PITTSBURGH -- Ben Roethlisberger spent Monday night o means would I rank Kennedy in that spot, but I can see some of the forces that were at play. For one thing, the process, removing the variability of shooting percentage, focuses on shots (and locations) and that helps Kennedy, who scored on a meagre 7.5% of his shots over those two seasons, ranking 227th among 230 forwards (Brian Rolston, Darren Helm and Nathan Gerbe were the only ones worse) that scored at least 20 goals over those two years. So, by removing shooting percentage (or goals) from the equation, a shot from Tyler Kennedy is considered the same as a shot from Steven Stamkos, even though Stamkos had scored on 18.3% of his shots through those two seasons. (By the way, I recognize that Im using overall shooting percentage as opposed to 5-on-5, but the point essentially, much like the song, remains the same.) This is particularly important in Kennedys case because he generated a lot of shots. He ranked 28th in the league in shots on goal per game over those two seasons (3.06 per game) and thats impressive enough, but he also did so in a fraction of the time that other leaders played. Over those two seasons, Kennedy played 2025 minutes. Of the 58 players to record at least 400 shots on goal, though, only one -- Evgeni Malkin -- recorded more on a per-60-minutes basis and Kennedy didnt have the benefit of significant power play time to increase his offensive numbers. Here are the leaders in shots/60 minutes for forwards with at least 400 shots on goal in 2010-2011 and 2011-2012 combined: Rk Player Current Tm Pos GP SOG SH% TOI SOG/60 1 Evgeni Malkin Pittsburgh C 118 521 12.5 2429 12.87 2 Tyler Kennedy Pittsburgh C 140 429 7.5 2025 12.71 3 Alex Ovechkin Washington LW 157 670 10.4 3232 12.44 4 Jeff Carter Los Angeles C 135 519 11 2515 12.38 5 Patric Hornqvist Nashville RW 155 495 9.7 2407 12.34 6 Rick Nash Columbus LW 157 611 10.1 2984 12.29 7 Evander Kane Winnipeg C 147 521 9.4 2600 12.02 8 Phil Kessel Toronto C 164 620 11.1 3256 11.43 9 Patrick Sharp Chicago C 148 550 12.2 2909 11.34 10 James Neal Pittsburgh LW 159 541 11.5 2913 11.14 11 Henrik Zetterberg Detroit LW 162 573 8 3194 10.76 12 David Booth Vancouver LW 144 439 8.9 2475 10.64 13 Joe Pavelski San Jose C 156 551 9.3 3145 10.51 14 David Clarkson New Jersey RW 162 420 10 2426 10.39 15 Radim Vrbata Phoenix RW 156 472 11.4 2729 10.38 16 Logan Couture San Jose C 159 498 12.7 2893 10.33 17 Daniel Sedin Vancouver LW 154 495 14.3 2876 10.33 18 Marian Gaborik N.Y. Rangers RW 144 468 13.5 2722 10.32 19 Johan Franzen Detroit C 153 459 12.4 2688 10.25 20 Michael Grabner N.Y. Islanders RW 154 402 13.4 2359 10.22 21 Justin Williams Los Angeles RW 155 454 9.7 2666 10.22 22 Drew Stafford Buffalo RW 142 405 12.dddddddddddd.6 2437 9.97 23 Steven Stamkos Tampa Bay C 164 575 18.3 3462 9.97 24 Jeff Skinner Carolina RW 146 425 12 2564 9.95 25 John Tavares N.Y. Islanders C 161 529 11.3 3207 9.90 26 Thomas Vanek Buffalo LW 158 442 13.1 2709 9.79 27 Corey Perry Anaheim RW 162 567 15.3 3540 9.61 28 Danny Briere Philadelphia C 147 420 11.9 2625 9.60 29 Jarome Iginla Calgary RW 164 540 13.9 3407 9.51 30 Eric Staal Carolina C 163 558 10.2 3544 9.45 31 Patrick Marleau San Jose C 164 530 12.6 3384 9.40 32 Marian Hossa Chicago RW 146 453 11.9 2898 9.38 33 Brad Richards N.Y. Rangers C 154 501 10.6 3226 9.32 34 Jason Pominville Buffalo RW 155 450 11.6 2939 9.19 35 Patrick Kane Chicago RW 155 469 10.7 3064 9.18 36 Teemu Selanne Anaheim RW 155 423 13.5 2776 9.14 37 Shane Doan Phoenix RW 151 447 9.4 2937 9.13 38 Bobby Ryan Anaheim RW 164 474 13.7 3160 9.00 39 Ilya Kovalchuk New Jersey LW 158 555 12.3 3709 8.98 40 Ryan Kesler Vancouver C 159 482 13.1 3228 8.96 41 Ryan Callahan N.Y. Rangers RW 136 414 12.6 2793 8.89 42 Jason Spezza Ottawa C 142 420 13.1 2846 8.85 43 Erik Cole Dallas LW 164 442 13.8 3033 8.74 44 Matt Moulson N.Y. Islanders LW 