
02 Jul
Ryan O’Reilly Trade Analysis
The NHL offseason opened with a bang as shortly after the first hour of free agency, John Tavares announced that he would be taking his talents to Toronto. That alone sent shock-waves through the NHL. The teams that missed out on Tavares likely then turned their attention to the Buffalo Sabres and center Ryan O’Reilly. Shortly after LeBron James sent shock-waves through the NBA by announcing his move to Los Angeles, the Sabres and Blues announced they had completed a trade for O’Reilly in what could be one of the biggest trades this offseason. There have been many mixed opinions about this trade and we thought we would add ours to the mix.
To St. Louis: Ryan O’Reilly
The key piece obviously in this trade is how good of a player Buffalo gave up in Ryan O’Reilly. We’re not going to say he isn’t a good player but we think we need to pump the breaks on the praise a little. On the surface, O’Reilly performed well in incredibly tough minutes for a horrible Buffalo Sabres’ team. He was also a quality player for the Colorado Avalanche. Let’s look at Ryan O’Reilly’s Relative Corsi For % during 5v5 play going back to the lockout. This statistic looks at how much better (if positive) or worse (if negative) O’Reilly’s team performed in shots when he was on the ice versus off the ice.
Season | Team | GP | TOI/GP | CF% Rel |
20122013 | COL | 29 | 14.19 | 7.62 |
20132014 | COL | 80 | 14.96 | 2.59 |
20142015 | COL | 82 | 14.10 | 4.1 |
20152016 | BUF | 71 | 15.05 | 0.93 |
20162017 | BUF | 72 | 15.15 | 2.19 |
20172018 | BUF | 81 | 14.48 | 3.06 |
The chart shows O’Reilly has been a solid player overall. For reference, the top forward in the league usually will be around 8% – 9% and the 50th best forward is usually around 4%. This metric attempts to strip away the team’s strength. For example, let’s say Player A and Player B both have a Corsi For % (all shots toward goal) of 50%. However, Player A plays on a team that only has a 45% Corsi For % (weaker team), while Player B plays on a team that has a Corsi For % of 50% (better team). Player A’s Relative Corsi For % is 5% while Player B’s is 0%. We can say that Player A is likely the better player.
Considering Ryan O’Reilly has improved his team’s results while he was on the ice, should mean he is a fantastic player especially since he has played on some pretty awful teams. However, this is where we need to take a deeper look. This is where we don’t want to say this should be taken as an absolute but a very interesting trend has emerged when looking at who O’Reilly has played with. As a clear top six player, it should be expected that O’Reilly will play with other good players. The trend that has emerged has been O’Reilly has struggled when playing away from some of his top teammates. Let’s look at his time in Buffalo first.
With | Season | Team | TOI With | TOI Away | CF% Rel Together | O’Reilly CF% Rel Without Teammate | Teammate’s CF% Rel Without O’Reilly |
Sam Reinhart | 2017 | BUF | 503.33 | 669.63 | 7.37 | -1.71 | 0.46 |
Kyle Okposo | 2017 | BUF | 414.23 | 659.07 | -0.63 | 2.01 | -3.01 |
Kyle Okposo | 2016 | BUF | 634.72 | 193.00 | 1.1 | 1.53 | -3.53 |
Evander Kane | 2016 | BUF | 261.97 | 643.77 | 5.38 | -0.29 | -1.57 |
Tyler Ennis | 2016 | BUF | 216.38 | 570.03 | 0.21 | -0.97 | 0.89 |
Matt Moulson | 2016 | BUF | 190.65 | 885.62 | -0.64 | 1.89 | 4.18 |
Sam Reinhart | 2016 | BUF | 168.98 | 881.30 | 6.07 | 1.28 | 1.54 |
Brian Gionta | 2016 | BUF | 157.08 | 933.75 | -0.67 | 1.63 | -3.52 |
Sam Reinhart | 2015 | BUF | 453.22 | 568.08 | 2.65 | -0.41 | 4.25 |
Evander Kane | 2015 | BUF | 399.32 | 412.23 | 2.59 | -1.79 | 4.33 |
Ryan O’Reilly and Sam Reinhart formed a dynamic duo for the Sabres, posting elite level shot metrics when playing together. Both were not nearly as good when playing with other teammates but O’Reilly’s drop when playing away from Reinhart was higher than Reinhart’s drop when away from O’Reilly. In his time with the Sabres, Reinhart has shown that he has steadily been one of the team’s top possession players.
