2024 NHL Draft: Intro to Playercards, Roadmap, Philosophizing
CBJ Coverage Plan
With this breakdown begins my draft coverage for CBJ. I have caught glimpses of a handful of prospects throughout the year but the large volume of my work was focused on continual video coverage of the Blue Jackets. As such, these viewings only served to give me quick gut reactions.
It’s possible, provided I can carve out the time, to do some more in-depth analysis on some of the prospects. I find Artyom Levshunov and Sam Dickinson both difficult evaluations who play in systems not necessarily conducive to long-term projection so digging into the tape on the team’s systems could help provide some clarity.
At the end of the day, an NHL team is going to have a development staff that will have preferences and strengths. It’s likely that the player selected is one who has the best frame for the organizations development and less in the specific current skills. Still, there’s plenty of work to do before Don Waddell’s first roster construction window opens at the draft.
Largely, the breakdowns will be centered around the resource that is Mitch Brown and Lassi Alanen’s tracking project. They are, as far as I’m concerned, at the cutting edge of tracking detail and I really hope to steal some of their specific techniques as it applies to NHL analysis.
Largely, as with all tracking data, there are sample size issues. Sometimes, you might track a great prospects game. Largely, both Lassi and Mitch do work to mitigate any issues with sample sizes. Mitch highlights players/teams whose numbers are changing and may still have variation with newly tracked games.
Similarly, this data does not account for teammates/competition/role/system, or perhaps most significantly league, which could alter the potential impact of specific stats. Perhaps a player doesn’t have many zone exits because their syste/coach doesn’t ask them to do that.
As far as I know, there hasn’t been any work on adjusting raw impacts but the Z scores on the cards should place them relative to league. Junior leagues are likely highly volatile and change season to season depending on the generation of players, so for now we’ll just have to take most of the data at face value.
Primarily, the absolute best use of playercards and tracking data is to get an idea of the style of player and their strengths/weakness and not purely an end-all evaluation tool.
None of the stats, whether that’s the Overall grade or Expected Goals per 60, suggest Player X is better than Player Y. It’s fair to say that Player X was better at generating scoring chances because of a superior xG/60 in the sample. It provides insight into a player’s style of play and impact in the sample. I find it useful for understanding how a player impacts the game and their ability to do so going forward.
Still, certain metrics, like the Advantages Created, xG Buildup, Offense Involvement, xG and xA1 all could have better predictive power than simply rolling up an NHLe based on points exclusively.
Playercard Glossary
Click the link for a full breakdown written by Mitch Brown himself. Otherwise, I’ll just include some of the more important definitions here.
This is, and I cannot stress this enough, manually tracked data. Each game takes anywhere from two to four hours, dependent on the camera angle, video quality, and more. Sample sizes around eight games up and generally the most stable, and thus, the more usable
Side note, the differences in spelling and style between American English and Canadian English is a constant source of confusion for me. If you ever see or are confused by my interchange of “s” and “c” in the following words, perhaps you’ll understand why.
Overall Offense
The Offence grade reflects a player’s scoring chance generation in the sample. Nine different metrics are weighted (see below for a full list), including volume (i.e., how many scoring chances they get), efficiency (i.e., how many passes into the slot they complete), and adjusting for the quality of their team.
Overall Transition
The Transition grade includes 11 metrics, that also accounts for volume, efficiency, and their impact relative to their teammates. Exits are weighted heavier for defenceman, entries heavier for forwards. That’s not just the result of (arguably) an exit being more valuable for a defenceman, but also sample size. Defencemen are usually more involved in breakouts to forwards having more entry attempts.
Overall Defense
The Defence grade is comprised of different components for forwards and defencemen. For forwards, it’s just break ups (which includes NZ break ups, NZ forced dump ins, DZ break ups, DZ slot pass interceptions, DZ shots against that the player contests) and OZ retrievals. For defencemen, it includes break ups, two rush defence metrics, and DZ retrievals.
