Sep 142013
 

A while back I came up with a stat which at the time I called LT Index which is essentially the percentage of a players teams ice time when leading that the player is on the ice for divided by the percentage of a players teams ice time when trailing that the player is on the ice for (in 5v5 situations and only in games in which the player played). LT Index standing for Leading-Trailing Index. I have decided to rename this statistic to Usage Ratio since it gives us an indication of whether players are used more in defensive situations (i.e. leading and protecting a lead and thus a Usage Ratio above 1.00) or in offensive situations (i.e. when trailing and in need of a goal and thus a Usage Ratio less than 1.00). I think it does a pretty good job of identifying how a player is used.

I then compared players Usage Index to their 5v5 tied statistics using the theory that a player being used in a defensive role when leading/trailing is more likely to be used in a defensive role when the game is tied. This is also an out of sample comparison (which is always a nice thing to be able to do) since we are using leading/trailing situations to identify offensive vs defensive players and then comparing to 5v5 tied situations that in no way overlap the leading or trailing data.

Let’s start by looking at forwards using data over the last 3 seasons and including all forwards with >500 minutes of 5v5 tied ice time. The following charts compare Usage Ratio with 5v5 Tied CF%, CF60 and CA60.

UsageRatiovsCFPct

UsageRatiovsCF60

UsageRatiovsCA60

Usage Ratio is on the horizontal axis with more defensive players to the right and offensive players to the left.

Usage Ratio has some correlation with CF% but that correlation is solely due to it’s connection with generating shot attempts for and not for restricting shot attempts against. Players we identify as offensive players via the Usage Ratio statistic do in fact generate more shots but players we identify as defensive players do not suppress opposition shots any. In fact, Usage Ratio and 5v5 tied CA60 is as uncorrelated as you can possibly get. One may attempt to say this is because those defensive players are playing against offensive players (i.e. tough QoC) and that is why but if this were the case then those offensive players would be playing against defensive players (i.e. tough defensive QoC) and thus should see their shot attempts suppressed as well. We don’t observe that though. It just seems that players used as defensive players are no better at suppressing shot attempts against than offensive players but are, as expected, worse at generating shot attempts for.

Before we move on to defensemen let’s take a look at how Usage Ratio compares with shooting percentage and GF60.

UsageRatiovsShPct

 

UsageRatiovsGF60

As seen with CF60, Usage Ratio is correlated with both shooting percentage and GF60 and the correlation with GF60 is stronger than with CF60. Note that the sample size for 3 seasons (or 2 1/2 actually) of 5v5 tied data is about the same as the sample size for one season of 5v5 data (players in this study have between 500 and 1300 5v5 tied minutes which is roughly equivalent of how many 5v5 minutes forwards play over the course of one full season).

FYI, the dot up at the top with the GF60 above 5 is Sidney Crosby (yeah, he is in a league of his own offensively) and the dot to the far right (heavy defensive usage) is Adam Hall.

Now let’s take a look at defensemen.

UsageRatiovsCFPctDefensemen

UsageRatiovsCF60Defensemen

UsageRatiovsCA60Defensemen

There really isn’t much going on here and how a defenseman is used really does’t tell us much at all about their 5v5 stats (only marginal correlation to CF60). As with forwards, defensemen that we identify as being used in a defensive are not any better at reducing shots against than defensemen we identify as being used in an offensive manner.

To summarize the above, players who get more minutes when playing catch up are in fact better offensive players, particularly when looking at forwards but players who get more minutes when protecting a lead are not necessarily any better defensively. We do know that there are better defensive players (the range of CA60 among forwards is similar to the range of CF60 so if there is offensive talent there is likely defensive talent too), and yet coaches aren’t playing these defensive players when protecting a lead. Coaches in general just don’t know who their good defensive players are.

Still not sold on this? Well, let’s compare 5v5 defensive zone start percentage (percentage of face offs taken in the defensive zone) to CF60 and CA60 (for forwards) in 5v5 tied situations.

