BLUE BULLET 2017 NHL ENTRY DRAFT GUIDE

Welcome to the Blue Bullet 2017 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 (DraftBuzz is an exception) 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 (effects 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. In 2017, Kailer Yamamoto is an example of a player that has wonderful numbers, but due to size factors is ranked anywhere from a mid-first round selection to an early second round selection. My system favours a talented player such as Yamamoto.

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, Lias Andersson has 24 points in 58 games in the SHL, which has a NHLE of 0.58 while the CHL has a NHLE of 0.30. Therefore, that means he would only score 46 points in 58 games in the CHL. That number would be understated, as it does not account for the fact that Andersson would play top six minutes in the CHL compared to playing in the bottom six back in Sweden. Therefore, one could find it reasonable that Andersson could see a 40% increase in playing time from 13:19 minutes/game to upwards of 19 minutes/game in the CHL, which would adjust his numbers to 65 points in 58 games. Based on that loose estimate, Andersson falls into the 55-61 range for NHLP.

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.” There are eight goalies in my rankings, with them falling between 32nd and 94th 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

For each player there will be two draft rankings. One will be based off of the Blue Bullet Draft Pick Value Chart. This will essentially be my analysis of what the consensus draft rankings are based off of the follow 11 draft rankings:

• ISS
• Hockey Prospect Black Book
• Draft Buzz
• McKeens
• THN
• Craig Button
• Jeff Marek
• Cory Pronman
• Future Considerations
• Recrutes
• Bob McKenzie

The other ranking will be my own rankings for the 2017 NHL Entry Draft, which is based off the 8 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 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, Matthews was the clear-cut winner for first overall with a 14.3 advantage over Laine. This year, it is a much tighter race as only 2.44 points separate Hischier and Patrick. A fair trade between New Jersey and Philadelphia, to swap selections, would involve Philadelphia giving up their 75th and 199th overall selections.
• It is best to remember that each draft year is different. A player taken 2nd overall in 2016 does not mean the same as a player taken 2nd overall in 2017. It is all relative. Laine scored a 88.78 in 2016, while Patrick scored a 94.43 this season. That does not mean Patrick is a better player than Laine was at the same age. In fact, if a prospect of Laine’s caliber was in the 2017 draft, they would likely be a consensus first overall selection, which would be a score of 107.03.
• With there being no consensus third overall selection, there is a tremendous gap between 2nd and 3rd overall. Based simply on the Blue Bullet Value Chart, Dallas does not have the draft assets to move into the top two. Add in the factor, that Vilardi sits at 3rd overall with a score of 52.53 and the gap widens. Dallas would need to give up a decent roster player, as well as all of their draft selections, to make a fair trade with Philadelphia. It just goes to show how important a top two pick can be.
• There are only two players that are in contention for third overall and it is the forward Vilardi edging out the top rated defensemen Heiskanen. Based simply on the average of the eleven draft rankings, Heiskanen edges Vilardi with a average ranking of 4.1 compared to Vilardi with a 5.0. My model, however, favours Vilardi due to the fact that historically forwards drafted in the top four are more likely to live up to their potential and play more games than a defenseman drafted in the top four.
• Each draft is different in where you can group selections. For this year, there is a distinct top two and top four. After that the draft values start to tighten up with 7.71 points separating the 5th spot from the ninth. From the third overall pick forward, the draft should really open up and it will be team preference that will dictate where players such as Makar, Glass, Mittelstadt, Tippett and Pettersson are taken.
• The Arizona Coyotes own two selections in the first round with the 7th and 23rd overall selections. Using the Blue Bullet Draft Pick Value Chart a fair trade would look like this                                                            However, based on my rankings in the 2017 draft this would be an overpay for Arizona. The 7th, 23rd and 78th ranked player add up to a score of 52.83 while the fourth overall selection has a score of 50.77. Therefore, to even out the trade remove the 78th and 128th pick from Arizona and the 187th pick from Colorado. It would leave the trade being simply the 7th and 23rd overall picks in exchange for 4th overall. 
• With the first nine selections, there is no difference in my rankings versus that of the scouts. That changes at the 10th selection with Suzuki in that spot, meanwhile the Blue Bullet Value Chart prefers Necas. Basically, this is the first point in the rankings where scouts and stats do not agree. As mentioned earlier in my rankings “One is much more likely to find a top six forward if they select a player with an NHLP above 62” and Suzuki has a score of 69. Meanwhile, Necas falls into the 55-61 range as I see his numbers in the Czech league being slightly below that of Lias Andersson, who I estimate to be around a NHLP of 60. Therefore, due to the fact that the model believes Suzuki has a better chance of becoming a top six forward he gets the nod.
• 77% of CHL forwards that go on to have a career average PPG of 0.80 or greater in the NHL, have a NHLP of 70 or greater. Generally, the best offensive players in the NHL were also the best offensive players back in their draft year. In 2017, there are four forwards that break the 70 point threshold, with two of them being the top two forwards in Hischier and Patrick. The two other forwards, who put up the numbers one would expect of a top four draft selection, is Kailer Yamamoto and Jason Robertson. However, neither is considered a top 10 pick due to flaws in their game. For Yamamoto it is his size, while for Robertson it is his skating. My model tends to favour these skilled players as historically they tend to outperform the scouting community`s opinion.
• The St. Louis Blues, like Arizona, have two selections in the first round. Using the Blue Bullet Draft Pick Value Chart a fair trade would look like this However, based on my rankings in the 2017 draft, this would be an overpay for St. Louis. The 20th and 27th overall selection add up to a score of 25.61 while the 11th overall selection has a value of 24.26. If L.A. added the 103rd to the mix and St. Louis dropped the 206th overall selection it would get one closer to a done deal. With no 7th round pick in 2017, the Kings would need to add a 2018 7th round pick to even out the trade.
• Vesalainen and Kostin are two wild-card selections that are all over the map, as some scouts view them as top 10 picks, while others have them outside their top 30. My rankings have them in the 22nd and 23rd spots, as neither player had an impressive season in terms of offensive production. For example, Vesalainen only produced 7 points in 15 games in the SEL J20. If it was not for his outstanding performance at the World Junior U18 tournament, Vesalainen would not be receiving top 10 buzz. Meanwhile, Kostin played in 18 games in three different leagues in Russia, recording only 2 points.
• There are 20 forwards and 11 defensemen ranked as first round selections. Once again, no goalies made the first round but Jake Oettinger did come close as he sits in the 32nd position.

