22-23 Bouncing Back Nominees, Including Schwartz, Peterson & Werensky – DobberHockey

Last week, we used a custom table generated from Frozen Tool Reports to get an idea of ​​some of the players who could be in line to disappoint if we take their 2021-22 production seriously. This week we’ll flip the script and see what the same data points tell us about the players who might be ready to bounce back.

This week in Frozen Tool Forensics: Possible Bounce Candidates

As a general reminder, here’s some background information from the past week to explain what we’re looking for and why.

For the purposes of these tables, target stats were personal shooting percentage, fifth team shooting percentage on fives, IPP, and secondary assist percentage. I was also concerned with time on the ice, and expected goal numbers, but the schedule got a bit tricky for this format, so I lowered my standards a bit. I picked a lot of these stats because aside from time on the ice and expected goals (which I didn’t include at the end), there is a lot of variance in the score. If players show deviations from their standards in these stats, it is likely that at some point it will fall back to average.

I used the Big Board report to capture time on ice, numbers of games played, point cadence numbers, and time on ice (I used point velocity and numbers of games played to calculate small sample sizes and ensure we were focusing on fantasy-related players). Next, I checked out the Advanced Stats report for my five-for-five imaging performance, IPP, and secondary assist ratio. I also used the time frame feature on the reports page so I could compare the 21-22 data to this player’s recent average. I ran a report for the 21-22 season, then a three-year report to get the reference point.

The table below shows all candidates who performed poorly across the board in 21-22 from the average of the last three years.

change in performance
Noun POS age Team s% 5on5S% IPP second assistant%
David Buster R 26 boss -1.3% -0.80 -4.50 -1.67
Patrick King R 33 chi -0.8% -0.40 -1.87 -3.40
Jacob Forske R 33 Central Bank of Jordan -3.0% -0.60 -0.53 -8.77
Tyler Toffoli R 30 CGY -2.7% -1.07 -2.70 -2.00
Jack Eichel c 25 VGK -1.8% -0.30 -8.40 -10.87
Niklas back c 34 WSH -2.5% -0.07 -8.70 -4.47
Conor Brown R 28 WSH -3.0% -0.27 -0.70 -8.73
Zach Ferensky Dr 25 Central Bank of Jordan -2.8% -0.13 -6.00 -2.30
Sean Cotter c 29 PH -4.4% -2.57 -7.73 -16.13
Cam Fowler Dr 30 ANA 0.0% -0.07 -0.87 -11.40

To read this table, we start with some basic information about the player (position, age and team), and then move on to changes in performance. For Tyler Toffoli, his shot has fallen from about 13 percent on average over the past three seasons to just over 10 percent at 21-22, a drop of about three percentage points.

David Pastrnak and Patrick Kane aren’t very interesting here because all of their changes are fairly small. Niklas Backstrom and Sean Couturier can be ignored for the time being due to injury issues. Someone like Jack Eichel is interesting because he was performing reasonably well on his own, but his IPP and auxiliary rates were a bit low which meant he didn’t score as many goals as we would normally expect. I imagine this is something that is likely to bounce back rather than a reflection of its new environment.

Zach Werenski is the most interesting here. He set a career high 58-point pace, but somehow he’s making the list of potential rebounds. His team’s average was good, but his personal goal average, and his IPP were low which means that if he continues to spread (which Seth Jones should still be in Chicago), he could be on the streak for another career best.

The above list only contains players who were below average across the board, but the players aren’t that specific. In the following tables I want to look at some of the cutting edge differences.

The first is the portrait photography ratio. These players all had a payback percentage of at least three and a half percent lower than their average recent career. For the sake of space, I edited the list a little manually. Since we’re focusing on players who might bounce, I’ve removed players for whom hit percentage was the only key number.

Noun POS age Team s% 5on5S% IPP second assistant%
Phil Kessel R 34 VGK -4.91% 2.30 -7.07 -3.87
TJ O’Shea R 35 WSH -4.39% -1.53 1.53 13.77
Sean Cotter c 29 PH -4.38% -2.57 -7.73 -16.13
Final Travis R 25 PH -3.79% 0.37 -3.83 -15.47
Jaden Schwartz The 30 Sea -3.49% -0.23 2.77 -9.07

There are some interesting names here. Phil Kessel looked like he deserved a little better in most cases, plus going to a new team that has a chance maybe to join the top six / get some looks with Eichel. This definitely makes it an interesting post of late.

Travis Konechny didn’t have a “landing year” unless you assumed his 75-point pace season was his benchmark. Otherwise, his point speed matches most of the rest of his career. Despite that, he seems to deserve the best, and as Konesny’s manager for most of last season, I’ve been waiting for the “best” to come out. The problem this year is just Philly in general. With Couturier out and Claude Giroud gone, it remains to be seen if Konecny ​​has anyone to play with, and I think he’s made it clear he can’t do it alone.

I love Jaden Schwartz as a candidate but the most important thing is health. He was fine, if not great when he was healthy, but the numbers suggest he deserves a little better. With reinforcements in the Seattle fold, there should be more targets to cross, and the hope is that Schwartz will be a part of that.

The following table includes those players whose team shooting percentage decreased from five to five by more than two percent. Again, the caveat states that some players have been removed for visual access if there are no other red flags (or if they are Sean Couturier – which was already discussed and might miss the entire season anyway).

Noun POS age Team s% 5on5S% IPP second assistant%
Elias Peterson c 23 transportation car 0.12% -3.50 4.50 0.33
Brooke Bowser R 25 transportation car -0.48% -3.40 -2.27 7.60
Patrice Bergeron c 37 boss -3.12% -2.53 8.10 -2.33
Jacob Franna The 26 The 3.81% -2.07 13.40 -10.50
Zach Hyman R 30 EDM -1.84% -2.03 0.33 -14.83

Love this Elias Peterson and Brooke Bowser. Sure enough, Peterson’s hot second half earned his personal shooting percentage and IPP, but his buddies still scored well below normal while on the ice. That should bounce a bit and benefit him and Boeser.

The final table here is for those players whose IPP was 10 points or more worse than their last average.

Noun POS age Team s% 5on5S% IPP second assistant%
Tyler Seguin R 30 DA 1.88% -0.23 -17.17 8.20
Nikolai Ehlers The 26 WPG -0.99% 0.40 -11.17 -9.93
Andrei Burakovsky The 27 Sea -2.47% 0.43 -11.13 -2.33
Ricard Raquel R 29 pit 2.31% 0.73 -11.03 6.77
Thomas Hertle c 28 SJ -0.34% 0.70 -9.93 -3.13

One of the odd things about this list is how different the secondary help numbers are across the board. One possible explanation for the low IPP is that players didn’t get the usual amount of secondary passes, but that’s only true in a meaningful way for Nikolaj Eilers. 2 or 3 percent for other players isn’t that big of a fluctuation in the secondary assist rate. Ehlers is certainly the most interesting here. His total points production closely mirrors his 19-20-point tempo season of 70, but the core numbers are very similar to his 80-point tempo season of the 20-21 season. It doesn’t seem entirely out of the realm of possibilities that he might return to that 80-point pace given these numbers.

Andrei Burakovsky is the other interesting person here but given his move to Seattle and how much it will change for him, it’s hard to read those numbers. He should get more ice and more opportunities, but it remains to be seen if he can rise to the top streak role he is likely to get on Team Kraken.

That’s all for this week

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