Kyle Okposo and Brian Gionta are the only players O’Reilly played with that were completely lost without O’Reilly. Everyone else was fine away from him. We can argue about the fact that the players played against weaker competition when they weren’t with O’Reilly while also likely playing with Jack Eichel at center as well. However, this wasn’t only a trend for O’Reilly with the Sabres. Let’s also look at his three previous seasons with the Avalanche.
With | Season | Team | TOI With | TOI Away | CF% Rel Together | O’Reilly CF% Rel Without Teammate | Teammate’s CF% Rel Without O’Reilly |
Gabriel Landeskog | 2014 | COL | 780.83 | 375.08 | 1.88 | -2.6 | 2.3 |
Alex Tanguay | 2014 | COL | 412.92 | 711.37 | -0.61 | 0.33 | -5.1 |
Matt Duchene | 2013 | COL | 810.07 | 221.65 | 2.74 | -2.86 | 4.43 |
Jamie McGinn | 2013 | COL | 391.52 | 756.88 | 1.25 | 1.08 | -0.82 |
Nathan MacKinnon | 2013 | COL | 310.33 | 886.80 | 1.78 | 1.65 | -0.56 |
Gabriel Landeskog | 2012 | COL | 235.78 | 163.80 | 7.01 | 6.93 | 3.19 |
Cody McLeod | 2012 | COL | 157.33 | 254.32 | 7.83 | 6.41 | -6.07 |
The way we look at this is you have to go back to 2012 before you find a season where O’Reilly was unquestionably the one making his team better and he only played 29 of the 42 games that season. After that, we think that an argument could be made that O’Reilly’s strong play in the past five seasons (outside of maybe 2016) could be as much a result of who he was playing with as his own play. We can debate the validity of this until we are blue in the face but we think it is something important to look at.
Shot metrics aren’t everything so we should also look at O’Reilly’s scoring during 5v5 play. We prefer to look at rates as it keeps everyone on the same scale, but we also realize it is hard for some to look at points per 60 and get a feel for how that stacks up so we also presented the pure scoring counts.
Season | Team | GP | TOI/GP | Goals/60 | Total Assists/60 | First Assists/60 | Second Assists/60 | Total Points/60 |
20122013 | COL | 29 | 14.19 | 0.44 | 1.46 | 0.29 | 1.17 | 1.89 |
20132014 | COL | 80 | 14.96 | 0.95 | 0.95 | 0.35 | 0.6 | 1.9 |
20142015 | COL | 82 | 14.10 | 0.62 | 1.3 | 0.88 | 0.42 | 1.92 |
20152016 | BUF | 71 | 15.05 | 0.51 | 0.9 | 0.67 | 0.22 | 1.4 |
20162017 | BUF | 72 | 15.15 | 0.61 | 0.77 | 0.39 | 0.39 | 1.38 |
20172018 | BUF | 81 | 14.48 | 0.36 | 0.72 | 0.51 | 0.2 | 1.07 |
Season | Team | GP | TOI | Goals | Total Assists | First Assists | Second Assists | Total Points |
20122013 | COL | 29 | 411.65 | 3 | 10 | 2 | 8 | 13 |
20132014 | COL | 80 | 1197.13 | 19 | 19 | 7 | 12 | 38 |
20142015 | COL | 82 | 1155.92 | 12 | 25 | 17 | 8 | 37 |
20152016 | BUF | 71 | 1068.75 | 9 | 16 | 12 | 4 | 25 |
20162017 | BUF | 72 | 1090.83 | 11 | 14 | 7 | 7 | 25 |
20172018 | BUF | 81 | 1172.97 | 7 | 14 | 10 | 4 | 21 |
Ryan O’Reilly’s scoring has clearly dropped during 5v5 play since coming to Buffalo. It could be due to him starting more in his own zone (though his offensive zone faceoff % has never been above 50% in the six years we have been looking at), him playing against tougher players, or him playing with lesser skilled teammates. However, it could be purely due to the fact that O’Reilly is simply on the downside of his career.
Clearly there were other factors at play when the Sabres decided to move O’Reilly. First, we have no way of knowing how O’Reilly contributed to the chemistry and culture in the locker room but it seems like that was a big part of the reason for this move. We have heard that there was a divide between him and Eichel and clearly the Sabres were going to choose Eichel.
Another concern that has to be discussed when assessing O’Reilly is his footspeed. He has never been the fastest player and as he gets older and the NHL gets faster, it certainly has to be a concern. He will probably be fine for the Blues, who don’t play as up tempo as some teams, for the next few years but having O’Reilly under contract for five more seasons is probably not ideal.
