are on the ice, whereas those with positive numbers on the top of the chart see the opponent shooting more often when they are on the ice. The bubble size is Relative SF%, with yellow bubbles representing positive values while white bubbles are negative.
Players in the bottom right quadrant are those that were most successful at controlling the flow of play, creating more chances while limiting the opponent's ability to get pucks on the net. Players in the top right quadrant were able to generate chances of their own, but also allowed the opponent more opportunity. Players in the bottom left quadrant were no generating chances on their own, but they were able to limit the opponent's ability to get shots off. And then those in the top left quadrant were ineffective both offensively and defensively, not creating many chances of their own and getting dominated by the opponents as well.
Orpik does appear this time, but keep in mind he played all of 5 minutes this series. In addition, Glass got cut off due to his limited playing time. However, if he were pictured he would be in the bottom left quadrant past Goc and Stempniak. The team barely generated any chances while he was on the ice, the lowest SF60 Rel on the team, but also didn't allow many chances, as he had the lowest SA60 Rel on the team too.
5-on-5 PDO Relative
And here we see the combination of possession and scoring, which players were able to best capitalize on the ample opportunities they generated on the ice. The X-axis is Relative Sh%, so players with positive values on the right of the chart see the team score at a higher rate while they are on the ice, whereas those with negative values on the left side of the chart are less likely to see the puck in the back of the net when they are on the ice. The Y-axis is Relative Sv%, so players with positive values on the top of the chart see the opponent score at a lower rate while they are on the ice, whereas those with negative values at the bottom of the chart are more likely to see the puck go into their own net when they are on the ice. The bubble size is Relative PDO, with yellow bubbles representing positive values while white bubbles are negative.
Players in the top right quadrant were most effective as they saw an increased ability for the team to find the back of the net and a decrease in the chances of the opponent scoring while they were on the ice. Those in the bottom right quadrant were able to contribute offensively but were perhaps a bit of a defensive liability when they were on the ice. Those in the top left quadrant were unable to contribute offensively, but were at least able to manage to keep the opponent off the board while they were on the ice. And then those in the bottom left quadrant struggled at both ends of the ice, neither adding to the offensive aspects not preventing the opponent's ability to score.
Once again we see Glass and Orpik got cut off as outliers, being that they didn't have a single Goal Against while they were on the ice and as such perfect 1.000 Sv%. Orpik would be in the extreme top right quadrant as a player who saw the team excel both offensively and defensively while he was on the ice, whereas Glass would be in the top left quadrant, a bit further right and far higher than Bennett, as a player that didn't do well offensively but managed to excel in his own end.
5-on-5 Zone Start Relative
Now that we have the production and the PDO, which you may choose to chalk up to luck or to player skill, we can look at Zone Starts in an effort to explain why some players were putting up less impressive numbers than others. The X-axis is Relative O-Zone Starts, so players with positive values on the right side of the chart were given more prime O-Zone opportunities than their peers, whereas those with negative values on the left side of the chart were used less often in the O-Zone. The Y-axis is Relative D-Zone Starts, so players with positive values at the top of the chart were given tougher D-Zone assignments than their peers, whereas those with negative values at the bottom of the chart were used less often in the D-Zone. The bubble size is Relative ZS%, with yellow bubbles indicating a player who gets more sheltered starts than his peers whereas a white bubble indicate tougher minutes.
Players in the top left quadrant faced the toughest minutes, getting fewer O-Zone starts and more D-Zone starts than their peers did. Then we have the less sheltered players, as those in the top right quadrant saw more D-Zone starts than their peers but they also saw more O-Zone starts, whereas those in the bottom left quadrant then saw fewer O-Zone starts but also fewer D-Zone starts than their peers. The most sheltered players fall into the bottom right quadrant, getting more O-Zone time and less D-Zone time than their peers.
This is the only chart in which we see all 20 skaters appear together without getting cut off as outliers. The one set of names that is difficult to read is Maatta and Letang, who oddly enough had nearly identical usage in this series. Based on zone time, we would expect those with sheltered minutes to have better numbers, while we can forgive those with tougher minutes if they do not.