For defenders, offence, defence, and transition are weighted equally, with boards-to-middle plays filling out the remainder.
xG/60
Expected goals per 60; the weighted likelihood of a player's shots resulting a goal, based on shot location, shot type, preceding passes, situation, and rebounds
xA1/60
Expected primary assists per 60; the weighted likelihood of a player's passes that resulted in a shot becoming a goal, based on shot location, shot type, preceding passes, and situation
While primary assists are given to players whose shots generate a rebound, that's not the case with this metric -- it exclusively looks at passing
Cross Lane Plays/60
Passes or carries that cross the dot lanes, either going outside-to-in, in-to-out, or cross-ice (outside-to-outside), rated per 60.
Entry Prevention %
The number of entry attempts that target the player that failed, rated relative to team
Defensive Plays/CA
The sum of a player's DZ break ups, slot pass interceptions, opposition shots that they pressured, neutral zone break ups, and recovered dump-ins in the defensive zone, rated per corsi against
Weakside Breakups/60
Since we’ve established that cross-ice passes for entries lead to more offence than straight-ahead ones, it only makes sense to figure out if certain defenders are better at intercepting them. Enter weak side breakups. These are when the weak side (the off-puck defender) intercepts a lateral pass to prevent an entry.
Retrieval Success %
The percentage of a player’s DZ retrievals that resulted in his team’s possession divided their total number of retrieval.
Successful Pinches/60
The combined number of opposition breakout attempts the player denied before the puck crossed the blue line and how often the turned a 50/50 puck battle along the boards into friendly possession, rated per 60 minutes.
Advantages Created/60
The number of times a player beats an opponent to successfully create space for themselves or a teammate, rated per 60 minutes.
Boards to Middle Plays/60
The number of times a player successfully takes the puck from the boards to the inside lane under pressure, rated per 60 minutes.
Off-Puck Assists/60
The number of times a player successfully sets a pick, lifts a stick, or drives the net to draw defenders and create shooting lanes for teammates, rated per 60 minutes.
Game Score/GP
An all-encompassing metric that weights shot contributions, xP1, exits, entries, rush defence, and in-zone defence to measure impact, rated per game – used to measure volume, not efficiency.
Offense Involvement
The player's percentage of the team's total xG that the player either shot or set-up
xG Buildup/60
The basic idea is this: Each breakout pass, entry, forecheck steal, breakup, and more are assigned a value based on their contributions to xG up the rink. Still too complex? This stat measures many of the little things a player does leads to offence – the higher, the better.
Roadmap
For the most part, my work leading up to the draft will be ordered by quality of players. Since Brown and Alanen’s expanded player cards come in a pair-comparison view (though separated by North America and Europe), and the prospects align somewhat well in that respect, this won’t be a perfect rank-order (partially because I also don’t have a thoroughly ranked order to begin with).
Primarily, the objective will be to pit players tracking data against similar position/value. The potential stylistic and performance tradeoffs of players with similar resumes or positions. Again, this isn’t a perfectly ordered ranking and will be far from a comprehensive preview of all of the players.
The plan, at least for this point, is to cover in the following order, depending on length these could be combined into multiple prospect thematic posts or not (like interesting European Pro League Defensemen), I have no idea:
Celebrini/Lindstrom
Demidov/Helenius
Levshunov/Buium
Catton/Iginla
Dickinson/Parekh
Yakemchuk/Mateychuk (no other good pair from CHL)
Interesting European Pro League Defensemen
Silayev/Jiricek
Solberg/Badinka
Potential Look into Past Top D: Jiricek, Seider, Heiskanen, Reinbacher
Brandsegg-Nygard/Chernyshov
Sennecke/Greentree
Hage/Boisvert
Solberg/Badinka
Late First Round/Potential 2nd Round Faller Forwards
Luchanko/Beaudoin
Stiga/Basha
Pettersson/Eriksson
Other Interesting D
Elick/Emery
Pitner/Kleber
Hutson/Brunicke
Pulkinnen/Shuravin
Muggli/Freij
Danford/Fryer
Later Round Forwards
Humphreys/Caswell
Montgomery/Powell
If there are any other prospect cards anyone would like a look at, I’d be happy to take requests and see what I can spin up prior to the draft.