DefensiveFOPctvsCF60

Percentage of face offs in the defensive zone is on the horizontal axis and CF60 is on the vertical axis. This chart is telling us that the fewer defensive zone face offs a forward gets, and thus likely more offensive face offs, the more shot attempts for they produce. In short, players who get offensive zone starts get more shot attempts.

DefensiveFOPctvsCA60

The opposite is not true though. Players who get more defensive face offs don’t give up any more or less shots than their low defensive zone face off counterparts. This tells me that if there is any connection between zone starts and CF% it is solely due to the fact that players who get offensive zone starts are better offensive players and not because players who get defensive zone starts are better defensive players.

You might again be saying to yourself ‘the players who are getting the defensive zone starts they are playing against better offensive players so doesn’t make sense that their CA60 is inflated above their talent levels (which presumably is better than average defensively)?  This might be true, but if zone starts significantly impacted performance (as would be the case if that last statement were true), either directly or indirectly because zone starts are linked to QoC, then there should be more symmetry between the charts. There isn’t though. Let’s look at what these two charts tell us:

  1. The first chart tells us that players who get offensive zone starts generate more shot attempts.
  2. The second chart tells us that players who get defensive zone starts don’t give up more shots attempts against.

If zone starts were a major factor in results, those two statements don’t jive. How can one side of the ledger show an advantage and the other side of the ledger be neutral? The way those statements can work in conjunction with each other is if zone starts don’t significantly impact results which is what I believe (and have observed before).

But, if zone starts do not significantly impact results, then the results we see in the two charts above are driven by the players talent levels. Knowing that we once again can observe that coaches are doing a decent job of identifying offensive players to start in the offensive zone but are doing a poor job at identifying defensive players to play in the defensive zone.

All of this is to say, NHL coaches generally do a poor job at identifying their best defensive players so if you think that guy who is getting all those defensive zone starts (aka ‘tough minutes’) are more likely to be defensive wizards, think again. They may not be.

 

Feb 112013
 

When I updated stats.hockeyanalysis.com this season I added new metrics for Quality of Teammates (QoT) and Quality of Competition (Q0C). The QoC metrics are essentially the average Hockey Analysis Rating (HARO for offense, HARD for defense and HART for overall) of the opponents that the player plays against. What is interesting about these ratings, as compared to those found elsewhere, is that I split the QoC rating up into offensive and defensive metrics. Thus, there is a QoC HARO rating for measuring the offensive quality of competition, a QoC HARD for measuring the defensive quality of competition, and a QoC HART for overall quality of compentition (basically the average of QoC HARO + QoC HARD). The resulting metrics give a result that is above 1.00 for above average competition and below 1.00 for below average competition and 1.00 would be average competition.

Let’s take a look at defensemen first and take a look at the defensemen who have the highest QoC HARO during 5v5close situations over the previous 2 seasons. This should identify the defensemen who have face the best offensive players and her are the top 15.

Player Name HARO QOC
GIRARDI, DAN 1.036
CHARA, ZDENO 1.036
GARRISON, JASON 1.035
MCDONAGH, RYAN 1.034
WEAVER, MIKE 1.033
GORGES, JOSH 1.031
ALZNER, KARL 1.029
GLEASON, TIM 1.026
SEABROOK, BRENT 1.025
BOYCHUK, JOHNNY 1.025
SUBBAN, P.K. 1.025
PHANEUF, DION 1.025
CARLSON, JOHN 1.022
HAMONIC, TRAVIS 1.021
LIDSTROM, NICKLAS 1.021

That’s actually a pretty decent representation of defensive defensemen though there is a bias towards the eastern conference in large part because the eastern conference has more offense (the top 4 teams in goals for last year were eastern conference teams while 9 of the 11 lowest scoring teams were from the western conference).

Now, lets take a look at the forwards with the toughest offensive competition.

