NHL Possession Efficiency Ratings

NHL statistics, ratings, possession analysis

WSH@PIT Game 6: Microstats

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Pittsburgh at Washington Game 6:  2017 NHL Playoffs
Individual Possession Analysis
Washington 5, Pittsburgh 2

The data presented below is the results of my Individual Possession Efficiency tracking.  Evaluating players on a per possession level at even strength (5v5).  I document how each individual possession ends for every player.  All corsi data was retrieved from Corsica.Hockey.

The chart below shows Turnovers Per Possession, by zone.  Bryan Rust led the team in corsi% at 5v5 with a 61.5% corsi%.  Rust’s overall turnover%(turnovers per possession) was 35%, which is higher than the team average of 30.6% for game 6.  These are very high turnover rates for the Penguins.  Based on my tracking in the past their average turnover% was ~23%.  So Washington is forcing ~8 more turnovers per 100 individual possessions over Pittsburgh’s normal average.

The Malkin line of Rust-Malkin-Guentzel led the team in neutral zone steals at 6.  The other 3 lines had 3 neutral zone steals combined.  The Malkin line was able to makeup for their offensive zone inefficiencies by regaining possession in the neutral zone.

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Kunitz and Kuhnhackl had two of the 3 highest overall turnover rates at 40% and 73% respectively.  Kuhnhackl had the highest offensive zone turnover rate at 36%, and the highest neutral zone turnover rate at 18%.

Although Sheary played on Pittsburgh’s top line with Crosby and Hornqvist, his Dump in turnover rate of 19% is far too high.  That’s 5 failed dump in for Sheary on 26 possessions.  That should never happen when playing on a line with Crosby.

The chart below shows shot attempts per individual possession and shot attempt assist per individual possession at 5v5.  Average shot attempts per possession for game 6 were .078 (7.8 shot attempts per every 100 individual possessions).  Average shot attempt assist per individual possession in game 6 were .049 (4.9 shot attempt assist per every 100 individual possessions).

Rust led the team in shot attempt assist% at 12%, where Guentzel was 2nd on the team in shot attempts per possession at 14%.

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The rebound analysis below shows that the Penguins had issues with defensive zone rebounding.  The team average for game 6 was 4.3%, where past tracking shows the average individual defensive zone rebound rate for Pittsburgh to be ~8.3%.  Pittsburgh giving up almost double the defensive rebounds per Washington shot attempt.

What stands out is the Crosby-Sheary-Hornqvist line did not grab one offensive rebound at 5v5 during the game.  This is usually a strong point for Crosby’s line, as offensive rebounding helps to maintain offensive zone pressure.

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Lots of red in the defensive zone passes completed per possession.  As Washington had Pittsburgh hemmed in their own zone quite often.  In Game 1 Pittsburgh’s average defensive zone passes completed per possession was .19 (19%), in Game 6 it was .18 (18%).

Based off of last year’s playoff run for Pittsburgh, their average defensive zone passes completed per possession average was ~13.4%.  The neutral zone steals from the Malkin line helped reduce their defensive zone passes completed %’s relative to the rest of the team.

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Written by RReed

May 10, 2017 at 8:17 AM

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PIT@WSH Game 1: Microstats

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Pittsburgh at Washington Game 1:  2017 NHL Playoffs
Individual Possession Analysis
Pittsburgh 3, Washington 2

The data presented below is the results of my Individual Possession Efficiency tracking.  Evaluating players on a per possession level at even strength (5v5).  I document how each individual possession ends for every player.  All corsi data was retrieved from Corsica.Hockey.

The chart below shows Turnovers Per Possession, by zone.  Hornqvist led the Penguins in 5v5 corsi% at 48%.  He also had the lowest turnovers per possession at .11 (4 turnovers on 35 possessions= .114).  Average turnover rate for the Penguins in game 1 was 23%.  Conor Sheary had the lowest corsi% at 5v5 at 4.3%.  Sheary posted the highest turnover rate at .67 turnovers per possession.  Overall Sheary had 9 possessions at 5v5, 4 resulted in a turnover in the offensive zone (4/9 = .44), and 2 resulted in a turnover in the neutral zone (2/9 = .22).