Closing Comments
Primarily, my analysis will be centered around the Blue Jackets’ needs and wants but that is always tenuous especially at high picks. My personal philosophy is to always pick the Best Player Available but that you also have to acknowledge that the draft is, at its fundamental level, asset acquisition.
As such, I prioritize Eliteness and Uniqueness with special considerations to attributes like hockey sense, skating and competitiveness or other tentpole abilities. At the end of the day, certain player archetypes are rare assets in the league. Projecting 17 and 18 year olds is always difficult and largely percentage based which is why development should be highly prioritized.
Certain player archetypes are more rare assets which means they will likely hold value in the event that we’d like to later reshape our team. This means that certain players, like Juraj Slafkovský, can still be good picks even if their ceilings appear to be lower simply because there aren’t many players in the NHL like them.
This, however, is folded back into “eliteness”. An elite player is someone who can regularly generate wins, or winning conditions, for their teams. There are a variety of ways to beat any team but having a routinely enforceable identity can go a long way (think of the Blue Jackets beating the Lightning by going to a forecheck below dots offensive zone game and coming out on top, Lighting were better in open-ice but he Blue Jackets found their win condition). Usually, single players cannot win games alone but they can form large pieces with reliable skillsets.
If Slafkovský is unparalleled and cannot be stopped by any defenseman along the wall and in getting off the boards then he is, hypothetically, both elite and unique. The phrase, “unicorns” is thrown around often and they are important but only after you have considered the total quality of their projection.
Similarly, Josh Anderson is a rare archetype and could fetch assets in excess of his game-impact but that doesn’t mean he should be a first wave priority. If Slafkovský doesn’t have commensurate eliteness, perhaps you’re drafting Logan Cooley in his place.
Though smaller playmakers are more common, Cooley still differentiates himself by eliteness (Cooley’s interior drive, competitiveness and skating could also qualify him for “uniqueness” but the analogy breaks down if I try to take too much into consideration).
At the end of the day, draft for upside and probability of hitting that upside. Tentpole skills and domains (offensive zone, transition, etc) give rise to scaffolding for a development staff and linchpins for confidence at the NHL level.
Said altogether differently, there are certain kinds of players that are easier to find through other asset acquisition means like trade or free agency. It’s increasingly unlikely that you land a bona-fide Cup Caliber 1C or 1D outside of the draft though smart and aggressive GMs may be flipping that narrative (Ryan O’Reilly and Jack Eichel were both acquired via Trade).
At this stage in their competitive cycle, I am not convinced that the Blue Jackets are in a position to be picking for system fits outside of the Elite/Unique position. Right now, they should simply get the best, most unique and highest impact players possible and this should continue, mostly forever, but at least until a Cup Winning Core is established.
For now, draft the best and therefore highest value player and plan on finding some emergent roster construction strategy later. Although it would be potentially painful to continue taking swings on undersized wingers with later round picks, if they’re the best player with the highest upside you have to do it (still paying respect to eliteness/uniqueness/tentpole skills).
In later rounds and later drafts, it will become more excusable to try to fill potential prospect pool holes or draft for downstream roster/system/skill fits (maximizing ELC performance is a hallmark of some previous cup-winners). The second wave must be carefully curated once the team is secure in it’s core players or has otherwise run out of asset accumulation time.
That change in philosophy would have the most impact on picks made in later first round and in later rounds. The objective may no longer be exclusively to draft for upside but to find players who can contribute on ELCs once certain players start aging out. That said, it should never be all of one or the other, there’s always a line.