#is the 4th picture rantanen

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It's my favorite gretzky picture! Hockey players hockeying...

[thrashermaxey]

Cage Match: Mikko Rantanen vs. Sebastian Aho

  As the 2018-19 season unfolds, we see changes in fantasy status of many players, from former stars now barely deserving of a roster spot, to youngsters coming into their own. Perhaps the most significant is players graduating from being very good fantasy assets to true fantasy studs. That’s what appears to be happening with this week’s combatants – Mikko Rantanen and Sebastian Aho. Which one projects to have a more successful 2018-19, and who stands to be better long term? Cage match is on the case!

Career Path and Contract Status

Rantanen, 21, was the 10th overall selection in the 2015 draft and starred in the AHL (60 points in 52 games) that same season after a nine-game trial with the Avs. For 2016-17 he averaged barely better than a point per every other game (38 points in 75 contests); but half of those points came in his final 33 games, leading many to expect a progression in production for 2017-18. What he did instead was break out big time, tallying 84 points after finding great chemistry with Nathan MacKinnon, but concerningly faltering (three points in eight games) when MacKinnon was out of the lineup. Yet so far this season he’s been nothing short of spectacular, currently sitting atop the NHL’s scoring leaders.

Aho, also 21, was selected 35th overall in the same 2015 draft and came stateside following a point per game (45 points in as many games) in his age-18 season in the Finnish Elite League. Aho spent no time in the AHL, suiting up for the Canes for 2016-17 and posting 49 points, with 15 coming in his final 23 games such that there were high expectations for him as well going into last season. And although Aho didn’t explode to the extent Rantanen did, he did post 65 points in 78 games, with 61 coming in his final 69 contests. That alone would’ve had poolies expecting great things from Aho this season; however, it was his 18 points in eight games performance at the spring IIHF World Championships that led many to expect him to have a truly elite 2018-19, which has indeed been the case thus far as he had the NHL’s longest streak of games (12) with at least one point to start the 2018-19 campaign.

Both players are in the last season of their ELCs, before becoming non-arbitration eligible RFAs, with Aho earning slightly more ($0.925M vs. $0.894M) this season as compared to Rantanen.

Ice Time (Data for 2018-19 in this and the other tables reflects games played through November 5)

Season

Total Ice Time per game

(rank among team’s forwards)

PP Ice Time per game

(rank among team’s forwards)

SH Ice Time per game

(rank among team’s forwards)

2018-19

20:54 (M.R.) – 2nd

19:46 (S.A.) – 2nd

4:23 (M.R.) – 2nd

3:33 (S.A.) – 1st

0:02 (M.R.) – 12th (tied)

0:30 (S.A.) – 6th

2017-18

18:58 (M.R.) – 3rd

17:55 (S.A.) – 2nd

3:44 (M.R.) – 1st

2:41 (S.A.) – 1st

0:01 (M.R.) – 13th

0:02 (S.A.) – 10th

2016-17

18:03 (M.R.) – 4th

16:47 (S.A.) – 5th

2:43 (M.R.) – 2nd

2:13 (S.A.) – 4th

0:05 (M.R.) – 13th

0:13 (S.A.) – 9th

For 2016-17 and 2017-18 we have straightforward ice time progression gains and corresponding scoring jumps made by the players. For 2018-19, the number that jumps off the page is Rantanen’s power-play time. It’s bound to drop, right? Maybe not much, if at all. Last season the Avs led the NHL in PP opportunities with 296. To date for 2018-19 they’re on pace for 293, and their team philosophy remains to lean on a PP1 unit. In fact, Rantanen took the ice for 62.9% of Colorado’s PP minutes in 2017-18, but this season he’s up to a whopping 69.8%. Thus, Rantanen is in a true power-play sweet spot which, along with his higher overall ice time, seemingly helps justify his 2018-19 scoring gains.

Looking at the same metrics for Aho, in 2017-18 Carolina was one of six teams which failed to receive 240 PP opportunities. Not only that, but their former coach divvied up power-play time quite evenly, resulting in Aho being team forward PPTOI leader at a mere 2:41 per game, which was fifth lowest among forward team leaders for all 31 teams.