We have developed a market value model internally where we can assess where a current player’s market value stands. This offseason we only had the time to run 40 players and their projections can be found here. Earlier returns on the accuracy are pretty good as it has beaten Matt Cane’s model in error percentage for the players we assessed. This model has Ryan O’Reilly at a market value of $6.8M under the present salary cap. O’Reilly currently has a cap hit of $7.5M so our model believes O’Reilly is currently overpaid. That gap is likely to widen as O’Reilly ages and his play drops. Because of this, the Sabres may be wise to make the move now while his perceived trade value was still very high. If he had another down season, which is not outside the realm of possibilities, the Sabres would likely have been stuck with the contract or would have had to sell at a discount.
Right now, we think the Sabres likely got pretty close to market value. O’Reilly is a good player and someone the Sabres definitely shouldn’t have tried to move purely to shed his salary. However, we also think there is a level of overrating O’Reilly whether it being in the analytic community or in “Hockey Circles.” O’Reilly is currently a solid second-line center, who is being paid more like a first line center with a $7.5M cap hit. It seems unlikely O’Reilly will really improve much over the remaining life of his contract and by the end he likely will be nothing more than a third-line center. Even with the rising cap, having a third-line center with a $7.5M cap hit will be less than ideal. Because all of this, we think moving O’Reilly was likely a smart move if the Sabres got a quality return, which we will discuss next.
To Buffalo: Tage Thompson, Patrik Berglund, Vladimir Sobotka, 2019 1st Round Pick, 2021 2nd Round Pick
After taking a deeper look into Ryan O’Reilly, we decided to look at the three players coming back to Buffalo. Tage Thompson is a recognizable name and many fans probably knew where he stood as a prospect, but they may be surprised to learn that he played about half the season last year in the NHL with the Blues. Patrik Berglund and Vladimir Sobotka are NHL regulars who are on contracts that the Blues were looking to move.
Some of the media and analytics community are looking at Berglund and Sobotka as pure salary dumps, and that the trade was Thompson and the picks for O’Reilly. We would not go that far, some of the numbers on Berglund and Sobotka are surprising, much like the ROR numbers from above.
Rather than focus on each of the three players individually we decided to look at specific metrics and where the three players ranked on the Blues this past season. For each statistic used we set the minutes limit at 200 minutes of 5v5 play. This resulted in 15 eligible forwards so when discussing where the players ranked, 15 is the number to keep in mind.
Let’s start with some of the basic metrics like Corsi% and Expected Goals For/Against. Corsi% is the percentage of shots that were taken by the players team when he was on the ice. For example, if 100 shots were taken while ROR was on the ice and the Sabres attempted 60, his Corsi% would be 60%. Expected goals is a metric that takes quality and quantity of shots into account and predicts how likely each shot attempt is to result in a goal.
The Sabres have been a Corsi% disaster recently and this season was a slight improvement, but their percentage of 47.61% was 26th in the league. The Blues were much better, they ranked 6th with a 51.70% Corsi. From an individual standpoint, the 3 forwards ranked 7th, 8th and 10th. Berglund had a CF% of 51.6, Thompson 50.9% and Sobotka 49.6%. So, the players were not grouped with players like Steen and Tarasenko, but they certainly were not holding the team back either. In Buffalo, O’Reilly had a Corsi% of 51.1%, which is impressive, but some would argue it would be expected based on his role and teammates that he played with.
From an expected goals for and against standpoint, none of the players from the Blues are particularly impressive, but there is still reason Sabres fans should be hopeful and we will explain why. The version of this statistic we used was from a team perspective, so it is how many goals for the entire team was expected to score or allow (per 60 minutes) while that one specific player was on the ice. Sobotka ranked 8th, which was the best out of the 3 players, but his differential was high. The Blues were expected to score 2.38 goals and allow 2.94 while he was on the ice. Next was Berglund, who ranked 10th with 2.23 goals for and 2.46 goals against. Finally, Thompson ranked 12th at 2.18 expected goals for and 2.94 expected goals against. However, all hope is not lost, Thompson and Sobotka significantly underperformed when looking at how their expected goals for lined up with their actual. That could be due to a variety of reasons, perhaps they missed some A+ chances or the goalies always seemed to make the big save while these players are on the ice. The conclusion we would draw from this is that Berglund and Sobotka may not be top 6 forwards, but they should be more than serviceable if used properly in Buffalo. Thompson is only 20 years old and will need to continue to develop but if his interview today is any indication, he will get an opportunity to prove himself in Buffalo.
