When I first begin contemplating statistical analysis in hockey, I was immediately struck by the outdated nature of a number of common stats. Whether it was the nebulous nature of the multiple assist, the deception of the +/- or even in the way we look at team-wide success on the power play and on the penalty kill, it seemed to me that we can, and maybe should, be doing better.
Last year, I developed a rudimentary method for tracking these last figures by opportunity cost in time (slaves to the clock, as we are) instead of raw opportunity, due to the variations in opportunity sizes. At the time, I held myself to tracking the Maple Leafs only. In isolation, it was pretty clear that the Buds had a solid power play, but were rather hopeless when disadvantaged. While interesting in isolation, the Leafs do not play themselves. I understood that to truly measure this stat, I would have to track the entire league. So I did.
As this season proceeded, I undertook to track the special teams activities of all 30 NHL teams. If you have not read the linked article, or my last article, what I am looking at is the average time each team needs on its power play before scoring and the average time between power play goals allowed. This requires measuring, to the second, how long each team spends on their special teams during games. To account for 2-man advantage situations, I have decided to double count the time. Also, while I am noting shorthanded goals, the numbers I am about to publish do not include them.
Let’s start with the power play. It stands to reason that the stronger power plays would require less time, on average, to score. In power play goals per opportunity, as measured in seconds, the leader board is as follows:
1) Van 337.882
2) Cal 346.000
3) Atl 347.600
4) Phi 349.714
5) Tor 349.929
6) NYR 350.929
7) SJ 372.000
8) Pho 399.692
9) Ana 408.800
10) LA 415.133
11) Det 448.167
12) Clm 451.818
13) Col 460.833
14) Edm 465.250
15) Was 479.769
16) NYI 480.500
17) Min 514.583
18) Pit 552.364
19) Chi 552.667
20) Dal 579.818
21) TB 588.778
22) Buf 612.556
23) Car 632.555
24) Mon 668.875
25) NJ 684.714
26) Bos 722.667
27) Ott 740.000
28) StL 749.667
29) Fla 767.429
30) Nas 817.500
The most prolific teams, the Canucks, Flames, Thrashers, Flyers, Maple Leafs (this is pre-Kessel!) and Rangers, need just over 5.5 minutes to score – that means scoring power play goals more than once every three full minor penalties.
The weakest power plays, such as those belonging to forward-starved Bruins, the Senators, Blues, Panthers and Predators, have so-far required more than double the opportunity, needing over 12 minutes each between power play goals.
For every power play, there is an equal and opposite penalty kill. The following chart lists NHL teams in how long they were able to kill penalties before succumbing to the opposition’s power play.
1) Min 886.167
2) Ott 808.571
3) Col 804.500
4) Chi 773.142
5) Phi 739.143
6) NYR 691.333
7) SJ 613.000
8) NYI 598.556
9) Atl 586.750
10) Pit 563.727
11) StL 529.800
12) NJ 526.250
13) TB 525.222
14) Car 524.667
15) Was 515.455
16) Edm 514.500
17) Cal 478.000
18) Clm 468.727
19) Buf 464.250
20) Pho 460.333
21) Van 420.538
22) Bos 405.900
23) Nas 402.818
24) LA 381.429
25) Dal 379.750
26) Mon 367.800
27) Fla 337.154
28) Det 328.833
29) Ana 326.056
30) Tor 284.059
Interesting to note that the worst penalty killing team (Toronto) surrenders power play goals faster than the best team (Vancouver) is at scoring them – 337-284 – while the best penalty killers (Minnesota) take more time between the allowing of power play goals by the opposition than the worst power play (Nashville) requires to score their own – 886-817.
We’ll end this column with one final long table, wherein I’ll list the aggregate special teams. From best to worst. Considering that we would all want our team to score more frequently when up a man than we would be surrending goals when down one, I have simply taken the power play efficiency number and subtracted the penalty killing number. Great special teams units will have negative numbers, and poorly, or poorly balanced teams will have positive numbers, the higher, the more poorly balanced.
1 Phi -389.429
2 Min -371.584
3 Col -343.667
4 NYR -340.404
5 SJ -241.000
6 Atl -239.150
7 Chi -220.475
8 Cal -132.000
9 NYI -118.056
10 Van -82.656
11 Ott -68.571
12 Pho -60.641
13 Edm -49.250
14 Was -35.686
15 Clm -16.909
16 Pit -11.363
17 LA 33.704
18 TB 63.556
19 Tor 65.870
20 Ana 82.744
21 Car 107.888
22 Det 119.334
23 Buf 148.306
24 NJ 158.464
25 Dal 200.068
26 StL 219.867
27 Mon 301.075
28 Bos 316.767
29 Nas 414.682
30 Fla 430.275
I’ll be back in the next few days to offer some analysis to go along with these numbers, and look at a few trends we should follow as the season builds.
How much are Toronto’s numbers on the power play affected by the 3 two-man advantage goals vs. the Ducks on Oct. 7, in addition to a 4-on-3 goal?
I won’t be able to get to the numbers until Tuesday or Wednesday, but it wasn’t that much. In that game, Anaheim gave the Leafs plenty of opportunity on the power play, and as a measurement of opportunity, that game’s effects on the total monthly numbers is mitigated. Also – remember that I measure both penalties in the 5-3 scenarios. The two penalties have the potential worth of 240 seconds. One goal will cut short the earlier of the two penalties, while the second one will continue to play out.
For argument’s sake, let’s say the two penalties occured simultaneously. After one minute, the Leafs scored. They did not score on the remainder of the power play. The total effeciency then is one goal per 180 seconds. I’ll run the numbers without that game when I can and post the results here.
Dillon – when I took away the Leafs PP from that one game against Anaheim, their PPG rate dropped from 349.929 to 423.222. In other words, from 5th to 11th. But if you look at most teams and took away their top game, especially within only their first 15 or so, their rate would drop a similar percentage.
[...] Some of you may be wondering why I didn’t post the Special Teams for January’s end. I figured that the short month of games in February would provide a better take on the state of the game. These will be the last numbers posted before the end of the season. For a recap of my methods, click here. [...]