This season Carolina’s power-play opportunities per game are way up (on pace for 298), perhaps manifesting a different approach implemented by new coach Rod Brind’Amour. Beyond that, Brind’Amour seems to be embracing a change in allocating man advantage minutes, as Aho is still team leader among forwards but now is taking the ice for 58.9% of the team’s total power-play time, which, although not nearly in Rantanen’s stratosphere, is still up a good bit from 53.7% last season. As such, Aho should see his PP scoring rise, and, in turn, find points where he didn’t last season. Still though, advantage to Rantanen here.

Secondary Categories

Season

PIMs

(per game)

Hits

(per game)

Blocked Shots (per game)

Shots

(per game)

PP Points

(per game)

2018-19

0.85 (M.R.)

0.43 (S.A.)

1.14 (M.R.)

0.78 (S.A.)

0.85 (M.R.)

0.64 (S.A.)

2.28 (M.R.)

2.71 (S.A.)

0.35 (M.R.)

0.28 (S.A.)

2017-18

0.42 (M.R.)

0.30 (S.A.)

0.39 (M.R.)

0.83 (S.A.)

0.49 (M.R.)

0.21 (S.A.)

2.19 (M.R.)

2.56 (S.A.)

0.43 (M.R.)

0.20 (S.A.)

2016-17

0.29 (M.R.)

0.31 (S.A.)

0.38 (M.R.)

0.62 (S.A.)

0.44 (M.R.)

0.17 (S.A.)

1.77 (M.R.)

2.61 (S.A.)

0.13 (M.R.)

0.19 (S.A.)

Seeing Rantanen’s SOG rate is surprising, as I expected it to be considerably higher. After all, while there are pass-first centers that score a lot without shooting a ton, normally wingers who fill the scoresheet also pepper the net with lots of shots. Need proof? Since 2005-06 there’ve been 54 instances of wingers who posted 85+ points but just one (Brad Marchand last season) did so without 200+ SOG and only three without 225 SOG. That’s concerning since in his breakout season Rantanen had a mere 178 SOG and he’s at a 186 SOG pace thus far this season. Although past results don’t automatically bear upon the present or future, this is concerning data in terms of Rantanen – notwithstanding his red-hot start to 2018-19 and superb PP deployment – being much more than a point-per-game player.

Aho doesn’t have that problem, having fired 200+ SOG in both his full NHL seasons. But he too isn’t exactly an SOG monster, although at least in his case he’s on pace for his highest rate this season, leaving hope his SOG rate isn’t done rising and he can continue his scoring ascent.

Rantanen achieved 84 points last season in large part by tallying 35 on the PP. The good news is that shows he can succeed with the man advantage and likely explains why he’s out there even more this season. But can wingers who take less than 200 SOG and score less than 30 goals really be perennial 30 to 35+ point PPPt scorers? It turns out there’s precedent for an age 22 or younger winger who tallied 35+ PPPts without also scoring 30+ goals or firing 200+ SOG in Ales Hemsky, who went on to twice more have 30+ PPPts without 200 SOG. And Hemsky might have done even better had his career not been derailed by injuries.

As for Aho, his improved power-play deployment has led to more PPPts thus far. Perhaps as important, he still has room for further realistic gains there. And he – as well as poolies who own him – better hope those gains occur if he’s to become a truly elite fantasy forward. After all, of the 70 total instances of 90+ point scorers since the 2005-06 season, only one (Connor McDavid last season) accomplished the feat without at least 25 PPPts in the same campaign, and just ten did so without 30+ PPPts.

As for other multi-cat contributions, Rantanen had nearly identical rates for penalty minutes, hits and blocks in past seasons, which means we can likely chalk up his elevated numbers for 2018-19 thus far as short-term variance. As for Aho, in the past two seasons he had comparable penalty minutes to Rantanen, was much worse in blocks, yet better in hits. Overall neither player will help win these categories but – notwithstanding Rantanen’s unsustainable early numbers for this season – are likely average to only slightly below average in these areas for top scorers.

Luck-Based Metrics

Season

Personal Shooting %

Team Shooting % (5×5)

Individual Points % (IPP)

Offensive Zone Starting % (5×5)

Average Shot Distance

Secondary Assists %

2018-19

15.6% (M.R.)

10.5% (S.A.)

15.2% (M.R.)

10.7% (S.A.)

80.0% (M.R.)

81.0% (S.A.)

55.7% (M.R.)

55.2% (S.A.)

34.3 (M.R.)

27.8 (S.A.)

42% (M.R.)