Player Name HARO QOC
SUTTER, BRANDON 1.032
PERRON, DAVID 1.032
CALLAHAN, RYAN 1.031
FISHER, MIKE 1.03
SYKORA, PETR 1.029
BOLLAND, DAVE 1.028
ZAJAC, TRAVIS 1.028
ELIAS, PATRIK 1.028
BERGERON, PATRICE 1.027
HAGELIN, CARL 1.027
ZUBRUS, DAINIUS 1.027
PLEKANEC, TOMAS 1.027
WEISS, STEPHEN 1.026
RECCHI, MARK 1.026
ERAT, MARTIN 1.025

Not a lot of surprises there.  They are mostly third line defense first players (IMO Brandon Suter is the best defensive center in the NHL and this is just more evidence of why) or quality 2-way players though as you go further down the list you start to see more offensive players showing up like Alfredsson and Spezza which is probably evidence of a coach wanting to line match top line against top line instead of a checking line against top line.

Where things get interesting is looking at who is 300th on the list of forwards in HARO QoC. It’s none other than Manny Malhotra of massive defensive zone start bias fame. Malhotra’s HARO QoC is just 0.980 while the Canucks center who is assigned mostly offensive zone starts, Henrick Sedin, has a HARO QoC 0.994, which isn’t real difficult but is somewhat higher than Malhotra’s. So, despite all those defensive zone starts by Malhotra (presumably because he is considered a better defensive player), Henrik Sedin plays against tougher offensive opponents. How can this be? Despite Malhotra’s significant defensive zone start bias his five most frequent 5v5close opponent forwards over the previous 2 seasons are David Jones, Matt Stajan, Tim Jackman, Joran Eberle, Matt Cullen. Aside from Eberle those guys don’t really scare you much. It seems Malhotra was facing Edmonton’s top line but not Calgary’s, Minnesota’s or Colorado’s. Henrik Sedin’s top 5 opposition forwards are Dave Bolland, Dany Heatley, Curtis Glencross, Olli Jokinen and Jarome Iginla. Beyond that you have Backes, O’Reilly, Bickell, Thornton, Zetterberg, and Getzlaf. Despite the massive offensive zone start bias, it seems the majority of teams are still line matching power vs power with the Sedins. The conclusion is defensive zone starts does not immediately imply playing against quality offensive players. It can be argued that despite the defensive zone starts Manny Malhotra plays relatively easy minutes.

Using a rigid zone start system like the Vancouver Canucks do actually makes it easier for opposing teams to line match on the road as they know who you are likely to be putting on the ice depending on where the face off is. If the San Jose Sharks want to avoid a Thornton against Malhotra matchup, just don’t start Thornton in the offensive zone. Here are all the forwards with >750 5v5close minutes and at least 40% of the face offs they were on the ice for being in the defensive zone along with their HARO QoC.

Player Name HARO QOC
Manny Malhotra 0.980
Jerred Smithson 0.977
Max Lapierre 0.970
Adam Burish 0.982
Steve Ott 0.993
Jay McClement 0.983
Sammy Pahlsson 1.014
Brian Boyle 1.010
Dave Bolland 1.028
Kyle Brodziak 1.002
Matt Cullen 0.998
Paul Gaustad 0.993

Only 4 of the 12 heavy defensive zone start forwards faced opposition that was above average in terms of quality while the majority of them rank quite poorly.

It is also interesting to see who plays against the best defensive forwards.  One might assume it is elite offensive first line players but as we saw above, teams seemed to want to avoid matching up top offensive players against Manny Malhotra. So, let’s take a look.

Player Name HARD QOC
FRASER, COLIN 1.044
BOLL, JARED 1.043
MAYERS, JAMAL 1.037
JACKMAN, TIM 1.035
MACKENZIE, DEREK 1.032
ABDELKADER, JUSTIN 1.031
CLIFFORD, KYLE 1.031
EAGER, BEN 1.029
BELESKEY, MATT 1.028
MILLER, DREW 1.028
KOSTOPOULOS, TOM 1.027
MCLEOD, CODY 1.025
NICHOL, SCOTT 1.024
WINCHESTER, BRAD 1.023
PAILLE, DANIEL 1.021

Pretty much only tough guys and 3rd/4th liners on that list. Teams are deliberately using the above players in situations that avoid them facing top offensive players and as a result are facing other teams third and fourth lines and thus are facing more defensive type players.

The one conclusion we can draw from this analysis is that quality of competition is driven by line matching techniques more so than zone starts.