Originally Posted by schuckers (Post 64919607)

There is plenty of information like this that would be very useful. In addition to your list, the degree to which the goalie is screened and the percentage of passes completed/tipped would be a start.

Originally Posted by almostawake (Post 66281401)

Yeah, that is the second step of the dataflow I outlined. You write a script that extracts the table data directly from the raw .html and stores/outputs it in whatever format you like.

Originally Posted by Dilettante (Post 64405433)

Regarding fenwick/corsi stats, i just looked them up for the rangers/devils game this afternoon http://timeonice.com/shots1213.php?gamenumber=20671

Judging by fenwick/corsi alone it looks like the devils outplayed the rangers, but the rangers actually won the game pretty handily 4-1. Am I interpreting this wrong and, if so, how should these results be interpreted?

Originally Posted by overpass (Post 66251885)

Can you really expect a team to shoot as well if it stops focusing on shooting percentage and starts trying to maximize shot volume? Consider that all of the teams who generated the data you analyzed were probably focusing on increasing both their shooting percentage and their shot volume.

Originally Posted by tag0519 (Post 62658041)

I'm not sure if this exists already but what would everyone think of a stat called - "Adjusted Plus/Minus"? Seems that +/- has a lot to do with the team as well as the individual. Lets face it - Stamkos and Tavares would have a better +/- if they were on Pitt or Chi. It would be good to get an idea of a players "real" +/-.

Originally Posted by MrCaptain (Post 66133309)

Another non-binary value you could use is average salary. This is essentially what GMs and agents conclude is the "worth" of a player. This would give a consistent measure (you won't be comparing apples to oranges, points by forwards, minutes by defencemen, etc). I'm not going to argue that every player in the study is worth exactly what he's making, but hopefully this will be averaged out over the entire sample.

Basically graph the average salary of every player picked first overall, second overall, etc.

I'd love to see a study done like this for all rounds of the draft. I think then you could say "a first overall pick is worth on average a 6 million dollar player. A tenth overall pick is worth on average a 2 million dollar player. I'll trade you the 9th, 10th, and 11th, overall picks for your first overall" :yo:

Originally Posted by PavelDatsyuk (Post 64524773)

I have a self made excel spreadsheet with this for personal use but don't want to share it

I will give you this chart to compare whatever players you want to league average though

http://imageshack.us/photo/my-images/534/shootinge.png/

X-axis is career games
Y is obviously SH%

Originally Posted by Sixbladeknife (Post 66160839)

Very nice work! It is indeed very interesting that there's no correlation. Maybe blocking a lot of shots means that the ones getting through are a lot more dangerous? I know the shot quality effect seems to be quite small in the studies I've seen, but off the top of my head I really can't come up with a better explanation.

If you have the time and effort, you could try fooling around with team SV% and see if a negative correlation emerges.