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With the exception of elite skilled players, the gap between skillsets from the third line – and sometimes the second – are closely resembling that of depth players. Skills development and tactical deployment are dependent on the interchangeability of players moving up and down the roster. Assessing first line players – which is fairly consistent whether using data and/or video and live views, but assessing talent down the roster possesses challenges.
As an example, puck moving defensemen were recently studied by Harman Dayal and Dom Luszczyszyn, to measure their impact in all three zones and produced good results, using data from InStat Hockey – an invaluable resource to the hockey community.
Another solid resource is by Greg Revak – also part of the McKeen’s Video Room team with Will Scouching and Sam McGilligan – putting the skills components on display on the daily in the Hockey Arsenal newsletter and Hockey IQ Podcast.
Evaluating individual skillsets for players – which may have been the predominant methodology leading up to the past four or five seasons – is giving way to single-digit metrics. The change of focus coincides with player effectiveness in game situations and not necessarily on the player’s skill set. Teams (and players) can be taught to use skills and tactics through coaching and developmental plans. On-ice execution can be measured differently and sometimes pushes players into lines and situations that would not have been expected. I find that Zach Hyman benefitted greatly by using this methodology and showing his worth on any line, while upgrading his skills to coincide with the uptick in responsibility. He embodies the ‘fine wine with age’ narrative.
Assigning single digit metrics changes the focused methodology to assess player impacts. It’s not all about individual skillset, in so much as how much the player is contributing to a particular aspect of winning.
Goals are the path to winning – scoring more, and not giving up as many. Measuring a player’s impact on goals above a baseline – replacement level players – normalizes the individual skillset to the measurement.
A replacement level player would amount to a recent call up or the 13 forward, and 7th defenseman. Any position where a replacement level player could be inserted, we can measure the player in that spot relative to the replacement level capability.
Originating from baseball, wins above replacement – how many wins does a player affect above a replacement level player is the natural progression, but we aren’t going to use WAR – for a reason we shall soon discover.
On the Evolving Hockey site, they capture SPAR, standing points above replacement, which is the individual effect of the player on standing points in a single number. I like the idea of measuring a player’s ability to affect standing points – and all the effects on teams in bubble playoff spots. How much can they influence the game? Goals and wins leave components on the table that can skew actual performance metrics – such as three point games affecting wins, or piling on goals in a 3-1 game to make it 5-1 or 6-1, meaningless in the overall scheme, despite padding the individual stats.
This article on Raw Charge is an excellent explainer of why to use SPAR over WAR – as would traditionally be the next metric. This gets to the heart of the reasoning.
This exercise is rather interesting once you move past the obvious tier of top players. Now, bear in mind we are one quarter into a brand new season, so small samples will create obvious outliers, so included in the rankings are the last 3-year SPAR. A full blown explanation of the model in use can be found here. For our purposes here, we are going to look at some first quarter results in groups of 10.
Leading the pack is the never breaking Russian, Alex Ovechkin, with 3.2 standing points, coming close to expectations (marked by xSPAR). His 3 year SPAR (the accumulation of standing points over the past three seasons) only amassed 5.8 standing points – his best of the three years coming in 2018-19 (2.8).
For the players shown in the tables below, the highest effect on standing points was a SPAR of 0.235 per 60 minutes. The average amongst the best SPAR/60 rates is 0.14 per 60 minutes.
| Player | Team | SPAR | Xspar | 3-yr SPAR |
| WSH | 3.2 | 3.3 | 5.8 | |
| EDM | 3.0 | 4.0 | 17.3 | |
| COL | 2.8 | 2.0 | 11.1 | |
| CGY | 2.8 | 1.3 | 8.9 | |
| TOR | 2.6 | 2.8 | 14.0 | |
| CGY | 2.5 | 1.0 | 10.9 | |
| COL | 2.5 | 0.7 | 9.3 | |
| ANA | 2.4 | 3.1 | 5.0 | |
| MIN | 2.4 | 3.2 | 5.5 | |
| WSH | 2.4 | 0.6 | 8.2 |
Beyond the stars, Anaheim Ducks Troy Terry enjoying a breakout early this season is actually lagging his expected SPAR. The Capitals, and Nick Jensen is the first defenseman to appear on this list at 10 as he’s enjoying a brilliant start to the 2021-22 season. Of note, Gabriel Landeskog has contributed 2.5 standing points despite the 0.7 expected SPAR. We shall see this similarity in a teammate further down the list.
In the next tier we find some exceptional names like Tom Wilson and Tony DeAngelo, sharing the spotlight with a renaissance year by Matt Duchene. The Flames Oliver Kylington has been red hot to start as the Flames keep rolling hard over the first quarter.
| Player | Team | SPAR | Xspar | 3-yr SPAR |
| BOS | 2.4 | 1.4 | 15.5 | |
| WSH | 2.3 | 1.9 | 5.0 | |
| S.J | 2.3 | 2.5 | 7.9 | |
| CAR | 2.3 | 2.4 | 6.1 | |
| OTT | 2.3 | 1.1 | 7.4 | |
| NSH | 2.2 | 3.6 | 10.3 | |
| CGY | 2.2 | 2.7 | -0.9 | |
| Alex Kerfoot | TOR | 2.2 | 1.2 | 4.8 |
| EDM | 2.2 | 3.3 | 22.5 | |
| EDM | 2.1 | 0.1 | 9.1 |
I would have expected David Pastrnak to be placed higher on this list, but he’s leading his expected SPAR by one, and his aggregated 3-year SPAR is only second to Leon Draisaitl sitting at number two position on this list. Both players are once again eclipsed by Connor McDavid’s 22.5 – while only affecting 2.2 SPAR so far this season.
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In this next tier we get to see one of the biggest disparities in Nazem Kadri. The ex-Leaf has been en fuego affecting 2.1 standing points, outpacing expectation of 0.8, similar to his teammate Landeskog.
| Player | Team | SPAR | Xspar | 3-yr SPAR |
| COL | 2.1 | 0.8 | 4.9 | |
| STL | 2.1 | 3.3 | 8.7 | |
| NYR | 2.1 | 2.9 | 8.4 | |
| FLA | 2.1 | 2.7 | 10.8 | |
| CGY | 2.1 | 3.7 | 8.5 | |
| BOS | 2.0 | 2.3 | 18.1 | |
| N.J | 2.0 | 2.2 | 4.8 | |
| EDM | 2.0 | 1.2 | 2.8 | |
| FLA | 2.0 | 2.1 | 13.1 | |
| T.B | 2.0 | 1.6 | 19.8 |
Adam Fox and Aaron Ekblad are the lone defensemen in this final tier, but the name to keep a close eye on is Andrew Mangiapane. The Flames forward grew into a respected player in 2020-21, and has become a downright force for the Flames early in 2021-22.
Braydon Point would likely have placed higher as well, but his injury status will likely stall his production and he will fall down the rankings as expected.
Overall, the impact an individual player exhibits on the ice is generally reflected in usage and moving up or down depending on the performance. Instead of simple box score stats to determine effectiveness, encapsulating underlying metrics for a single metric is beneficial, especially of the areas between skills assessment continue to close ranks.