Turnover Rates Per line at 5v5:
Guentzel-Crosby-Hornqvist:  17.8%
Rust-Malkin-Kessel:  33.8%
Wilson-Bonino-Sheary:  29.2%
Kunitz-Cullen-Kuhnhackl:  31.5%

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Clearance Rates Per Line at 5v5:
Guentzel-Crosby-Hornqvist:  11.1%
Rust-Malkin-Kessel:  6.8%
Wilson-Bonino-Sheary:  16.7%
Kunitz-Cullen-Kuhnhackl:  13%

Now I track clearances separately as they do not count towards turnovers.  Simply because I want to differentiate player intent.  Clearances are part of the possession totals for each player, but not included in the turnover total.  Looking at clearances, gives you a good idea as to which players were under duress at times.

Turnover rates per defensive pair:
Schultz-Cole:  13.2%
Dumoulin-Hainsey:  16.9%
Maatta-Daley:  20%

Defensive Zone turnover rates per defensive pair:
Schultz-Cole:  7.5%
Dumoulin-Hainsey:  9.2%
Maatta-Daley:  3.6%

The chart below presents shot attempts and shot attempt assists per possession.  League average per my tracking thus far for shot attempts per possession is .11 (1.1 shot attempts per every 10 individual possessions).  League average Shot Attempt Assists Per possession are .066 (1 Shot attempts assist per every 15 individual possessions).

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The chart below shows passes completed per possession by the zone they were completed in.  For example, Hornqvist completed 8 passes in the offensive zone (8/35 = .23 Offensive Zone Passes Completed Per Possession).  Judging by the high defensive zone passes completed per possession for Pittsburgh’s defensemen, you can see how the ice was tilted quite a bit in Washington’s favor.

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The chart below shows offensive and defensive rebound% at 5v5.  Team average offensive rebound% in game 1 was 8.7%.  Average defensive rebound% was 5.2%.

For reference, in game 2 vs Columbus the average offensive rebound% was 10.3%. Average defensive rebound% was 6.5%.
In game 4 vs Columbus, average offensive rebound% was 7.8%. Average defensive rebound% was 8%.

Combined Offensive Rebound%’s per line:
Guentzel-Crosby-Hornqvist:  47.3%
Rust-Malkin-Kessel:  37.5%
Wilson-Bonino-Sheary:  0%
Kunitz-Cullen-Kuhnhackl:  16.7%

Combined Defensive Rebound%’s per line:
Guentzel-Crosby-Hornqvist:  0%
Rust-Malkin-Kessel:  16.1%
Wilson-Bonino-Sheary:  11.1%
Kunitz-Cullen-Kuhnhackl:  24.3%

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Written by RReed

April 29, 2017 at 1:20 PM

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PIT@CBJ Game 4: Microstats

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Pittsburgh @ Columbus: Game 4  2017 NHL Playoffs
Individual Possession Analysis
Columbus 5, Pittsburgh 4

The data below are the results of my individual possession efficiency tracking, where players are evaluated on a per possession level.  I track each individual turnover per possession by the zone it occurred in.  The efficiency rates are then compared to their Corsi%, which I retrieved from Corsica.Hockey.

The chart below shows Matt Cullen as having the lowest turnover rate per possession across the board.  Cullen’s overall turnover rate was .11 (1.1 turnovers per every 10 individual possessions).  League average per my tracking to date is ~.25 turnovers per possession.

Dump ins as a means of entering the zone did not appear to work out well for Hornqvist and Bonino.  In game 4, Pittsburgh’s average dump in turnover rate was .05 (1 dump in turnover per every 20 individual possessions).  Hornqvist and Bonino’s rate were ~3 times higher than the team average.  The dump in success rate for Pittsburgh in game 4 was 16% (4 dump ins recovered on 25 attempts).

