• The Bolts have had a rough go of it in the 2016-17 season, and there's plenty of possible sources for the struggles–but is there a solution?
By Department of Hockey Analytics
February 05, 2017

To call the current season a disappointment doesn’t do justice to the emotions that must be felt throughout the Tampa Bay Lightning organization and its fan base right now.

This summer many pundits thought GM Steve Yzerman would have to pull out the Jedi Mind Trick to keep his talented core together. When he started that project by signing Steven Stamkos and Victor Hedman to reasonably priced long-term deals and then managed to get Nikita Kucherov on a bridge deal, the Lightning rocketed to the top of many “Cup Favorite” lists.

As of the All-Star break the Lightning found themselves 22nd in the standings and their once lethal offensive attack had netted them a paltry 2.68 goals per game played (16th). 

So what happened?

Let’s start with the obvious. Tampa Bay has suffered a lot of injuries this season.

Thanks to a cool tool from NHL Injury Viz, there are lots of different ways to visualize just how bad things have been, but the charts below are probably the most instructive.

Illustrated Review: Why Patrick Maroon is such a good fit for Connor McDavid

The first shows how much of each team’s cap hit was allocated to injured players in each game (CHIP). The blue areas indicate a team that’s healthy; the red ones, a team that’s thoroughly depleted.

via NHL Injury Viz

Of course, as every fan knows, even clubs as smart as the Lightning occasionally make mistakes or end up with players on long-term deals who provided value at one point but are now overpaid. So while injuries are never a blessing, the loss of an overpaid but under-performing vet doesn’t hurt as much as the chart above might indicate.

Which is why the following visualization is even more awesome. The circles indicate the specific games a player missed due to injury (the colors reflect his position, so goalies are green, forwards blue, and defensemen red).

NHL Injury Viz

Tampa Bay’s CHIP started to look ugly as soon as Steven Stamkos went down with a knee injury at the 17 game mark, but Ryan Callahan, who has been out for most of the season as well, was clearly in decline anyway. So he’s less of a loss than his $5.8 million cap hit might suggest.

But during a five-game stretch the Lightning were also without Kucherov and Ondrej Palat. 

In light of the carnage, Yzerman must have been wondering if he had enough juice left to suit up.

There’s no doubt injuries have hurt the Bolts. But this narrative belies a more fundamental problem that was starting to become obvious before the Stamkos injury.

As we noted last month, Tampa already had worse than coin toss odds of making the playoffs at the 25 game mark. Many may have snickered at the time, but we bucked the “experience matters in a long NHL season” conventional wisdom and gave the rookie-laden Toronto Maple Leafs squad, which was two points behind Tampa Bay at that point, a 62.5% chance of making the playoffs vs. the Bolts' 44.3%.

Analytics: NHL playoff probabilities at the quarter mark

We based this largely on the fact that the Lightning’s offensive attack had more or less sputtered. Suddenly a team that had been known for generating both shot attempts and quality scoring chances struggled to produce either.

To be fair, Stamkos had already been gone for eight games by then, so let’s turn back the clock and see what the team has done over the past few years during the regular season.  

The chart below shows Tampa Bay’s shot attempt percentage (CF%), scoring chance percentage (SC%) and high danger scoring chance percentage (HDSC%).

All stats are courtesy of naturalstattrick.com and are 5-on-5

You might notice a pattern. 

In 2014-15 the Lightning dominated by pounding opponents with their speed and skill. They didn’t just outshoot other teams, they often undressed opposing defenses by getting more than 55% of the high danger chances.

Most pundits missed how good they were at the time, but it was why we predicted them to win the Stanley Cup that season. They had another strong effort in 2015-16, although not quite as impressive. 

This season, however, has been a different story from the start.

In every category Tampa Bay stumbled out of the gate, and surprisingly their underlying performance has mostly improved in Stamkos’s absence. It appears that even before Stamkos got hurt, other teams had started to learn how to shut this team down.