164 456 14.7 3130 8.74 45 Olli Jokinen Winnipeg C 161 431 9.3 2959 8.74 46 Scott Hartnell Philadelphia RW 164 409 14.9 2819 8.71 47 Jonathan Toews Chicago C 139 418 14.6 2891 8.68 48 Andrew Ladd Winnipeg LW 163 460 12.4 3230 8.54 49 R.J. Umberger Columbus C 159 420 10.7 2976 8.47 50 Mikhail Grabovski Toronto C 155 402 12.9 2871 8.40 51 Dany Heatley Minnesota RW 162 455 11 3290 8.30 52 Tomas Plekanec Montreal C 158 447 8.7 3240 8.28 53 Anze Kopitar Los Angeles C 157 463 10.8 3369 8.25 54 Patrice Bergeron Boston C 161 402 10.9 2936 8.22 55 David Backes St. Louis RW 164 445 12.4 3256 8.20 56 Dustin Brown Los Angeles RW 164 442 11.3 3242 8.18 57 Martin St. Louis Tampa Bay RW 159 439 12.8 3463 7.61 58 Claude Giroux Philadelphia RW 159 411 12.9 3250 7.59 Kennedy sticks out like sore thumb in this group, too, so I see how his ability to generate shots on goal could have sent his ranking to a level that no one would have anticipated. That doesnt mean, however, that the idea behind the rating system isnt a good one. Refining, and including power play and penalty-killing values, could eventually present a list that seems more representative of player values and, at that point, can be utilized to help find assets that may be undervalued. Im a sucker for player rankings, having provided them on TSN.ca for more than a decade, so I will readily keep tabs on further developments in this field. Of course, my frustration from the get-go with the Sloan Conference is that NHL teams dont seem to be as accepting of analytics as I am. Im numbers-oriented, pretty much always have been, so I get that Im more open to some of the analysis presented, but Im always hoping for some sign that NHL teams are taking analytics as seriously as teams in MLB and NBA, two sports that seem to be most accepting. Even if Gabe Desjardins, of Behind the Net fame, says that the number of teams hiring a blogger to provide consulting services is growing, that pales in comparison to MLB and NBA teams, at the very least, in which most not only have someone working full-time on analytics but, in more and more cases, have actual analytics teams, so that they might have half a dozen people working on numbers, salaries and player evaluation, trying to find an edge. Eric Tulsky went through NHL team pages and found four teams that employ someone in an official analytics capacity. There are certainly others, with job titles that dont necessarily include analytics, but its not like its the industry standard for an NHL team to have a full-time analytics staff. By my count, there were six teams (Dallas, Edmonton, Minnesota, Tampa Bay, Vancouver and Washington) represented at this years conference by someone in hockey operations, so Im left feeling like theres a lot of room for growth, both in the conferences hockey content and in NHL teams willingness to consider analytics as part of their everyday operations. I dont know if the cost makes sense to have six or seven analysts, but it remains unfathomable to me that teams dont, as standard business practice, pay $100,000 or $200,000 a year to a couple of people who can help them make better decisions on payrolls that are between $50-million and $70-million a year. While there werent any official hockey panels convened at Sloan, there were several informal gatherings both Friday and Saturday night. Schuckers and Brian Macdonald have been trying to push hockey analytics at the conference in the three years Ive attended, so I enjoy discussing their analysis. It was good to meet Tulsky, a chemist in the real world, who sees how much room for improvement there is when it comes to the use of analytics in the NHL. NHL statheads can dare to dream, right? Scott Cullen can be reached at Scott.Cullen@bellmedia.ca and followed on Twitter at http://twitter.com/tsnscottcullen. For more, check out TSN Fantasy on Facebook. cheap nfl jerseys ' ' '