Does hitting lead to winning in the NHL? (Puck Momalytics)

Jen Lute Costella
Puck Daddy
Nov 4, 2014; Winnipeg, Manitoba, CAN; Winnipeg Jets defenceman Jacob Trouba (8) hits Nashville Predators defenceman Ryan Ellis (4) during the third period at MTS Centre. Winnipeg wins 3-1. (Bruce Fedyck-USA TODAY Sports)
Nov 4, 2014; Winnipeg, Manitoba, CAN; Winnipeg Jets defenceman Jacob Trouba (8) hits Nashville Predators defenceman Ryan Ellis (4) during the third period at MTS Centre. Winnipeg wins 3-1. (Bruce Fedyck-USA TODAY Sports)

(Jen Lute Costella is our new analytics writer, breaking down the fanciest of stats for you each week. She's a mom. She's writing for Puck Daddy. Hence, Puck Momalytics) 

Hockey fans have always loved hits for their entertainment value. Coaches and analysts spend tons of time during the season talking about the need for physicality. Fans of skill teams default to bemoaning a lack of big hitters as soon as the team struggles in a game. The question is, does hitting really make a difference? Is this much ado about nothing or is hitting actually important to the game?

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We can all think of times when a hit has caused a player to lose the puck so there are certainly times when a little physicality can make good things happen. We can also all think of times when a player ended up completely out of position on the play because he was too busy chasing a hit. Hitting is part of the game though so how hitting is used and the effect it has on play is an interesting topic. 

What is the purpose of hitting in the NHL? Ideally, hits are supposed to stifle a team’s offensive attack. If players and teams are using hitting correctly, it should show in shot suppression metrics, i.e. stats that show the shooting rates and offensive pressure of opponents.

Team Level Analysis

Above is a graph plotting each team’s Hits Per 60 (hitting rate) and Fenwick Against Per 60, which measures the opponent’s shooting rates. Teams near the bottom have lower FA60, which means they have done a better job of limiting or suppressing their opponent’s shots so far this season. Teams higher on the graph have allowed shots by their opponents at a higher rate. Teams with lower hitting rates are at the left with the rates increasing as the plot moves to the right.

Hitting rates and opponents’ shooting rates correlate (R2 = 0.2136) in a manner suggesting that either teams allowing more shots against hit more frequently or that teams with higher hitting rates are giving up shots against more frequently. This seems counter-intuitive if hitting in hockey is designed to thwart an offensive attack. Because this is a small sample size due to only covering the 2014-15 season, let’s look at other seasons to see what correlations may exist.

 

The correlation falls very far once we look past this season alone at least on a team level. Over a longer sample, team level hitting rates do not seem to have a positive effect on shot suppression.

 

If we look at this from the perspective of CF% (Corsi For Percentage), we see that again there is no meaningful correlation between hitting rates and puck possession on the team level. The Stanley Cup winning teams from 2007-08 to 2013-14 are marked in red with their opponent marked in yellow. These are regular season measures at even strength with no score adjustment applied. The Cup winning teams are located along the entire spectrum of hitting rates, although the larger concentration of finalists and winners is near or below the 27.00 Hits Per 60 mark.

The one area where there is fairly good correlation on the team level, is a comparison between hitting rates and zone starts.

 

Teams with higher offensive zone starts per 60 tend to take hits at a higher frequency than others. The data used for the graph above spans from 2005-06 through the present season.

Likewise, teams with more defensive zone starts per 60 tend to hit their opponents at a higher frequency than others. This makes sense when you consider that hitting as a tactic is designed to quell the offensive attack of a team’s opponent.

Player Level Analysis

If you watch a lot of hockey, you know that defensemen seem to be different when it comes to style of play. Some defensemen are known for being big hitters while others are speedy skaters that don’t ever seem to hit. The numbers evidence this as well.

 

 

The graph above shows all defensemen with at least 200 minutes of ice time from 2007-08 through 2013-14. There is really no correlation between these players’ hitting rates and their opponents’ shooting rates. The dense grouping of defensemen spans a wide range of FA60 values as would be expected; however, the vertical grouping is also fairly wide indicating a large range of hitting rates.

When we shift the look to Hits Per 60 and Hits Taken Per 60 there is an interesting difference in defensemen 

Forwards 200+ Time on Ice from 2007-08 through 2013-14

The forwards show a much higher correlation between Hits Per 60 and Hits Taken Per 60 than the defensemen do during the same period. Because defensemen are used very differently and play differently than forwards, the data we have for them is not as useful to explore how hitting is used in modern hockey. Instead of inserting a lot of noise into the data by including defensemen, we will look at how hitting is used by forwards.

