BLUE BULLET 2018 NHL ENTRY DRAFT GUIDE

Welcome to the Blue Bullet 2018 NHL Entry Draft Guide. Another season is in the books, which means it is now time to turn our attention to those young men who each are trying to make the difficult goal of playing in the NHL. After countless hours of practice and games, 217 of the best draft eligible players will be weeded out and selected by one of the thirty-one NHL teams. Of those players selected, few of them will turn out to be long-term NHL players. Therefore, it is the job of each team to do their research to create the very best draft list through use of scouting and statistical analysis.

While the public is not able to see an actual team’s draft list, there are many draft guides available for purchase, with the majority of them focusing on the scouting aspect of the draft. Very few incorporate statistical analysis and this is a weakness of many draft guides. While the eye test is beneficial, it does not tell the whole picture. I did a previous study on CHL forwards drafted in the first round between 1990 and 2010 and found that when selecting a CHL forward, on average, teams would have been better off by simply selecting the CHL forward who had the highest point-per-game in their draft season. Relying simply on scouting will not give a team the best results and that is why one must look for where scouts and stats collide.

METHODS OF ANALYSIS

To create my rankings, I have always started by using the average rankings of a player from the various draft guides as my base. It is a good starting point as it averages out the varying opinions on a player, from the different scouting guides. However, the problem with averaging out the draft rankings in this fashion is that it is suggesting that the value of a draft selection decreases in a linear fashion. That is not the case. Instead, the value of a draft selection decreases at an exponential rate.

Therefore, to obtain a more accurate consensus ranking, the Blue Bullet Draft Pick Value Chart is an essential tool to utilize. The chart is based off my research on the expected value of forwards and defensemen and Michael Schuckers’s Value Chart. My research revolves around finding ranges of draft selections that provide similar value in terms of NHL career average points-per-game in forwards and NHL career average time-on-ice in defensemen. My results for forwards and defensemen are:

Michael Shuckers’s research revolves around the value of players based on NHL games played. Therefore, Schuckers’s research was based off of quantity while my research is based off of quality. By combining the two sets of data, it gives the best of both worlds.

Blue Bullet Value Pick Chart

To utilize the Blue Bullet Draft Pick Value Chart, to create a consensus ranking, one starts by simply substituting the values from the chart for the corresponding draft position. For example, if a forward is ranked 12^th they will receive a score of 22.8, meanwhile a defenseman ranked in the same 12^th position will receive a score of 21.3. From there it is simply averaging all the scores and ranking from highest score to lowest.

For those disbelievers that have little faith in the numbers, this is where you would stop and simply go by what the scouts are saying. However, I know there is value in the numbers and will continue forward. The research I will be utilizing for forwards is based off of my NHL point prediction model called NHLP. NHLP is a tool to project the future upside of a CHL forward by predicting how many points they would score in their best NHL season (based on an 82 game season).

The formula is based off my research that shows that for CHL forwards, who play at least 250 NHL games, over 1/3 of their future NHL production can be explained be their junior production, in the season they become draft eligible. The formula accounts for the following three factors:

• Points-per-game (separated between non-power play and power play points)
• % contribution to team scoring (percentage of team’s goals they receive a point which helps measure how much of the play they are driving, the higher the number the higher the point prediction)
• Age (impacts power play scoring only, theory is younger players receive less power play ice time, most people overrate the age factor)

NHLP Formula

Non-Power Play: 0.201645 + (0.220766 X Non-PP Pts/G) + (0.563435 X Non-PP Contribution %)

+

Power Play: 0.699759 + (0.179796 X PP Pts/G) – (0.036095 X Age on Sep 15 of Draft Year) + (0.250900 X PP Contribution %)

The results for every CHL forward selected in the first round since 1998 can be found here.

Using my NHLP formula, I have done research on finding ranges of NHLP scores and draft positions in which forwards have similar value in terms of NHL career average points per game. The results are:

Note: The average PPG is based off of those forwards who reached 100 games played.

Therefore, since my draft pick value chart is based off of draft position, it does not incorporate any of my statistical measurements in to the mix. That simply will not cut it for me. Therefore, for my draft rankings, I had to create Value Charts for each of the six groups of NHLP. For example, a CHL forward selected 8^th to 12^th overall, with a NHLP of at least 70, has a career average points per game that is 161% greater than that of an average pick in that draft range. Meanwhile, a 5^th to 7^th overall selection with a NHLP of 55 to 61 has a career average points per game that is 97% that of an average pick in that draft range. Applying those numbers to the Blue Bullet Value Chart, it gives a score of 38.9 for a 7^th overall selection with a NHLP in the 55-61 range. Meanwhile, an 11^th overall selection with a NHLP above 70 provides the same value of 38.9. By combining scouts and stats, one accounts for the fact that the offensive player ranked 11^th is likely being underrated while the player ranked 7^th is being ranked accordingly.

