Every now and again someone asks me how I calculate HARO, HARD and HART ratings that you can find on stats.hockeyanalysis.com and it is at that point I realize that I don’t have an up to date description of how they are calculated so today I endeavor to write one.

First, let me define HARO, HARD and HART.

HARO – Hockey Analysis Rating Offense
HARD – Hockey Analysis Rating Defense
HART – Hockey Analysis Rating Total

So my goal when creating then was to create an offensive defensive and overall total rating for each and every player. Now, here is a step by step guide as to how they are calculated.

Calculate WOWY’s and AYNAY’s

The first step is to calculate WOWY’s (With Or Without You) and AYNAY’s (Against You or Not Against You). You can find goal and corsi WOWY’s and AYNAY’s on stats.hockeyanalysis.com for every player for 5v5, 5v5 ZS adjusted and 5v5 close zone start adjusted situations but I calculate them for every situation you see on stats.hockeyanalysis.com and for shots and fenwick as well but they don’t get posted because it amounts to a massive amounts of data.

(Distraction: 800 players playing against 800 other players means 640,000 data points for each TOI, GF20, GA20, SF20, SA20, FF20, FA20, CF20, CA20 when players are playing against each other and separate of each other per season and situation, or about 17.28 million data points for AYNAY’s for a single season per situation. Now consider when I do my 5 year ratings there are more like 1600 players generating more than 60 million datapoints.)

Calculate TMGF20, TMGA20, OppGF20, OppGA20

What we need the WOWY’s for is to calculate TMGF20 (a TOI with weighted average GF20 of the players teammates when his team mates are not playing with him), TMGA20 (a TOI with weighted average GA20 of the players teammates when his team mates are not playing with him), OppGF20 (a TOI against weighted average GF20 of the players opponents when his opponents are not playing against him) and OppGA20 (a TOI against weighted average GA20 of the players opponents when his opponents are not playing against him).

So, let’s take a look at Alexander Steen’s 5v5 WOWY’s for 2011-12 to look at how TMGF20 is calculated. The columns we are interested in are the Teammate when apart TOI and GF20 columns which I will call TWA_TOI and TWA_GF20. TMGF20 is simply a TWA_TOI (teammate while apart time on ice) weighted average of TWA_GF20. This gives us a good indication of how Steen’s teammates perform offensively when they are not playing with Steen.

TMGA20 is calculated the same way but using TWA_GA20 instead of TWA_GF20. OppGF20 is calculated in a similar manner except using OWA_GF20 (Opponent while apart GF20) and OWA_TOI while OppGA20 uses OWA_GA20.

The reason why I use while not playing with/against data is because I don’t want to have the talent level of the player we are evaluating influencing his own QoT and QoC metrics (which is essentially what TMGF20, TMGA20, OppGF20, OppGA20 are).

Calculate first iteration of HARO and HARD

The first iteration of HARO and HARD are simple. I first calculate an estimated GF20 and an estimated GA20 based on the players teammates and opposition.

ExpGF20 = (TMGF20 + OppGA20)/2
ExpGA20 = (TMGA20 + OppGF20)/2

Then I calculate HARO and HARD as a percentage improvement:

HARO(1st iteration) = 100*(GF20-ExpGF20) / ExpGF20
HARD(1st iteration) = 100*(ExpGA20 – GA20) / ExpGA20

So, a HARO of 20 would mean that when the player is on the goal rate of his team is 20% higher than one would expect based on how his teammates and opponents performed during time when the player is not on the ice with/against them. Similarly, a HARD of 20 would mean the goals against rate of his team is 20% better (lower) than expected.

(Note: The OppGA20 that gets used is from the complimentary situation. For 5v5 this means the opposition situation is also 5v5 but when calculating a rating for 5v5 leading the opposition situation is 5v5 trailing so OppGF20 would be OppGF20 calculated from 5v5 trailing data).

Now for a second iteration

The first iteration used GF20 and GA20 stats which is a good start but after the first iteration we have teammate and opponent corrected evaluations of every player which means we have better data about the quality of teammates and opponents the player has. This is where things get a little more complicated because I need to calculate a QoT and QoC metric based on the first iteration HARO and HARD values and then I need to convert that into a GF20 and GA20 equivalent number so I can compare the players GF20 and GA20 to.

To do this I calculate a TMHARO rating which is a TWA_TOI weighted average of first iteration HARO. TMHARD and OppHARO and OppHARD are calculated in a similar manner. TMHARD, OppHARO and OppHARD are similarly calculated. Now I need to convert these to GF20 and GA20 based stats so I do that by multiplying by league average GF20 (LAGF20) and league average GA20 (LAGA20) and from here I can calculated expected GF20 and expected GA20.