46% (S.A.)

2017-18

16.3% (M.R.)

14.5% (S.A.)

9.80% (M.R.)

8.97% (S.A.)

69.4% (M.R.)

73.9% (S.A.)

56.8% (M.R.)

54.9% (S.A.)

29.9 (M.R.)

29.9 (S.A.)

47% (M.R.)

33% (S.A.)

2016-17

15.0% (M.R.)

11.2% (S.A.)

8.08% (M.R.)

7.21% (S.A.)

56.7% (M.R.)

70.0% (S.A.)

50.3% (M.R.)

53.6% (S.A.)

24.6 (M.R.)

25.2 (S.A.)

44% (M.R.)

52% (S.A.)

Make no mistake – Rantanen’s team shooting percentage is unsustainable; however, his IPP, while perhaps a bit too high, is keeping with his trend of it rising with each passing season. Although Rantanen hasn’t made a name for himself as a goal scorer, his personal shooting percentage is especially high for someone whose average shooting distance is nearly 35 feet, making it – along with his SOG rate – less likely he’ll morph into a goal scorer over the course of this season and perhaps down the road. As a whole, I’d say his data is in keeping with the picture of a player whose current spot atop the league’s scorers isn’t sustainable, but for whom better production than last season can reasonably be expected.

Turning to Aho, he too has a high IPP this season; but in his case it’s less far above what it had been last season and is also continuing an upward trend. Thus, it could stay this high or perhaps drop only slightly. It’s also likely Aho will see more goals as the season unfolds, since his personal shooting percentage is down despite his average shooting distance being lower. His team shooting percentage also has risen each season, but thus far is likely at least somewhat unsustainably high. Between that and his also high percentage of secondary assists, he too should see his scoring rate slip from where it is now.

Who Wins?

In terms of raw talent, I believe these players are more comparable than not. But opportunity trumps talent in fantasy hockey, making Rantanen the winner of this match.

Is Rantanen’s NHL scoring lead sustainable? Unlikely – not with his very high team shooting percentage to go along with his low (for a winger) SOG rate and the historical data which very clearly shows the nexus between high scoring wingers and firing lots of pucks on net. But Rantanen’s PP prowess is indeed for real and what ends up winning him the match. After all, if things unfold for the rest of the season (and in future seasons) on the PP the way they have this season and last, Rantanen should best Aho by at least five man advantage points each season. Add to that the benefit of Rantanen having a world class center on his line, whereas Aho is clearly his team’s best player, and – not to take anything away from Aho – Rantanen is the winner of this battle.

Even still, I’d peg Aho as an 80-85 point player for this season and the next several, with a shot at 90 points if he’s surrounded by more talent and continues to gets better PP deployment. Rantanen, on the other hand, should be able to sleepwalk to 90 points with a realistic chance at more. If you own either player in your keeper league, I’d only sell to fill a big hole at another position and if you’re also getting back as close to guaranteed value as possible. In one-year leagues, it’s best to hold since although both will likely see their scoring pace slow from where it is now, they’re still key pieces to any team seeking to win its league.

from All About Sports https://dobberhockey.com/hockey-home/cage-match/cage-match-mikko-rantanen-vs-sebastian-aho/

[thrashermaxey]

Cage Match: Kyle Palmieri vs. Gabriel Landeskog

It’s time for yet another battle between players with similar projections in the Fantasy Guide (which is still available for order here). This time it’s Kyle Palmieri, coming off his third straight season with a full season scoring pace of 54 to 58 points, against Gabriel Landeskog, who reversed a several season trend of diminishing points by tallying 62 in 2017-18. Who’s the better own this season and down the road? Cage Match is on the case and starts now!

Career Path and Contract Status

Landeskog, 25, was drafted second overall in 2011 and went straight to the NHL, where he posted a very respectable 52 points as a rookie. In his next full season (2013-14) he upped his total to 65, and poolies envisioned him on the fast track to stardom. Little did they know at the time, however, that Landeskog would amazingly see his point total drop in each of the next three seasons, first to 59, then 52, then all the way to 33 in 2016-17. But as alluded to above, last season he – like other Avs – reignited, and his scoring climbed all the way back to 62 points, with 18 of those points coming in his final 21 games.