 

Using QoT (Quality of Teammates) metrics based upon CF% to look at forwards’ On Ice Shooting Percentage (OnIce sh%), the increase in QoT correlates to an increase in OnIce sh% at R2 0.0782. This isn’t as high as one may expect. This is likely due to the difference in puck possession strength at the team level. When we change our tactics to use QoT based upon Time on Ice, the analysis is much different.

The correlation between a forward’s QoT and OnIce sh% is much higher, R2 0.3971 when using Time on Ice to categorize teammates. This is logically sound when we think practically about the way forwards are used. The forwards getting lower ice time per game are usually those playing in the bottom six or outside of a team’s top two scoring lines which often get far more ice time per game. Because QoT based upon TOI seems to line up a bit more with the in-game use of forwards, it makes sense to use that to categorize forwards in this analysis.

 

Hitting rates for forwards tend to decrease as their Quality of Teammates increases. Plainly put, the forward lines lower on the depth chart tend to incorporate higher hitting rates into their tactics more regularly than the scoring lines. When teams send out their bottom six forwards in a game, we often hear that they are out there to bring “energy”. I think it’s safe to say that “energy” translates to “go hit some guys” more often than not in hockey at this point in time.

What’s most curious about this is that the players with the highest hitting rates are also often the players with the highest hits taken rates as seen on the “Forwards 200+ Time on Ice from 2007-08 through 2013-14 Hits Per 60 versus Hits Taken Per 60” graph. The correlation is R2 0.2523. Essentially, this seems to indicate that the energy lines are often matched up against other energy lines or that their opponents increase their hitting rates when these energy lines are on the ice.

By increasing the time on ice threshold for forwards to 300 minutes in a season, which is still very low, we remove even more of the noise from the data.

Again, this supports the idea that the lower QoT forwards are those with the more frequent hitting rates when we see the correlation between OnIce sh% and hitting rates above.

 

A similar pattern emerges when CF% Relative, which measures puck possession strength relative to a player’s teammates, is compared to Hits Per 60. The players with the higher hitting rates tend toward being on the lower end of the team’s effective puck possession players. This is not an absolute of course, but it is an observable pattern in the data that gives us insight into how players are being used and whether that usage is effective.

The hard hitting power forwards in the league that produce a high number of points are few and far between as we saw in the first part of this look at hitting. 

Many of the heavy hitting forwards in the league play on the lines considered to be in the bottom six of the depth chart. We know that players are often, but not always, given ice time based upon talent or their perceived value from a team perspective.

 

The graph above breaks forwards with at least 200 minutes of ice time per season into groups based upon average ice time per game. It includes data during even strength play from the 2007-08 season through the 2013-14 season. Players in the 0-19.99% group are those with the lowest time on ice per game. This increases until we get to the 80-100% group which has the highest time on ice per game.

The goals, assists, hits and hits taken are the raw numbers and not rate stats. The percentages on the vertical axis represent the portion of the total goals, assists, hits and hits taken by the entire group attributable to each of the TOI/Game groups.  The lowest TOI/Game group is responsible for the lowest portion of the goals and assists. The percentages are significantly lower than the 20% groupings. It is interesting to note that this group is responsible for more than 20% of the hits though. The same observations can be made for the next two groups of TOI/Game forwards in that they are responsible for a higher percentage of hits and hits taken than goals and assists.

The top two groups of forwards are responsible for nearly 60% of the goals and assists compared to the bottom three groups having only 40%. The top two groups are responsible for less than 40% of the hits dished out while taking nearly 55% of the hits.

Looking only at this season, despite the fact that we are working with a much smaller sample size than the previous graph, the same trends hold true. The groups with the lower TOI/Game are disproportionately responsible for hits and hits taken while the highest TOI/game groups are underrepresented in the Hits column.

So, do all these hits help the lower TOI/Game group forwards slow down their opponents?

This graph shows Fenwick For Per 60 and Fenwick Against Per 60 for forwards with at least 200 minutes of time on ice per season from 2007-08 through 2013-14. The blue markers represent the bottom two groups of forwards in terms of TOI/Game. The red markers are all of the other forwards.

There is very little correlation for either of these groups, which is not surprising; however, it is worth noting that the majority if the blue markers are on the lower end of FF60. This means that the team is not generating as much in terms of shot attempts with the lower TOI/Game player on the ice.

What does all of this tell us? Well, it means that there does not seem to be much of an appreciable benefit from having a high hitting rate.

Likewise, there does not seem to be much of a benefit in having a line of “energy” guys other than to give a little bit of a rest to the players on the scoring lines. While hitting may hold some benefits, these benefits seem reserved mostly for the high scoring power forwards and episodically when other players make a hit that causes a turnover.

As an overall tactical approach though, there does not seem to be a good link between hitting and suppressing the opponent’s offensive attack, which is supposed to be the point of it as a tactic in the first place.

*All data herein collected from war-on-ice.com and NHL.com and current through at least 11/22/14

 

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