Moving into the second part of this pool of data, I wanted to take the same players I looked at in establishing "good" hitters (Part 1, Part 2; Part 1 has methodology) and observe the characteristics of the players within each of the percentiles. I was particularly interested in the possibility that we would see age, osize, hitting rate, or nationality (this will come in a later post) differences among this group, and among the percentiles. Granted, there are a number of explanations for these differences, including tendencies of line deployments for younger players and the fact that some European players that would normally only serve on the 3rd and 4th lines choose to stay in Europe. That said, it's still interesting to see how this plays out…
I maintained the forward/defencemen split I held before, as the two populations have distinct differences that are borne out in the data. First, let's look at our percentiles and age (remember, 1 = "best" hitters, 10 = "worst" hitters):
Forwards | Defencemen | ||||
%ile | n | Age | %ile | n | Age |
1 | 108 | 25.91 | 1 | 60 | 25.91 |
2 | 116 | 27.16 | 2 | 59 | 27.44 |
3 | 117 | 26.18 | 3 | 69 | 27.04 |
4 | 118 | 26.40 | 4 | 66 | 27.42 |
5 | 116 | 26.92 | 5 | 64 | 27.41 |
6 | 117 | 27.72 | 6 | 65 | 28.14 |
7 | 111 | 27.46 | 7 | 65 | 28.24 |
8 | 113 | 28.09 | 8 | 66 | 27.62 |
9 | 107 | 27.71 | 9 | 59 | 28.13 |
10 | 95 | 27.98 | 10 | 57 | 28.80 |
avg | — | 27.15 | avg | — | 27.62 |
Damn geezers. In all seriousness, this is a very interesting split…especially when you break the measures into age groupings:
Forwards | Defencemen | |||||||||
Age | n | TOI/G | Aw H/15 | ChPIM/15 | Age | n | TOI/G | Aw H/20 | ChPIM/15 | |
18-20 | 65 | 15.08 | 0.91423 | 0.06774 | 18-20 | 23 | 20.57 | 1.19856 | 0.12989 | |
21-23 | 237 | 14.96 | 1.12220 | 0.10154 | 21-23 | 122 | 19.57 | 1.35475 | 0.15080 | |
24-26 | 347 | 14.83 | 1.21042 | 0.12411 | 24-26 | 177 | 19.69 | 1.35558 | 0.15843 | |
27-29 | 270 | 15.17 | 1.14854 | 0.12433 | 27-29 | 146 | 19.66 | 1.40406 | 0.16213 | |
30-32 | 180 | 15.22 | 1.08750 | 0.12484 | 30-32 | 110 | 20.38 | 1.27939 | 0.17503 | |
33-35 | 120 | 15.40 | 0.94010 | 0.10420 | 33-35 | 80 | 20.44 | 1.20727 | 0.15957 | |
36+ | 70 | 15.31 | 0.82412 | 0.08786 | 36+ | 41 | 18.91 | 0.95119 | 0.15081 |
The most-striking suggestions to me are that a.) more-talented players (and thus more-talented hitters) reach the league earlier, and b.) players that hit a lot don't appear to stay in the league as long. In both forward and defence populations, the 30-32 years seem to be problematic; the hitting noticeably decreases, yet the PIMs reach their highest point. I can't seem to get over those figures for 18 to 20 year olds, even despite the small sample – the contrast between that cohort and the next is so stark in regards to checking minors, across the positions…it's funny because the impression we have is that it's rambunctious youth that can cause physical penalties. Or maybe some young gun trying to "prove" themselves. Now back to our percentiles: how about the size of our good/bad hitters?
Forwards | Defencemen | ||||
%ile | Ht | Wt | %ile | Ht | Wt |
1 | 72.99 | 202.19 | 1 | 73.65 | 209.08 |
2 | 72.77 | 201.63 | 2 | 73.78 | 212.97 |
3 | 72.89 | 201.44 | 3 | 73.74 | 210.94 |
4 | 73.13 | 205.36 | 4 | 74.00 | 209.76 |
5 | 72.79 | 204.64 | 5 | 73.84 | 209.83 |
6 | 72.88 | 203.13 | 6 | 74.15 | 210.11 |
7 | 72.70 | 200.83 | 7 | 73.75 | 209.60 |
8 | 72.78 | 199.97 | 8 | 73.77 | 208.67 |
9 | 72.91 | 201.25 | 9 | 73.69 | 210.20 |
10 | 72.97 | 202.31 | 10 | 73.79 | 209.47 |
avg | 72.83 | 201.93 | avg | 73.80 | 209.02 |
Doesn't really tell us much, eh? Which is okay, because size shouldn't be a determining factor on hitting effectiveness. Probably the most telling information is in the comparison of TOI figures alongside the hitting and penalty rates:
Forwards | Defencemen | |||||||
%ile | TOI/G | AwH/15 | ChPIM/15 | %ile | TOI/G | AwH/15 | ChPIM/15 | |
1 | 12.25 | 1.79 | 0.01 | 1 | 18.36 | 1.91 | 0.06 | |
2 | 13.52 | 1.63 | 0.05 | 2 | 18.68 | 1.74 | 0.10 | |
3 | 14.59 | 1.48 | 0.07 | 3 | 18.98 | 1.53 | 0.11 | |
4 | 13.72 | 1.62 | 0.12 | 4 | 19.38 | 1.58 | 0.14 | |
5 | 13.42 | 1.82 | 0.19 | 5 | 18.88 | 1.58 | 0.19 | |
6 | 13.60 | 1.47 | 0.26 | 6 | 18.65 | 1.39 | 0.24 | |
7 | 14.98 | 1.19 | 0.20 | 7 | 19.10 | 1.26 | 0.21 | |
8 | 15.88 | 0.89 | 0.15 | 8 | 19.18 | 1.08 | 0.21 | |
9 | 16.49 | 0.70 | 0.15 | 9 | 20.46 | 0.97 | 0.21 | |
10 | 16.78 | 0.51 | 0.17 | 10 | 19.76 | 0.77 | 0.27 | |
avg | 14.53 | 1.31 | 0.14 | avg | 19.19 | 1.38 | 0.17 |
Now we're in business…those 9th and 10th (really, 90th and 100th) percentiles retain a combination of hard-nosed players that can't keep it clean and, more prominently, scoring types that can't stay out of the box. The latter can offset the detriment, but it remains to be seen whether the former could also (particularly in the case of forwards).
Next time, I'll take a look at some of those fun North American/European debates in regards to physicality.