With defensemen, I do not have a point prediction model to utilize, as there is a weak correlation between junior scoring and NHL scoring. What I utilize instead is the fact that, overall, power play scoring does not carry over to the NHL at the same rate as non-power play scoring. Therefore, when evaluating defensemen, I adjust power play scoring so that it is worth 58% that of a non-power play point. So does that mean the higher the number, the better? Not exactly. While it does give insight into the offensive potential of a defenseman, it is better utilized as a pass/fail measurement. Research done by Rhys Jessop showcased that CHL defensemen who scored at a rate of 0.55 Pts/game or better turn out to be much more likely at becoming a NHL defenseman. It makes intuitive sense to those watching today’s NHL game given that the best defensemen tend to have the best puck skills. Taking this knowledge into account, I found that for my adjusted point per game measurement the cutoff was 0.44. Therefore, for defensemen I have created two value charts, one for defensemen who have an adjusted PPG of 0.44 or above and one for those who do not.

While my value chart for forwards is based on NHL career average points per game, my value chart for defensemen is based on their NHL career ATOI (average time on ice). However, that is comparing apples and oranges and therefore a conversion chart was created to convert the career ATOI of a NHL defenseman into an equivalent PPG measurement so that I could compare forwards against defensemen. A sample of the conversion chart is as follows:

With the two value charts for defensemen, the results can be staggeringly different from each other. For example, defensemen selected between 19^th-29^th, who have an adjusted PPG of 0.44 or greater, end up having a converted PPG that is 129% greater than that of an average selection in that range. Meanwhile, those that fall below 0.44 points per game, have a converted PPG which is 75% that of an average selection in the 19-29 range. Therefore, a defenseman ranked 24^th overall with an adjusted PPG of at least 0.44 will receive a value of 12.0 while those below 0.44 will receive a value of 7.0. What the stats are telling us is that stay at home defensemen are consistently overrated by the scouting community, likely due to their love of size.

With all my various value charts completed, there is one last item to address before I could apply my rankings, which is the fact that all my research is based off CHL players. This is due to the CHL having the largest collection of data in which to base my research. This is where NHL equivalency (NHLE) will come into play. Therefore, for all players outside the CHL, I tried to do an estimate of what NHLP group they will fall into for forwards and for defenseman, I tested whether they passed the pass/fail measurement of 0.44 points per game or better. One problem, I ran into is lack of data, especially from the European leagues which could make it difficult to do a proper estimation. The other issue is that there are a few European prospects that play primarily in pro leagues. While NHLE helps resolve this issue somewhat, the lack of data on time on ice makes it difficult to estimate an NHLP score. For example, Jesperi Kotkaniemi has 30 points in 64 games in the SM-Liiga (regular seasons and playoffs combined), which has a NHLE of 0.452 while the WHL has a NHLE of 0.302. Therefore, that means Kotkaniemi would score roughly 45 points in 64 games in the WHL. That number would be understated, as it does not account for the fact that Kotkaniemi would play more minutes in the CHL compared to playing in a men’s league in Finland. Therefore, I had to make assumptions of how much his playing time would increase if he played in the CHL. Based on that loose estimate, Kotkaniemi falls into the 55-61 range for NHLP, similar to my estimate for Lias Andersson in 2017.

The rankings will not be separated between skaters and goalies despite having zero value charts completed for goaltenders. Instead, I use the overall score from the Blue Bullet Draft Pick Value Chart. In a previous post, I analyzed the expected draft value of goaltenders based on their likelihood to reach 50 games played. I than compared this against the likelihood of skaters reaching 100 games played. I concluded that “the best method of drafting goalies is to stay away from using a first round pick on a goalie (unless it is an exceptional goalie) as the odds are significantly better if you draft a forward or d-men over a goalie (over 40% better). Instead, the best time to draft one of the top rated goalies from North America or Europe is to grab them in the 2nd or early 3rd round. Goalies in this range tend to out perform the forwards and d-men by 50% and if you wait to long all the good goalies will be gone. However, this year is not a very good year for goaltenders with my top ranked goalie being Jakub Skarek at 72nd overall.

And there you have it. My method of creating a draft list based off of finding where scouting and statistics meet. While in the past I would pour over the scouting reports reading every detail trying to determine what insights I could grab from the reports, I have chosen to forgo that process going forward. The theory behind this is that the work is redundant as I am basically scouting the scouting reports. While I would like to think I am good at doing this, I have no evidence of that and to just assume I do would be a fallacy on my part. Instead, I will let the rankings from the scouts and from my statistical measurements do the speaking for themselves. With that in mind it is finally time to get down to the rankings.