Palmieri, 27, was selected 26th overall in 2009 and played one year of college hockey before jumping into the pro ranks. Despite 134 points in 146 AHL games, Palmieri couldn’t find a home in the Ducks’ line-up until 2013-14. Once in the NHL, he didn’t take things by storm, with less than point per every other game output through his first two seasons (60 points in 128 games). But all that changed once he was traded to his hometown Devils, with whom he posted 57 points in 2015-16 and 53 in 2016-17. Last season he played only 62 games, yet his full season scoring pace was 58 points and he too finished strong, amassing 30 of his 44 points in his final 41 games.

Both players are signed through 2020-21, with Landeskog’s cap hit ($5.571M) being nearly 25 percent more than Palmieri’s ($4.65M). Both will be UFAs upon the expiration of their current deals.

Ice Time

Season

Total Ice Time per game

(rank among team’s forwards)

PP Ice Time per game

(rank among team’s forwards)

SH Ice Time per game

(rank among team’s forwards)

2017-18

20:09 (G.L.) – 1st

17:19 (K.P.) – 4th

3:35 (G.L.) – 3rd

2:47 (K.P.) – 4th

1:07 (G.L.) – 6th

0:42 (K.P.) – 8th

2016-17

18:47 (G.L.) – 2nd

17:21 (K.P.)- 4th (tied)

2:21 (G.L.) – 4th

2:38 (K.P.) – 2nd

1:47 (G.L.) – 2nd

0:57 (K.P.) – 7th

2015-16

18:56 (G.L.) – 1st

17:48 (K.P.) – 5th

2:45 (G.L.) – 5th

2:38 (K.P.) – 5th

1:26 (G.L.) – 5th

0:38 (K.P.) – 7th

2015-16

18:30 (G.L.) – 3rd

14:06 (K.P.) – 10th

2:29 (G.L.) – 3rd

1:43 (K.P.) – 6th

0:28 (G.L.) – 8th

0:00 (K.P.)

When I saw Palmieri’s scoring rate had been virtually constant in New Jersey, I figured his ice times nevertheless might’ve varied season to season; yet as we can see they were constant too. And when I say constant I really mean constant, with his total varying less than 0:30 and his power-play time less than 0:10. Moreover, even as he was red hot at the end of last season he was still getting the same power-play and total ice times, suggesting he might’ve benefitted from unsustainable good luck over the short haul.

For Landeskog, it makes sense from what we see here that 2016-17 was his statistically worst season. Moreover, his ice times from 2017-18 were up enough from 2014-15 and 2015-16 to justify a jump into 60+ point territory rather than the 50s for those seasons.

In all, this data for both players is apparently straightforward. Even still, their SOG and PPPts metrics could show there’s more to things than what seemingly meets the eye, so let’s dissect those now.

Secondary Categories

Season

PIMs

(per game)

Hits

(per game)

Blocked Shots (per game)

Shots

(per game)

PP Points

(per game)

2017-18

0.47 (G.L.)

0.48 (K.P.)

1.91 (G.L.)

1.51 (K.P.)

0.65 (G.L.)

0.80 (K.P.)

2.34 (G.L.)

2.92 (K.P.)

0.22 (G.L.)

0.37 (K.P.)

2016-17

0.86 (G.L.)

0.57 (K.P.)

1.98 (G.L.)

1.55 (K.P.)

0.57 (G.L.)

0.45 (K.P.)

2.34 (G.L.)

2.40 (K.P.)

0.08 (G.L.)

0.23 (K.P.)

2015-16

0.92 (G.L.)

0.47 (K.P.)

1.88 (G.L.)

1.57 (K.P.)

0.88 (G.L.)

0.62 (K.P.)

2.25 (G.L.)

2.70 (K.P.)

0.18 (G.L.)

0.28 (K.P.)

2014-15

0.96 (G.L.)

0.65 (K.P.)

2.06 (G.L.)

1.70 (K.P.)

0.89 (G.L.)

0.42 (K.P.)

2.61 (G.L.)

1.96 (K.P.)

0.20 (G.L.)

0.19 (K.P.)

Again, Landeskog’s 2016-17 would be expected to be his poorest season based on what we see here. Combine that with the lack of offense from the Avs that season, and it helps at least partially explain why he cratered to 33 points. Moreover, Landeskog had a slightly better output in PPPts in 2017-18 than 2015-16 and 2014-15. So here as well, his scoring trajectory appears to check out.

