I’ve found it more difficult to look at offense than defense as players have more effect over more factors that determine goal production, but none of which I would call great statistical tools for understanding offense. Goals represent a small sample of large selection of time. Shots only measure a players shooting, not how good these shots are. You can look at how good of shots players shoot; however this isn’t worth anything if you can’t score. You can also look at shooting percentage, which is just as statistically useful as goals. Or you can look at how well players perform on a given shot compared to their peers. One can also extend all this to include all shots by line mates (increasing the shots by five times). All these things combined could likely determine good from bad; however as individual statistics they are almost useless. The other question then is how does one combine them, and at this point I have no clue. This all said I will attempt to measure offense via a few of these factors.
When analyzing the power-play the first question will be one of shots per minute, each player was compared to their team’s shooting rate, the resulting error was well within binary error as such players shoot based on how often their team shoots, what this means is hard to say. One can therefore conclude that players shoot more or less based on coaching (team factors). That doesn’t say whether shooting more or less is good or bad coaching. However, when one compares expected goals vs. actual goals one sees a distinct patter, similar to even strength, of positive error growth, so coaches choose players to play on the power-play who score more than average, based on shooting percentage. You can see how much better players due than expected by looking at shot quality neutral shooting percentage .
Since I scaled out the team factor I should at least note some facts of teams on shooting percentage. If you do a regression with respect to shots per hour and goals per hour you get a very linear relationship between the two. If you look at shooting percentage you will find that there is no reason to assume shooting more affects your shooting percentage. In other words it would be hard to argue to shoot less. That being said, there are a number of teams with very successful power-plays who shoot very little, or unsuccessful power-plays that shoot a lot. These results are strange in my opinion, because it basically means teams should shoot more no matter what. Of course each team has different players, but players in relation to their teams don’t shoot more or less. The only cost of a shot for is the loss of puck possession (what’s that worth?).
Since we know that the only thing that matters is shooting percentage here’s a list of the top players shooting percentages on the power-play.
 SQN% - or shot quality neutral shooting percentage, is a measure of offense. It's calculated by: (goals for/shots for)/(expected goals for/(league average shooting percentage*shots for)) or (goals for * league average shooting percentage/expected goals for). I don'texpect this necessarily to make sense so you can go to Hockey Analytics and read about their Shot Quality article.