BLUE BULLET DRAFT RANKINGS

The rankings are based off of the draft value charts I created to find where scouts and stats collide. While at times it can be hard not to allow my own views on players to get involved, it can be freeing to let the numbers speak for themselves, which is what this model allows me to do. For this year I have expanded the number of draft rankings that I utilized to include the following:

• ISS
• Hockey Prospect Black Book
• McKeens
• THN
• Future Considerations
• Recrutes
• The Draft Analyst – Steve Kournianos
• The Athletic – Corey Pronman
• The Athletic – Scott Wheeler
• TSN – Craig Button
• TSN – Bob McKenzie
• ESPN – Chris Peters
• Dobber Propsects – Cam Robinson
• The Hockey Writers – Ryan Pike
• The Hockey Writers – Larry Fisher
• Canucks Army
• Defending Big D – Derek Neumeier

For each forward, I have presented their NHLP score, which is my point prediction for their best NHL season. Where possible, I have also presented the breakdown between power play and non-power play estimates. Remember for many of the European players I was only able to estimate which group they most likely belong and that some assumptions needed to be made so there is less accuracy when it comes to my ranking of European players. In addition, I also presented the percentage team contribution to scoring, which is the percentage of goals they receive a point (goals scored in games missed are removed). As with NHLP, it is separated between non-power play and power play totals. To get a better picture of NHLP, I have created some pie charts to show the distribution of forwards selected top 90 overall as well as the distribution based off of career average point per game.

One is much more likely to find a top six forward if they select a player with an NHLP above 62.

For defensemen, I have presented their adjusted point per game total and as with forwards, I have also presented their non-power play and power play totals.

ROUND ONE

• Last year, it was a tight race between Hischier and Patrick as only 2.44 points separated the two players. This year I cannot say the same, as Dahlin is clearly at the top of this draft class with a 11.21 point advantage over Svechnikov. If Carolina offered every pick that they had in the 2018 draft class it would not be enough to move up from 2^nd to 1^st, as the combined value of their picks in rounds two through seven is 7.2.
• My value chart looks at historical data based on draft position, but you run into an issue when it comes to defenseman drafted first or second overall due to a tiny sample size. In the case of Dahlin, the draft value chart suggests to take Svechnikov 1^st overall. However, that is based on a small sample size of just three players (Johnson, Doughty, Hedman) and is also influenced due to defenseman historically playing less games than a forward as they take longer to make the jump to the NHL. For Dahlin, who is touted as the best defensive prospect since Potvin, it is likely he will make the jump straight to the NHL next year, similar to Doughty and Hedman. Therefore, I adjusted his game played projection to match the amount I use for forwards and adjusted his career ATOI to be the average of Doughty and Hedman.
• The difference between 2^nd overall and 3^rd overall is historically quite large and that is why the value of Zadina, the consensus 3^rd ranked player in this draft, is 19.67 points below Svechnikov. To move up from 2^nd to 3^rd Montreal does have the assets, but they would need to consider moving all of their 2^nd and 3^rd round selections. A fair trade would be the 2^nd and 104^th overall selections for the 3^rd, 35^th, 38^th, 56^th, 62^nd and 66^th overall selections.
• The gap in value between 3^rd and 4^th is similar to the gap between 2^nd and 3^rd. If Montreal is considering moving down in the draft to take a centre they should be asking for a lot. If no one is biting, they should simply take the best player available in Zadina and move one of their roster players to fill in the centre position instead of drafting for need. One team that does have the assets to move up in the draft is Detroit who sit in the 6^th spot. The gap in value between the two selections is 23.69 and the players ranked on my list at 30, 33, 36 and 81 cover that spread with a value of 23.79.
• Once the top three players are gone, the value starts to tighten between players. For example, the difference between 2^nd and 3^rd is larger than the difference in value between 4^th and 10^th. This is where the draft should start to get interesting, but with Montreal owning the 3^rd overall selection, it will probably start one pick earlier. Between 4^th and 10^th there is a wide range in opinions and most teams drafting in these positions have a good chance of finding a player available that is high in their rankings.
• My model favours forwards over defensemen, as historically forwards end up making it to the NHL sooner than defensemen and end up playing more games. That is why in the fourth and fifth spot you find Wahlstrom and Tkachuk over Hughes. If I adjusted the model so that Hughes is expected to play the same amount of games as a forward he would leapfrog into the 4^th spot on my rankings. The other defensemen in my top ten would not move positions if adjusted.
• Wahlstrom is ranked between 5^th and 10^th in all the rankings used for this model, but ends up 4^th for my rankings. The reason why is because my model tends to favour skilled offensive players, as historically they tend to outperform the scouting community`s opinion. Based on my research of CHL forwards, 77% who have a NHLP of 70 or greater go on to have a career average P/GP of 0.80 or greater in the NHL. Basically, the best offensive players in the NHL were also the best offensive players back in their draft year. In 2018, the only two forwards that hit the 70+ point threshold are Svechnikov and Wahlstrom. If you feel that Wahlstrom’s numbers are slightly inflated by playing with Jack Hughes and that he belongs in the 62-69 NHLP range, it would drop him to the 6^th spot in my rankings.
• Two players in my top 10 that I expect to go higher than I have them rated is Dobson and Kotkaniemi. It is human nature to be influenced more by our last impressions and it is one of the flaws if you rely purely on scouting when evaluating a player. In the case of these two players, they both left lasting impressions in the scouting community to end the season and I believe they will both be taken slightly too early. Add in the fact that this is a weaker than normal draft for centres and I am almost certain that Kotkaniemi will not be available where I have him ranked.
• The value of each draft pick recedes at a faster rate in the first half of the first round compared to the second half. For example, the 10^th ranked player is worth 1.91 times that of the 15^th ranked player while the 15^th ranked player is valued at 1.82 times that of the 32^nd ranked player. Teams need to be aware of this and to take it into consideration when making a trade to move down in the draft, especially those teams with early selections.
• The New York Islanders own the 11^th and 12^th selection in the 2018 NHL Entry Draft. The two players in those spots have a combined value of 44.57, which is in between the value of the 5^th and 6^th ranked players on my list. Therefore, if the Islanders were looking to bundle these picks, they should be targeting Arizona or Detroit.
• Another team with two selections is Philadelphia with picks 14 and 19. The two players in those spots have a combined value of 32.36 which is in between the 9^th and 10^th ranked players on my list. Therefore, if the Flyers were looking to bundle these picks to move up, they should be targeting the Rangers or the Oilers.
• The New York Rangers have a chance to make some trades in the draft as they own three picks in the 1^st. If they wanted to move up to the 4^th spot, those three picks are an overpay for Ottawa to move down in the draft. If they just wanted to move the 26^th and 28^th selections, the teams to target would be those sitting in the 12-14 spots.
• There are 18 forwards and 13 defensemen ranked as first round selections with 5 of those 13 defensemen ranked in my top 10.