For Palmieri, despite him being a consistent top power-play performer, he saw his power-play scoring jump to a new stratosphere in 2017-18, along with his SOG rate. And sure enough all this came in the second half of 2017-18, during which he amassed 14 of his 23 PPPts and fired 115 of his 181 shots on goal. The question is whether poolies should see this as Palmieri – at age 27 – taking the next step and becoming a 65+ point player, or instead just a run of unsustainable good luck. Given his age, and with his ice time not jumping to match the increases, chances are this is good luck that won’t continue, but we’ll examine that next.

But before doing that, it’s worth examining their multi-cat contributions. As most poolies are already likely aware, Landeskog was a multi-cat stud. In fact, if we combine his outputs from the 2014-15 and 2015-16 seasons, there was no player who had more penalty minutes, hits, blocks and SOG per game than him, with only Ryan Kesler and David Backes besting him in three of the four categories (PIM, Hits, Blocks). And although Landeskog’s contributions in all but hits have come down somewhat, there’s no question he’s still a huge multi-cat asset.

As for Palmieri, he’s dropped penalty minutes with each passing season but his hits have remained nicely at or slightly above the 1.5 per game mark and 2017-18 saw him post his highest power-play points, shots and blocks. Long story short, these are players who you look for an excuse to draft in multi-cat leagues.

Luck-Based Metrics

Season

Personal Shooting %

Team Shooting % (5×5)

Individual Points % (IPP)

Offensive Zone Starting % (5×5)

Average Shot Distance

Secondary Assists %

2017-18

13.7% (G.L.)

13.3% (K.P.)

10.11% (G.L.)

7.93% (K.P.)

51.2% (G.L.)

62.0% (K.P.)

54.0% (G.L.)

52.7% (K.P.)

27.8 (G.L.)

28.2 (K.P.)

50% (G.L.)

59% (K.P.)

2016-17

10.7% (G.L.)

13.5% (K.P.)

6.24% (G.L.)

9.05% (K.P.)

67.3% (G.L.)

67.9% (K.P.)

47.6% (G.L.)

46.5% (K.P.)

29.6 (G.L.)

28.9 (K.P.)

50% (G.L.)

54% (K.P.)

2015-16

11.8% (G.L.)

13.5% (K.P.)

7.89% (G.L.)

7.80% (K.P.)

69.7% (G.L.)

75.0% (K.P.)

52.2% (G.L.)

42.6% (K.P.)

32.1 (G.L.)

31.0 (K.P.)

43% (G.L.)

46% (K.P.)

2014-15

10.7% (G.L.)

12.5% (K.P.)

8.97% (G.L.)

8.65% (K.P.)

70.2% (G.L.)

72.5% (K.P.)

43.1% (G.L.)

49.3% (K.P.)

29.9 (G.L.)

26.8 (K.P.)

37% (G.L.)

53% (K.P.)

Focusing first on Palmieri, we see that his OZ% was a good bit higher for 2017-18 than past seasons; but unfortunately we can’t tell if that was the case all season long or weighted toward the end of the season when he was red hot. That being said, his IPP was a bit lower than his norm, which might have been a function of playing on a line with more talented players. The good news is he has a strong history of high IPP, so chances are even if he was to stay with those same players his share of points would rise at least slightly. What might balance that out in a negative way, however, is his 60% secondary assists percentage from last season, which indicated that he likely lucked into at least a few more points than he deserved. In all, this paints the picture of a player whose hot play at the end of the season wasn’t entirely unsustainable, yet also someone who, due to his history of consistent scoring on New Jersey, shouldn’t be expected to score much more than 60 points this coming season or in the near future.

Here too we see evidence as to why Landeskog’s 2016-17 was such a disaster, since as his scoring was cratering so too was his 5×5 team shooting percentage, which spiked last season thanks in large part to the line he was on. The good news is that line likely can stay in that high of a range; however, the bad news is if Landeskog was to remain on the line his IPP probably would stay in the low 60s due to the talent and ability to hit the scoresheet of his linemates Nathan MacKinnon and Mikko Rantanen. Also, Landeskog’s higher than normal secondary assists percentage last season further suggests he’s more of a space occupier on that line as opposed to a strong contributor. Accordingly, he probably shouldn’t be counted on for additional points this coming season and beyond, and perhaps even fewer, due to the talent around him and his inability to insert himself – as compared to them – into the scoring picture.