ExpGF20(2nd iteration) = (TMHARO*LAGF20 + OppHARD*LAGA20)/2
ExpGA20(2nd iteration) = (TMHARD*LAGA20 + OppHARD*LAGF20)/2

From there we can get a second iteration of HARO and HARD.

HARO(2nd iteration) = 100*(GF20-ExpGF20) / ExpGF20
HARD(2nd iteration) = 100*(ExpGA20 – GA20) / ExpGA20

Now we iterate again and again…

Now we repeat the above step over and over again using the previous iterations HARO and HARD values at every step.

Now calculate HART

Once we have done enough iterations we can calculate HART from the final iterations HARO and HARD values.

HART = (HARO + HARD) /2

Now do the same for Shot, Fenwick and Corsi data

The above is for goal ratings but I have Shot, Fenwick and Corsi ratings as well and these can be calculated in the exact same way except using SF20, SA20, FF20, FA20, CF20 and CA20.

Goalies are a little unique in that they only really play the defensive side of the game. For this reason I do not include goalies in calculating TMGF20 and OppGF20. For shot, fenwick and corsi I do not include the goalies on the defensive side of things either as I assume a goalie will not influence shots against (though this may not be entirely true as some goalies may be better at controlling rebounds and thus secondary shots but I’ll assume this is a minimal effect if it does exist). The result of this is goalies do have a HARD rating but no HARO, or shot/fenwick/corsi based HARD or HARO rating.

I hope this helps explain how my hockey analysis ratings are calculated but if you have any followup questions feel free to ask them in the comments.

Lidstrom has officially announced his retirement from the NHL ending what was one of the best, if not the best, NHL career by an NHL defenseman, and for that matter one of the best careers of any NHL player.  Bobby Orr may have been a better and more dynamic defenseman in his prime but Lidstrom was the dominant defenseman during his time in the NHL and had the longevity that Bobby Orr never had.  In fact, Lidstrom was still a dominant defenseman in the NHL into his 40’s.  Since I have the data readily available, let’s take a look at Lidstrom’s impact on the Red Wings the past 5 seasons, or ages 37-41.

I believe the best way to evaluate a player is that players impact on his teammates, often called WOWY (with or without you).  Here are Lidstroms teammates WOWY goals for percentage for each player who played 300 minutes of 5v5 zone start adjusted ice time with Lidstrom over the past 5 seasons.

2011-12

 Player Season w/ Lidstrom wo/ Lidstrom w/ – wo/ White 2011-12 62.9% 52.5% 10.4% Howard 2011-12 60.6% 61.1% -0.5% Datsyuk 2011-12 67.6% 61.3% 6.3% Franzen 2011-12 78.8% 55.8% 23.0% Bertuzzi 2011-12 68.8% 61.1% 7.7% Zetterberg 2011-12 58.8% 57.5% 1.3% Filppula 2011-12 54.5% 61.0% -6.5% Average 2011-12 64.6% 58.6% 6.0%

2010-11

 Player Season w/ Lidstrom wo/ Lidstrom w/ – wo/ Howard 2010-11 56.4% 48.4% 8.0% Stuart 2010-11 53.2% 50.0% 3.2% Zetterberg 2010-11 50.0% 48.2% 1.8% Franzen 2010-11 56.7% 54.7% 2.0% Bertuzzi 2010-11 50.0% 51.5% -1.5% Datsyuk 2010-11 55.8% 58.1% -2.3% Holmstrom 2010-11 52.0% 45.7% 6.3% Average 2010-11 53.4% 50.9% 2.5%

2009-10

 Player Season w/ Lidstrom wo/ Lidstrom w/ – wo/ Howard 2009-10 58.3% 47.2% 11.1% Rafalski 2009-10 57.9% 53.6% 4.3% Datsyuk 2009-10 63.8% 52.5% 11.3% Zetterberg 2009-10 55.1% 50.0% 5.1% Bertuzzi 2009-10 59.0% 39.6% 19.4% Holmstrom 2009-10 63.3% 50.0% 13.3% Osgood 2009-10 45.8% 32.5% 13.3% Cleary 2009-10 51.6% 45.2% 6.4% Average 2009-10 56.9% 46.3% 10.5%

2008-09

 Player Season w/ Lidstrom wo/ Lidstrom w/ – wo/ Rafalski 2008-09 63.5% 50.0% 13.5% Osgood 2008-09 62.0% 46.4% 15.6% Datsyuk 2008-09 58.8% 73.3% -14.5% Conklin 2008-09 61.5% 57.6% 3.9% Zetterberg 2008-09 55.6% 48.8% 6.8% Hossa 2008-09 68.4% 66.7% 1.7% Cleary 2008-09 48.4% 45.0% 3.4% Franzen 2008-09 73.7% 60.4% 13.3% Average 2008-09 61.5% 56.0% 5.5%