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.
• There are three goalies that make it into the second round of my rankings. The consensus top goalie in the draft is Jake Oettinger who sits 21 spots ahead of the next closest goalie. While I have Oettinger as being the first pick of the second day, it is unlikely he makes it past the first day of the draft as a team coveting a goalie will likely snap him up.
• It this day and age it is common for most goalies to be at least 6’2″ and the fact that seven of the eight goalies in my top 100 are at least 6’2″ demonstrates that. That is why it is impressive to see 6’0″ Michael DiPietro sitting as the 2nd best goalie on my list at 53rd overall.
• If you are looking to find a forward with top six potential it is better to target a forward with at least a NHLP of 55. That is why forwards such as Heponiemi, Mattheos, Strome, Morand and Shaw are higher on my rankings than compared to many other lists. It is better to take a chance on a skilled forward than to play it safe with a role player.
• There are a number of forwards in my top 100 that are less than 6′ in height. In the first round, only 30% of the forwards are less than 6′ tall but that number climbs to 35% for the second round and 47% for the third round. Of the 62 forwards ranked in my top 100, 37% are less than 6’0″ tall.
• 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 Brook, Farrance, Phillips and Salo are seen as top 50 selections.
• There are three teams that have enough second round draft assets to move them into a first round selection. Buffalo could potentially move up to 28th, New Jersey to 26th and Carolina to 25th by packaging their second round selections.
• The second round is where to load up on forwards rather than defense. Only 5 of the 30 defenseman in my top 100 are ranked in the second round.
• There are 23 forwards, 5 defensemen and 3 goalies 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 79th (1.88) and 93rd (1.55) spots, they are separated only by a score of 0.33. Therefore, to make up the difference in value of 14 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 one player available with a projected NHLP of 55 or greater and that is Ivan Chekhovich at 65th overall. 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.
• While the forwards dominated the second round of my rankings, that is not the case for the third round. In fact, forwards only account for 15 of the 31 players ranked. Teams looking for a defenseman or a goalie is best to snatch one up at this point.
• 4 goalies are ranked in the third round and it was almost a 5th as Cayden Primeau sits just outside in the 94th spot. Historically, the best goalies are gone before the 80th selection so I would recommend to a team needing a goalie to grab Skinner or Petruzelli before it is too late.
• There is only one overage player to break into my top 100 and that is Morgan Geekie at 67th overall. He went from having only 25 points last year in the WHL to finishing with 90 points this season. Tyler Steenbergen, who also had 90 points as an overage forward in the WHL, just barely missed making it onto this list. He sits at 102nd overall with a score of 1.08 just behind Reilly Walsh.
• There are seven teams that have enough third round draft selections to package them for a second round pick. These teams include New Jersey, Carolina, Arizona, Detroit, Philadelphia, Edmonton and Buffalo. Detroit with 4 third round selections (71,79,83,88) could move up the furthest as a fair trade would be the 33rd overall pick belonging to Vancouver.
• There are 15 forwards, 12 defensemen and 4 goalies ranked as third round selections.

ROUND FOUR (94-100)