Who Wins?

Because for the most part the story checked out for each player, we should expect them to score roughly the same in 2018-19 as they did in 2017-18, with Palmieri perhaps receiving a slight boost in production to put him closer to Landeskog’s 62 point tally from last season. But here’s the thing – even if Palmieri wasn’t in line for a possible uptick in scoring, I’d nevertheless declare him to be the winner here, and it’s based on cost vs. value.

Landeskog’s cost had cratered; however, with his resurgence as part of one of the hottest and highest profile lines in hockey last season, not to mention poolies recalling Landeskog’s status as a former top two draft pick, the result will be expectations for him to score even more points this season than last. As such, his cost – which arguably would’ve already been higher than Palmieri’s – will climb even higher. Look no further than Yahoo drafts conducted thus far, which have Landeskog as, on average, the 100th player being selected, and Palmieri much farther down at 164th. Although to some extent Landeskog’s higher cost factors in his slight edge in multi-cat, it’s still too large of a gap for two players who likely will produce comparable scoring. As such, Palmieri is the winner of this match because he can provide you with comparable – or close to comparable – scoring output as Landeskog for a far lower price to draft and, presumably, in trade as well.

The gap is even wider in points-only leagues, whereas in dynasty keepers it shrinks a bit due to Landeskog being two years younger. You’d be justified in holding both players in keepers, although if someone was to blow you away with a trade offer for Landeskog that values him as a 70+ point player, you’d probably want to take that offer.

from All About Sports https://dobberhockey.com/hockey-home/cage-match/cage-match-kyle-palmieri-vs-gabriel-landeskog/

[thrashermaxey]

Fantasy Cage Match: Barzal vs. Draisaitl

This is one of my favorite times of year for Cage Matches, since I have enough season-long data to see if breakout players are for real or simply enjoying a long but ultimately unsustainable spike in production. Case in point is Mathew Barzal, who, although always highly touted, has already far and away exceeded rookie expectations. Taking on Barzal is Leon Draisaitl, who might be in the midst of one of the quietest 75-80+ point seasons in recent memory. Which of these two should you want to own in fantasy? Cage Match is here to lead you down the correct path.

  Career Path and Contract Status

Barzal, 20, was selected 15th overall in 2015 after posting 54 and 57 points in two WHL seasons. The Isles opted to let him stay in juniors for two more seasons, which saw Barzal post a collective 167 points in a mere 99 games, signifying he was NHL ready. Sure enough he broke camp with the big club this season tabbed as its second line center; after a somewhat slow October (7 points in 12 games), he’s posted 12+ points per month of the season, plus tallied a remarkable three separate five point games.

Draisaitl, 22, was picked third overall in 2014 after posting 105 points in 64 OHL games. He was ticketed to Edmonton right away but struggled (nine points in 37), leading him back to juniors, where he once again shined (53 points in 32 games). The 2015-16 campaign saw Draisaitl stick in Edmonton, where he emerged with 31 points in 28 games and posted 51 for the season. He built on that with 77 points last season, and in 2017-18 might hit the 80-point mark for the first of what could be many occasions.

Barzal is arguably one of hockey’s best bargains, playing on an ELC that runs through 2020-21 and dings the cap at $0.863M per season. Draisaitl’s cap hit is a lofty $8.5M per season through 2024-25.

Ice Time (data in this and the other tables is current through March 12th)

Season

Total Ice Time per game

(rank among team’s forwards)

PP Ice Time per game

(rank among team’s forwards)

PP Ice Time per game

(rank among team’s forwards)

2017-18

17:35 (M.B.) – 3rd

19:17 (L.D.) – 2nd

3:07 (M.B.) – 1st (tied)

2:43 (L.D.) – 2nd

0:02 (M.B.) – 12th (tied)

0:52 (L.D.) – 7th

2016-17

18:53 (L.D.) – 2nd

2:54 (L.D.) – 2nd

0:25 (L.D.) – 9th

2015-16

18:03 (L.D.) – 4th

2:33 (L.D.) – 6th

0:03 (L.D.) – 12th

  The questions surrounding Draisaitl entering 2017-18 were how dependent his scoring was on playing with Connor McDavid, and could he produce gaudy numbers if/when they played fewer shifts together. After all, last season Edmonton scored 2.52 goals per 60 minutes when Draisaitl played apart from McDavid, versus 3.57 when McDavid was apart from Draisaitl and 4.00 when the two skated together.