2007-08

 Player Season w/ Lidstrom wo/ Lidstrom w/ – wo/ Rafalski 2007-08 69.6% 50.0% 19.6% Datsyuk 2007-08 77.6% 58.5% 19.1% Osgood 2007-08 72.2% 48.6% 23.6% Zetterberg 2007-08 69.8% 58.3% 11.5% Hasek 2007-08 73.0% 58.3% 14.7% Holmstrom 2007-08 78.1% 48.3% 29.8% Average 2007-08 73.4% 53.7% 19.7%

As you can see, almost every player Lidstrom has played significant minutes with over the past 5 seasons had better results when Lidstrom was on the ice with them than when he wasn’t.  Of the 36 player seasons listed above, only 5 times did a player peform better without Lidstrom than with and only twice could you call the difference substantial (Filppula’s 6.5% in 2011-12 and Datsyuk’s 14.5% in 2008-09).  To me that is a sign of greatness, especially considering a lot of the players Lidstrom plays with are great players in their own right.

Regular readers of HockeyAnalysis.com are probably aware of my rating system that takes into account on-ice results, quality of teammates and quality of competition and takes into account all of the information shown in the tables above.  My ratings are HARO+ for offensive rating, HARD+ for defensive rating and HART+ for total overall rating.  Here are Lidstrom’s ratings over the past 5 seasons.

 Season HARO+ HARD+ HART+ 2011-12 1.060 1.097 1.079 2010-11 1.198 0.896 1.047 2009-10 1.157 1.014 1.086 2008-09 1.145 1.205 1.175 2007-08 1.397 1.474 1.435

Lidstrom’s 2007-08 season was truly a remarkable season.  Anything better than 1.00 is very good and above average but to have both offensive and defensive ratings in the 1.400 range or higher is truly remarkable and he deservedly earned the Norris Trophy for top defenseman in the NHL that year.  He hasn’t matched his 2007-08 season since but his numbers have still been quite good and remarkably consistent for an aging NHL player, save for his defensive rating in 2010-11.  Lidstrom won the Norris Trophy in 2010-11 but I did not believe he deserved it as there were more deserving defensemen (specifically, Zdeno Chara).  But regardless, Lidstrom has been and still is a top tier defenseman.

Over the past 4 seasons there have been 68 defensemen to play 4000+ minutes of zone start adjusted 5v5 ice time.  Of those defensemen Lidstrom ranks 9th in HARO+13th in HARD+ and 4th in HART+.  The only defensemen more valuable overall over the past 4 seasons are Chara (excellent offensive and defensive play), Willie Mitchell (excellent defensive play which we are clearly seeing these playoffs) and Marc-Edouard Vlasic (excellent defensive ability, good offensive play).  Of the 68 defensemen there are only 6 defensemen who have both a HARO+ and a HARD+ rating above 1.00 and Lidstrom is one of them (Chara, Matt Carle, Christian Ehrhoff, Toni Lydman, and Keith Yandle are the others).  Having both top end offensive ability and top end defensive ability is what makes Lidstrom so great, and this is just looking at his years at the end of his career.  Statistics from his prime years are probably ridiculously good.

The big question is how will the Red Wings possibly replace Lidstrom.  Everyone is pointing to Ryan Suter who is set to become an unrestricted free agent this summer and there is little doubt that the Red Wings will show some serious interest.  So how does Suter stack up against Lidstrom?  Let’s look at his ratings over the past 5 seasons.

 Season HARO+ HARD+ HART+ 2011-12 1.012 1.080 1.046 2010-11 1.004 1.271 1.137 2009-10 1.084 0.955 1.020 2008-09 0.860 0.914 0.887 2007-08 1.041 0.991 1.016

Suter had a poor 2008-09 season but otherwise has been very good as well with ratings quite close to Lidstrom’s but probably a small step back.  Of the 68 defensemen discussed above, Suter ranks 30th in HART+ over the past 4 seasons but that was dragged down by his poor 2008-09.  Over the past 3 seasons he ranks 20th (to Lidstrom’s 16th) in HART+ among defensemen with 3000 minutes of zone start adjusted 5v5 ice time with Lidstrom being the better offensive defenseman and Suter being the better defensive defenseman.  All said, Suter would be a quality replacement for Lidstrom but I would expect the Red Wings offense to take a bit of a hit with Lidstrom not being in the line up.