With the NHL season paused, and no live hockey to cover, many a fan’s attention has turned to the past. With 50+ plus NHL seasons played in franchise history, there’s a lot of hockey to look back on when discussing the Flyers, and many great players who us fans have been fortunate enough to possibly see live in person. Obviously, that being said, there will be many names that will have been forgotten, either due to time or relevancy.
This got me thinking…
There have been 575 skaters in the team’s history who have played at least one game with the Flyers, so what does the average of these players’ tenures look like?
Thanks to Hockey Reference, I’ve compiled the career stats of those 575 Flyers who have played at least one game with the club, and done some simple averaging to answer my question. It should be noted that these are only stats that these players compiled while playing for the Flyers, and not in their entire NHL careers.
So, what does the average Flyers’ career look like? Well, if every Flyers’ player in history were one skater, he would have played 126.20 games, totaling 62.40 points (23.40 goals and 38.97 assists if you break down the individual totals).
That seemed…a little low to me, given the depth of talent that have laced up for the organization since 1967. The average Flyer only scores at a rate of 0.3847 points per game, which to put into the perspective of an 82 game season, is roughly 32 points. According to the Pension Plan Puppets model, the average Flyer is an average to poor third line center, or an average to poor second line winger.
Yet, upon further analysis, this makes sense according to distribution theory. I mentioned this next concept in an article I wrote last July about the salary cap, and I think it still holds true now.
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Probability theory states that most items in a set with an assigned value (a third of them) will occur around the median of the data set, creating what is known as a bell curve. However, as I explored with players’ season point totals in relation to salary, equally with the average career, it doesn’t quite work out that way. The graph, instead, seems to follow a Poisson distribution, where the majority of occurrences are at the front of the data set. The X axis represents Flyers’ players career points and the Y axis represents how often the totals occur on a standard distribution. The model also assumes to create more data points than actually exist, in order to extrapolate and predict results given time.
In this case, the distribution works because we not only can assume, but we know that in terms of the value of time, all the data points are independent of each other and are not impacted by each other. Obviously, Bobby Clarke’s career point totals don’t affect what Claude Giroux is doing now. Regardless, the median of the distribution does not equal the largest total of distribution. If that were the case, then most players would fall in between 453 and 756 points, with the average being at 605 career points. Obviously that isn’t true, and we shouldn’t expect that to be true.
Instead, the Poisson distribution tells us that the most likely occurrence is 127.36 points, which could very well be the case in 50 years when more Flyers players have had careers here. This is both more realistic than the 605 mean average that would have been generated under a bell curve model, and also takes into account career length. Obviously not every Flyer has played 10+ seasons with the club. The vast majority of players only factor in to short term careers with the club. Therefore, 62.40 points in 126.20 games sounds about right for the average Flyer.
However, I was then thinking…how does this stack up to other clubs? Well, in terms of career point distribution, theory goes that all clubs, when analyzed, will have a roughly similar curve. However, I’m not concerned with prediction anymore. Would the average Penguin have a better career than the average Flyer? Taking the same measurement process I did at first, here are the average career results for all the other clubs in the Metropolitan division:
Metro Division – Average Career Points
| Team | Games Played | Goals | Assists | Points | Points ajusted to 82 games |
|---|---|---|---|---|---|
| Pittsburgh Penguins | 109.64 | 20.66 | 34.91 | 55.57 | 41.56 |
| New York Rangers | 108.74 | 20.13 | 32.2 | 52.28 | 39.42 |
| New York Islanaders | 129.86 | 23.19 | 38.5 | 61.7 | 38.96 |
| Washington Capitals | 125.12 | 22.16 | 36.93 | 59.09 | 38.73 |
| Carolina Hurricanes | 118.93 | 19.65 | 32.85 | 52.5 | 36.2 |
| New Jersey Devils | 122.28 | 19.97 | 33.44 | 53.41 | 35.82 |
| Philadelphia Flyers | 126.2 | 23.4 | 38.97 | 62.4 | 32 |
| Columbus Blue Jackets | 103.1 | 14.72 | 24.74 | 39.47 | 31.61 |
Perhaps unsurprisingly, the Penguins are at the top, boosted by the incredible careers of players like Mario Lemieux and Jaromir Jagr. The Rangers are also helped by the fact they’re an original six franchise and have had more players historically. Though the Flyers are near the bottom of the table, they aren’t separated from the other teams by too wide a margin. As I thought, nearly every team’s average player career is that of a third liner, give or take.