  Digging deeper, last season McDavid and Draisaitl shared the ice for roughly 80% of Draisaitl’s even strength (ES) shifts, and Draisaitl tallied 31 of his 50 ES points (i.e., 62%) with McDavid also on the ice. Fast forward to 2017-18, and although they’ve played a good bit less together at even strength (just under 65% of their ES shifts), the percentage of Draisaitl’s scoring at ES with McDavid has stayed nearly the same – 30 of 50 points (i.e., 60%). Thus, Draisaitl is arguably relying on McDavid more to score this season than last.

  But let’s remember, for 2017-18 Draisaitl’s other line mates have been arguably less skilled than last season, with the departure of Jordan Eberle and Ryan Nugent-Hopkins missing time due to injury. Plus, McDavid and Draisaitl are signed for years to come, so if they “need” to play together for one or both to succeed, what’s wrong with that? Look at Patrice Bergeron and Brad Marchand, Sean Monahan and Johnny Gaudreau, or Nathan MacKinnon and Mikko Rantanen. Concern about Draisaitl’s dependence on McDavid is seemingly overblown or, even if true to some extent, shouldn’t scare off poolies.

  As for Barzal, his Ice Time is low for his scoring pace; but with scoring being up for 2017-18, it now takes less TOI to score as many points. To illustrate, Barzal’s points per 60 minutes is 3.41, ranking him just outside the top ten for 2017-18. But it also puts him within the top 25 for all skaters who played in 60+ games in any season since 2010-11! In fact, 14 of the top 30 instances of 60+ game forwards in P/60 since 2010-11 are from 2017-18. Thus, what was once thought impossible (or highly unlikely) in terms of TOI and production is now seemingly possible, provided scoring stays high in future seasons. Beyond that, Barzal is in an Ice Time sweet spot, with almost no SH duty and a high percentage of PP Time, plus a low enough overall Ice Time to ward off concern about a rookie wall.

  Secondary Categories

  Season

PIMs

(per game)

Hits

(per game)

Blocked Shots (per game)

Shots

(per game)

PP Points

(per game)

2017-18

0.34 (M.B.)

0.40 (L.D.)

0.26 (M.B.)

0.54 (L.D.)

0.39 (M.B.)

0.34 (L.D.)

2.17 (M.B.)

2.50 (L.D.)

0.29 (M.B.)

0.12 (L.D.)

2016-17

0.24 (L.D.)

0.50 (L.D.)

0.44 (L.D.)

2.09 (L.D.)

0.31 (L.D.)

2015-16

0.27 (L.D.)

0.52 (L.D.)

0.25 (L.D.)

1.84 (L.D.)

0.12 (L.D.)

  As Draisaitl’s SOG rate has increased, so has his scoring. But his PPP rate is tracking his first full season after being nearly triple that rate last year. Cause for concern? Most likely no, as it’s perhaps due to the Oilers having no real PP QB plus it can’t realistically get any worse, except in the highly unlikely event Draisaitl’s role on the PP is de-emphasized. Think of it this way – if Draisaitl’s PP scoring this season was merely the average of 2015-16 and 2016-17, he’d be headed toward 85+ points. Of course, there could be reason to worry if Draisaitl’s luck metrics – notably his IPP and/or team shooting % – paint the picture of unsustainable good luck this season and/or last. We’ll check on those below.

  Barzal has already reached 50 assists; and if he stays at point per game scoring he’ll be just the fourth forward to meet both criteria as a first-year player since 1995-96, with the others being Alex Ovechkin, Sidney Crosby, and Evgeni Malkin. If we go back to 1990-91, we can add two others, the venerable Teemu Selanne, plus one who doesn’t stack up – Joe Juneau. But I’m not seeing parallels with Juneau and Barzal, since Juneau was a winger playing with a 142-point Adam Oates. In other words, Juneau was along for the ride, while at even strength Barzal plays with no one of the caliber of Oates and thus is making more things happen on his own. In doing so, I’d liken Barzal’s accomplishments more to those of Crosby, whose 102 rookie points were nearly 50 more than any other forward he skated with at ES.

