Data Exploration: Goals and Shots

Enough with the poetry already! Time to dig in some numbers!

Inspired and enabled by mc79hockey and his data-grabbing wizardry, I decided to get a bit nerdy and start playing with NHL.com official stats. Specifically, I took a look at Anaheim's regular season and their shots-on-goal. (I pulled empty-net goals, because I think the point I want to make about this is really about goalies and not about empty nets.)

First off, here are these Duck goals sliced by shot type, as tracked by NHL.com. I don’t know why the Ducks didn’t score any (or try many) wrap-around goals, but I can’t think of an incident off-hand to say that this data is wrong.

Shot Type	Goals	Shots	Percentage
Slap	83	1,110	7.48%
Wrist	61	637	9.58%
Snap	38	382	9.95%
Backhand	20	258	7.75%
Tip-In	39	154	25.32%
Wrap-Around	0	34	0.00%
Total	241	2,575	9.36%

As you'll note, tip-ins are remarkably efficient. Lesson 1: shot type matters.

Next comes distance, as measured in feet. Andy Grabia at BoA has noted in a rather long post that this distance is measured from the back boards, not the goal line. Whatever, the point is that it is measured.

Distance (feet)	Goals	Shots	Percentage
0 - 12	62	282	21.99%
13 - 24	106	745	14.23%
25 - 36	31	519	5.97%
37 - 48	24	508	4.72%
49 - 60	16	410	3.90%
61 +	2	111	1.80%
Total	241	2,575	9.36%

The findings feel right; closer shots are more efficient. Lesson 2: shot distance matters.

I didn’t bother separating 5-0n-3 or 4-on-4 or any other such useful nonsense, but here’s the layman’s take on man-advantages.

Strength	Goals	Shots	Percentage
PP	87	601	14.48%
ES	146	1,848	7.90%
SH	8	126	6.35%
Total	241	2,575	9.36%

Lesson 3: man-advantage situation matters.

Measuring time elapsed is trickier, and certainly has kinks. This 'rebound' tracker really just tracks the time elapsed (a) from the start of the period, or (b) from the last shot taken. I also failed to do some useful stuff like think about stoppages in play, but the point really is about rebounds.

Time Since Last Shot	Goals	Shots	Percentage
within 3 seconds	35	97	36.08%
within 30 seconds	73	675	10.81%
within 60 seconds	43	497	8.65%
more than 1 minute	90	1,306	6.89%
Total	241	2,575	9.36%

Wowzers! Lesson 4: time elapsed between shots matters.

And for sure, it’s separable by shooter, of which here’s a glimpse:

Shooter	Goals	Shots	Percentage
Teemu Selanne	38	265	14.34%
Andy McDonald	34	229	14.85%
Other Forwards	138	1,430	9.65%
Scott Niedermayer	13	181	7.18%
Francois Beauchemin	8	121	6.61%
Other Defensemen	10	349	2.87%
Total	241	2,575	9.36%

Lesson 5: shooter (and player position) matter.

This last one took me a little while, as I still depend on some manual-ish data manipulation, but I tracked what the score was at the time of each shot.

Anaheim Margin	Goals	Shots	Percentage
Down by 2 or more	32	293	10.92%
Down by 1	49	538	9.11%
Tie Game	89	1,004	8.86%
Up by 1	41	437	9.38%
Up by 2 or more	30	303	9.90%
Total	241	2,575	9.36%

Lesson 6: Margin seems not to matter. (though it might when combined with other variables)

So my point is really not about shots, but about saves and save quality. A Selanne power play tip-in is not the same as a Vishnevski short-handed wrap-around, and a good system to really measure goalies and their save percentages should include probably all six of these factors.

“But Sleek! All you’ve done is show me singular cuts of one team’s data. Isn’t there some correlation going on here, and wouldn’t it be more statistically relevant to run this for 30 teams?”

Yeah, yeah, those are future posts, when I can kind of work out the kinks in my dinosaurish data skills. But I’m getting it going, boys.

Maybe you’re looking at a future Islanders G.M.