To his credit, coach Jon Cooper has acknowledged the problem, which suggests he’s probably spending a lot of time thinking about a solution.

The chart below provides further context for what’s going on here.  Specifically, it shows the number of shot attempts against per 60 minutes (CA/60), scoring chances against per 60 minutes (SCA/60) and high danger scoring chances against per 60 minutes (HDSCA/60). 

All stats are courtesy of naturalstattrick.com and are 5-on-5

Put simply, Tampa’s team defense was horrendous at the start of this season. Its CA/60 remains solid and only a modest decline from 2014-15, but the real problem has been shot quality.

We can debate whether or not the Lightning were actually good at playing defense or were simply the embodiment of the adage that the best defense is a great offense. Regardless, the effect was that during the 2014-15 season they kept opponents to 8.4 high danger chances per 60 minutes, which was eighth best in the league. That number actually improved to 8.2 last season, the NHL's second best. 

This year they’ve been giving up 10.4 HDSCA/60 (16th), and the disturbing part is they’ve improved from 10.7 to 10.2 in the 33 games since Stamkos was injured.

It’s fair to ask who are the culprits here. The table below, which shows every Tampa Bay player with more than 300 5-on-5 minutes played in 2016-17, is sorted from the most to fewest HDSCA/60. 

Player TOI/GP CF/60 CA/60 SCF/60 SCA/60 HDSCF/60 HDSCA/60
Vladislav Namestnikov 11.7 61.1 51.9 32.4 25.7 12 11.6
Jonathan Drouin 13.4 55.3 52.5 28.4 26.4 9.8 11.1
Nikita Kucherov 14.2 58.4 48.5 30.2 25.5 12 11.1
Cedric Paquette 9.7 54.3 55.6 24.1 26.6 9.6 10.8
Ondrej Palat 13.1 53.8 52.6 28.4 26.5 10.2 10.7
Braydon Coburn 13.6 56 50.5 28.5 25.4 11.1 10.7
Nikita Nesterov 14.6 60.1 49.9 28.1 25.2 10.2 10.6
Valtteri Filppula 12.8 54.8 54.5 26 27.8 9.7 10.6
Slater Koekkoek 12.3 51 56.5 24.3 27.2 10.8 10.5
Alex Killorn 13.3 53.9 55.3 25.5 29.8 8.9 10.5
Tyler Johnson 12.7 51.6 54.7 25.6 27.1 8.8 10.4
Jason Garrison 15.7 48.6 53.4 21.6 26.1 7.1 10.3
Anton Stralman 16.9 56.8 51.4 30.4 27.1 12.5 10.1
Andrej Sustr 15.4 49.9 55.1 22.6 26.9 6.8 10
Victor Hedman 17.5 57.1 51.2 28.2 25.6 9.8 9.8
Brayden Point 12.5 55.5 52 27.9 25.8 9.7 9.6
J.T. Brown 9.4 51.3 52.2 22.2 25 8 7.8
Brian Boyle 10.5 57.5 45.9 28.9 20.7 10.6 7.8
Mattias Ekholm Underlying Stats
Season TOI/GP CF/60 CA/60 SCF/60 SCA/60 HDSCF/60 HDSCA/60
2014-15 16.2 57.3 45 19.7 14.5 9.1 7.7
2015-16 16.8 53.1 46.1 19.8 14.6 10.1 6.8
2016-17 18.3 59.2 51.3 27.8 21.6 9.2 6.9
Ryan Ellis Underlying Stats
Season TOI/GP CF/60 CA/60 SCF/60 SCA/60 HDSCF/60 HDSCA/60
2014-15 15.6 58.2 46.9 20.3 15.8 8.9 7.8
2015-16 16.8 55.9 46.3 20.6 15 10.7 7.2
2016-17 18.2 57.4 59.2 27.3 27 9.6 8.8