2019 Nashville Predators Prospect Rankings: An Introduction

In place of the annual ‘Top 25 Under 25’ breakdown, I’ll be doing a more prospect-focused breakdown.

Each year, many of SB Nation’s NHL sites conduct a breakdown of the top 25 players in each organization under the age of 25. It’s a fun exercise that each website conducts differently and has often inspired good debate among fans.

Here at On The Forecheck, we are no strangers to this process. But, despite this, I wanted to provide a different analysis this year that maintained the spirit of the T25U25 rankings. In the past, I’ve loathed the 25-year benchmark because the rankings often begin with a middling prospect like Justin Kirkland and end with a franchise star like Filip Forsberg; it seems weird to me. Additionally, earlier this year I provided a statistical recap, with the help of Bryan Bastin, of the Milwaukee Admirals that involved building my own metric to measure individual success.

(You can read that here).

I was largely pleased with what that analysis discovered and believe it dealt a fair ranking of Milwaukee’s best performers in 2018-19 while also highlighting underrated players like Zach Magwood or Joe Pendenza.

Over the summer I have been working on a more holistic ranking for every prospect in the organization. This process has involved accounting for many variables like age, league, and consistency. In the end, I think I’ve developed a fair ranking of the entire organization but have not exclusively used this metric. Naturally, my formula favors scoring, so defenders are often left short-changed. Therefore, I have combined my scouting of each player throughout the season with what the numbers added up to create a top-25 prospects list.

Below I’ll explain my schedule for how this list will be released and the methodology behind my work.


Over the course of the next couple weeks, I will parse out my analysis into the following pieces (the top-25 will be a ranking based off scouting and numbers, whereas the position rankings will highlight my metric more):

  • Prospects #25 — #21
  • Prospects #20 — #16
  • Prospects #15 — #11
  • Prospects #10 — #6
  • Prospects #5 — #1
  • Organizational Goalies, Ranked
  • Organizational Defenders, Ranked
  • Organizational Wingers, Ranked
  • Organizational Centers, Ranked
  • Prospects Compared Team & League-Wide
  • Best Breakout Candidates
  • Likely Drop-off Candidates/


This is where things may get dicey, so I will do my best to explain thoroughly. First, what are the parameters of who is included?

  • For the top-25, all prospects on an NHL contract under the age of 25 are included. This means traditional prospects in amateur leagues and those who played primarily in the AHL or ECHL last year. There are no regular NHL skaters accounted for (including Dante Fabbro).
  • For the position-based rankings, all prospects are considered regardless of age or contract status. This will rope in AHL veterans like Matt Donovan and players on AHL contracts like Hunter Garlent./

In the visualizations I will provide, you will be able to see how each player ranks when weighing the comparison for various statistics. But, as an overview, here is what is accounted for in my analysis for skaters:

GPgames played in their primary league in 2018-19
P1goals and primary assists
Shotsshots on goal
Ggoals in all situations
ST Goalspower play and shorthanded goals
PIMpenalty minutes
GA/60measured only for defenders; goals scored while that player is on the ice relative to 60 minutes
Rel GF%measured only for forwards; the rate at which goals-for are scored when that player is on the ice versus when they are not
Line 'x'this is a multiplier used to consider a player’s ice time and how that values their production
Prob. Makea prospect’s probability to make the NHL based on production and success of cohorts (similar ages, leagues, production, etc.). This rate was constructed by Manny Perry
Proj. WAR/82a prospect’s projected wins-above-replacement value over 82 games in the NHL. This rate, constructed by Manny Perry, assumes the player has made the NHL full-time
Proj. WAR%how a prospect’s projected WAR/82 has increased or decreased since entering the organization
NHLethe rate at which players scoring in various leagues would continue over 82 NHL games (i.e. 1 point in the KHL is equivalent to 0.7461 points in the NHL). The most up to date measurements can be found here courtesy of Manny Perry

For goalies, the following things were considered:

GSgames started in 2018-19
SV %save percentage
GSAAgoals-saved above average. This measures how many more or less goals a player stopped than the average league goalie given the amount of shots they faced
QS %quality start percentage. This is a measure of how many starts a goalie posted a better save percentage than this league-average rate in compared to their total number of starts
Line 'x'this is the same multiplier mentioned above to account for backups versus starters
NHLethis rate was constructed using the framework of Perry’s stated above to normalize how close players are to the NHL. For instance, Ethan Haider may have stronger numbers than Niclas Westerholm, but the latter’s above average stats in a league more similar to the NHL help widen his edge

For all of this, I had to be careful not to weigh certain things too much. That seems obvious, but there are significant measures than can severely inflate these rankings. One example is Eeli Tolvanen. Tolvanen’s probability to make the NHL is a staggering 97%. While that is plausible, I also want to consider his lower-than-expected scoring rate this season. Another anecdote is Grant Mismash. Mismash had a horrendous year via traditional counting stats but had a surprisingly high scoring rate relative to his teammates. Finally, Arvin Atwal is a good example. He was an excellent scoring defender in the ECHL this year but also committed an obscene amount of penalties that hurts his score due to his lack of value when he’s in the penalty box.

As my rankings come out, I will be conducting polls on Twitter to gauge your feelings on these respective prospects. I want to see what differences and surprises we can uncover, so look out for tweets like this one:

Finally, I wanted to issue a note on this process. A decent amount of these statistics had to be hand-tracked or manually pulled. I’ve poured through more game sheets from the NCAA last season than you could imagine calculating scoring rates. It’s inspired me to be more proactive about this for 2019-20. For this season, I hope to maintain an active visualization of all prospects' counting stats and advanced metrics through frequent game tracking and scouting trips. If all goes as planned, this will likely include and therefore replace the weekly stats updates shared on Twitter. But don’t fret—this will be even better.