Frozen Tools Forensics: Deployment From Second-Round Playoff Exits

Chris Kane

2022-06-24

We are back this week with our analysis of the playoff rounds. And no, we won't be talking about that overtime goal. We have moved through all of the first-round exits, and this week will turn our attentions to the teams that didn't survive the second round.

This week on Frozen Tool Forensics: Second Round Exits

The teams in question this week are St. Louis, Calgary, Carolina and Florida. Given that these are two-series teams, our sample size is beginning to look a little larger. In this case we have a range of 10-14 games for teams (obviously less for specific players if they were benched or injured)

We are starting to get some larger sample sizes but are still predominantly going to focus on deployment and look at how players were utilized in these win-or-go-home series. Doing so might give us a bit of insight into how coaches are viewing certain players and who might be primed for a different role next season compared to this one.

So far, we have been working under the caveat that these trends should be taken with a grain of salt because they are small sample sizes, and at the end of the day these teams lost. These second-round exits did at least win one round so something about their strategy worked at least a bit. It gives a little bit more weight to what we might see in the structures (with the possible exception of Florida. Not exactly sure what is going on there right now, or how Paul Maurice will change things).

Additional notes from last week's article.

And now on to the process. We will be looking at deployment and specifically percent of time on the power-play, at even strength, and total time on ice. We will be using percent as overtime games can add significant time to a player's overall count without changing that player's real deployment opportunity. In order to get this data, we will be running a custom Time on Ice report for the playoffs and comparing that to a second custom Time on Ice report for the last two months of the regular season. That comparison will tell us which players have gained or lost time between these two samples.

 So now on to the data. First up: Total Time on Ice

NamePosAgeTeamGP%PP Playoff%EV Playoff%TOI Playoff%PP Season%EV Season%TOI Season%PP Change%EV Change%TOI Change
RYAN O’REILLYC31STL1256.73235.154.228312.504.004.10
MIKAEL BACKLUNDC33CGY123630.531.726.52727.69.503.504.10
DAVID PERRONR34STL1258.133.132.558.427.828.5-0.305.304.00
COLTON PARAYKOD29STL1214.943.841.63.840.337.611.10</