ROUND TWO

• I said it last year and I will say it again. The spread between players tightens as the draft unfolds. If anyone has done their own rankings they will attest to it being harder to rank the second round and later.
• Denisenko is a player that the scouting community is a fan of but my model is not. That is due to the poor numbers he put up in the MHL this year. It’s always been a tendency for scouts to put a higher value on the international tournaments than club play and I think that can be risky as you are placing a high value on a small sample size. It will be interesting to see if the scouts or the stats is more accurate in projecting Denisenko.
• My value charts for defenseman place a high value on defensemen that can generate offense. Therefore, one is much more likely to see a smaller defenseman with some offensive ability higher on my list than a big stay at home type. That is why below average height d-men such as Addison and Beaudin are in my top 35.
• 2/3 of the players I have ranked as 2nd round picks are 6′ in height or less. Today’s NHL is more about speed than it is size.
• The second round is where to load up on forwards rather than defense. Only 7 of the 31 defenseman in my top 100 are ranked in the second round.
• There are 24 forwards and 7 defensemen ranked as second round selections.

ROUND THREE

• By the third round, teams are really splitting hairs on who is better than who. If you look at the scores for the players in the 71st (2.30) and 81st (1.95) spots, they are separated only by a score of 0.35. Therefore, to make up the difference in value of 10 spots, a team only needs to sacrifice a 7th round selection at this point.
• The offensive forwards will start to dry up into the third round and teams should be focusing on finding depth players. There is only two players available with a projected NHLP of 55 or greater and that is Adam Mascherin and Matej Pekar. At this point in the draft, teams are much more likely to find a forward that will have a career average PPG that ends up being less than 0.60.
• 4 goalies are ranked between 72nd and 100 on my list. Historically, the best goalies are gone before the 80th selection so I would recommend to a team needing a goalie to grab Skarek or Rodrigue before it is too late.
• There are four overage players to break into my top 100 with Sean Durzi the highest at 50th overall. Perunovich (68), Mascherin (73) and Hutsko (97) are the other three.
• There are 18 forwards, 10 defensemen and 3 goalies ranked as third round selections.

ROUND FOUR (94-100)