Speaking of opportunities there is an interesting statistic that favors Patrik Berglund. Berglund had the highest rate of his zone entries result in a shot on goal for the Blues. 44% of the time Berglund controlled the entry into the offensive zone, the Blues registered a shot on goal. However, when looking at the quantity of entries per 60 minutes, he ranks 12th with only 7.17 controlled entries per 20 minutes. Berglund figures to be the second or third center behind Jack Eichel and possibly Casey Mittelstadt. He should see more ice time in Buffalo and the Sabres should allow him to drive possession when he is on the ice. Thompson and Sobotka ranked 3rd and 5th, with averages of 11 and 9.45. Each of the three players have shown the ability to carry the puck into the zone. Thompson is particularly exciting here and if he earns a top 6 role this is a promising nugget, if nothing else. For comparisons sake, ROR averaged 8.35 controlled entries per 60 minutes in Buffalo this past season.
We also wanted to focus on one more possession-based metric. This one is simple, it is simply how many minutes per 60 minutes of being on ice the player spends with the puck on his stick in the offensive zone. Sabres’ fans should be encouraged by this statistic, the 3 players ranked 5th, 6th and 7th among Blues forwards with possession times of 1:36, 1:35 and 1:34. O’Reilly only possessed the puck in the offensive zone for 1:18. Of course, this is not the be all end all when evaluating forwards, but it is an encouraging sign, especially for Tage Thompson. Thompson is touted as a power forward with an elite shot. He is only 20 years old, it is a good sign that he is possessing the puck as often as his veteran counterparts.
Since possession time is not the only way to measure offensive output we also looked at how many scoring chance generating plays each player was able to make per 60 minutes. Sobotka and Thompson generated 18.9 and 18.2 scoring chances per 60 while Berglund only generated 16.3. Sobotka was a surprise here, ranking 4th on the team is impressive for a player who was playing a bottom six role for most of the season. The Sabres are losing ROR’s 20.4 chances which should really help the Blues, but the drop is not one that should cause total panic. Faceoffs and play in their own end is where the Sabres will miss O’Reilly the most.
Patrik Berglund figures to play difficult minutes against top competition to help Casey Mittelstadt ease his way into being an NHL regular. The market value analysis for Berglund had him at $4M over the next 4 years, which falls right in line with his current contract. He is not as much of a salary cap dump as some are thinking. In many ways, he will play a similar role that O’Reilly played and if used right he could produce enough points to make his contract look more than fair.
Vladimir Sobotka is the biggest “salary dump” in this trade. He has 2 years left on his deal that carries a cap hit of $3.5M. Our market valuation had him at only one year with a cap hit of $2M. Frankly put, the Sabres had the cap space and Sobotka is a competent player. A player like Sobotka with only two years left on his deal is not a horrible accusation for a team like the Sabres and he should slot in seamlessly to a bottom 6 role in Buffalo.
Lastly, Tage Thompson is the wild card in the deal. If he can fulfill his potential the Sabres have landed a scoring winger to play alongside Eichel or Mittelstadt. The sample size is too small to make any predictions about his future, but there are encouraging signs as well as some signs that would make you scratch your head. Thompson was not one of the top 3 prospects in the Blues organization, but he immediately jumps players like Nick Baptiste and Justin Bailey in Buffalo. It will be interesting to see how he takes advantage of this opportunity. We think the Sabres’ saw Mittelstadt’s success in the World Juniors with Kieffer Bellows and think Thompson could fill a similar role.
The trade truly seems like one where the Sabres gave the Blues a dollar bill, and the Blues gave the Sabres back a dollar in change. We believe that the team trading the best player in the deal almost never “wins” a trade, but this trade seems like one where both sides could end up happy this season as well as in the future.
Thank you for taking the time to read our analysis! We hope you check back in throughout the summer for more pieces like this! Stats courtesy of Natural Stat Trick and Proprietary Stats.
KYLE STICH is the Director of AFP Analytics. In addition, Mr. Stich is a tax specialist and Director of Operations at AFP Consulting LLC, whose clientele include professional athletes performing services on three separate continents. Mr. Stich earned his Master of Science in Sport Management with a Concentration in Sport Analytics from Columbia University in 2017. He earned his undergraduate degrees in Accounting and Sport Management from St. John Fisher College in 2015, where he has served as an adjunct professor teaching Sport Finance and Baseball Analytics.
JUSTIN WHITE is an intern AFP Analytics. Justin is a graduate of St. John Fisher College where he earned his degree in Sport Management and Statistics. He has worked with the Rochester Americans and members of their coaching staff on various analytics and statistics-based projects.