  But before we anoint Barzal the second coming of any of these players, let alone Crosby, we need to realize he’s not cut from the same cloth. In particular, his 2.17 SOG per game is more than a full SOG less than Crosby averaged and nearly that much less than Malkin’s rookie average. If we look instead at forwards who had 55+ assists (Barzal is on pace for 60) and averaged 2-2.5 SOG per game in a season while age 25 or younger since 1995-96, the good news is all ten who met the criteria not only scored 70+ points in that particular season but also at least one other campaign as well. However, although the list includes some fantasy luminaries Joe Thornton, Jason Spezza, Ryan Getzlaf, Doug Weight and Nicklas Backstrom, it also features Ales Hemsky, Josef Stumpel, Scott Gomez, and Paul Stastny. Thus, Barzal’s accomplishments may indeed portend greatness, yet his failure to shoot the puck a lot allows for him also to be rightfully compared to some players who were unable to sustain successful fantasy careers.

  Luck-Based Metrics

  Season

Personal Shooting %

Team Shooting % (5×5)

Individual Points % (IPP)

Offensive Zone Starting % (5×5)

Average Shot Distance

Secondary Assists %

2017-18

13.0% (M.B.)

13.8% (L.D.)

9.44% (M.B.)

9.17% (L.D.)

74.2% (M.B.)

75.3% (L.D.)

52.2% (M.B.)

55.4% (L.D.)

24.8 (M.B.)

24.1 (L.D.)

49% (M.B.)

25% (L.D.)

2016-17

16.9% (L.D.)

9.74% (L.D.)

70.6% (L.D.)

53.2% (L.D.)

20.4 (L.D.)

35% (L.D.)

2015-16

14.3% (L.D.)

8.03% (L.D.)

73.9% (L.D.)

53.8% (L.D.)

23.5 (L.D.)

50% (L.D.)

  The news for Draisaitl is encouraging pretty much across the board. For one, he’s managing to produce just as well this season as last despite sporting lower team shooting and secondary assists percentages. Why might his secondary assists percentage be so low? Probably due in part to the chemistry between him and McDavid, where one of them likely scores from the other’s pass, and vice versa. And this too would be an area that should rise if (when?) the Oilers start achieving more success on the PP.

  Looking at the other areas, things are also rock solid with respect to IPP, with Draisaitl being above the “magic” 70% threshold in each of his full seasons, which is no small task when playing as much as he does with a point magnet like McDavid, who sports a career IPP average above 80%, meaning when a goal is scored with McDavid on the ice in most cases there are at most two other points available for the other four skaters out there with him. So the fact that Draisaitil has managed to stay above 70% for his IPP not only further underscores his chemistry with McDavid, but also his own nose for scoring.

  Barzal’s team shooting percentage is elevated; however, I’d argue that for it to be high despite him being on a line with less talented players is more of a testament to his skill than being the beneficiary of unsustainable good luck. Predictably his IPP is also high; however, if it was to go down that would mean he’d have better players surrounding him who’d also help create more goals, and the net result could be no lost points. In other words, the fact that both his IPP and his team shooting percentages are high is a better sign than if one was high but the other low. His secondary assists percentage is higher than is likely sustainable; but that too isn’t as much of a concern given his circumstances, since if he had more talented line mates some of those could instead be goals or primary assists.

  Who Wins?

  Nothing against Barzal, but Draisaitl wins the match. If Edmonton was having even a halfway decent season both in general (they’re on pace for 228 goals for 2017-18, which would be 15 fewer than last season) and on the PP (they’re converting on 15.2% of the PP chances this season, down sharply from 22.9 last year), we’d likely be looking at Draisaitl making a push for 85+ points. Barzal is having a rookie season for the ages; however, as we saw above his lack of SOG puts him as much at risk of turning into a Stumpel, Gomez, or Hemsky, as it does a Getzlaf, Backstrom, or Thornton.

  If you can parlay Edmonton’s disappointing season and Draistail’s “quiet” 75-80 point pace into getting him for a lower cost than might be expected, you should likely pull the trigger, since the price might not be this low again for the next decade. Barzal is likely a hold, although by the same token if you’re in a non-cap league you couldn’t be faulted if you explored selling him for proven point per game or better value or to upgrade at another position, since given what you likely paid to get Barzal that would be a very good return on investment.

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Recent Cage Matches:

Vegas, Part 1

Vegas, Part 2

from All About Sports https://dobberhockey.com/hockey-home/cage-match/fantasy-cage-match-barzal-vs-draisaitl/