Now I track clears and dump ins separately, so that if a player dumps it in then goes for a change, I document that as a clearance because there was no intent.

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Crosby and Guentzel had low turnover rates as compared to the rest of the team, at .17 and .21 respectively.  Guentzel also had the 3rd highest passing accuray% at 85.7%.  Sheary’s turnover rate was .42 (4.2 turnovers per 10 possessions).  Now this is extremely high, but Sheary makes up for it with well above average Offensive and Defensive Rebound%’s.

The team average in Game 4 for offensive rebound% was 7.8%.  The team average for defensive rebound% was 8%.  Sheary and Guentzel both well above the team average in rebounding, were able to sustain longer possession spells in Columbus’ zone.

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The chart below shows each players’ shot attempts (SOG, Miss, Blocked) per each individual possession, as well as their passes to setup players for a shot attempt (Shot attempt assist).  The league average per my tracking thus far for shot attempts per possession is .11, and .066 for shot attempt assist per possession.

Crosby had a shot attempt assist on 22% of his individual possessions, which is ~3 times higher than the league average.  Guentzel’s shot attempts per possession(.21) were ~2 times the league average.

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The chart below shows each players passes completed per possession by zone.  The Crosby-Sheary-Guentzel line had some success in the offensive zone.  Crosby completed an Offensive zone pass on almost 40% of his individual possessions.  The team average for this game was .17 (1.7 out of every 10 individual possessions).

The increase in offensive zone time relative to their teammates, as well as above average offensive rebounding, contributed to the Sid and the Kid’s success in this game.   Schultz’s high defensive zone passes per possession jump out as very high, but this is more due to him being patient in his own zone.  If the pass through the neutral zone isn’t there, Schultz will look to pass to his defense partner.  This delays the breakout to wait for another passing option out of the zone to potentially open up.

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Written by RReed

April 20, 2017 at 8:14 AM

Posted in Uncategorized

CBJ@PIT Game 2: Microstats

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Columbus @ Pittsburgh: Game 2  2017 NHL Playoffs
Individual Possession Analysis
Pittsburgh 4, Columbus 1

Below, are the results of my individual possession efficiency tracking, where I document what each player does per each time they have an opportunity to make a controlled play (Possession) at even strength (5v5).  All Corsi%’s were retrieved from corsica.hockey.

The chart below presents each players’ Turnovers Per Individual Possession at 5v5, broken down by the zone they occurred in.  For example, Phil Kessel had 18 individual possessions at 5v5 in game 2, and committed .39 Turnovers Per Possession.  Phil had 18 Individual Possessions at 5v5 and committed 7 turnovers. (7/18 =.39 Turnovers Per Possession)

The average turnover rate for the team was .23 turnovers per possession.  Based on my tracking to date, the league average individual turnover rate is ~.25 (2.5 turnovers per every 10 individual possessions)  Matt Cullen had the highest overall individual turnover rate at .50, so half of Cullen’s individual possessions resulted in a turnover.  Hornqvist at .42, and Hainsey at .35 turnovers per possession.

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The passing analysis below shows each players’ passes completed per possession at 5v5, and the zone which it occurred in.  Schultz is really good.  While considering his high individual possession count (29), Schultz was very much involved.  Schultz completed 17 of 18 passing attempts for a Passing Accuracy% of 94.4%.  Kessel and Hainsey posted the two lowest passing accuracy%’s of 30% and 50% respectfully.  More reasons as to why Kessel should shoot even more.

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The data below shows each players’ shot attempts (SOG, Miss, Attempt Blocked) per individual possession.  Shot attempt assist document each players pass completed in the offensive or neutral zone, where the receiving player attempts a SOG, Miss, or attempt blocked.

Per my tracking to date, the league average for Shot Attempts Per Possession is .11, where the league average for Shot Attempt Assist Per Possession is .066.  So ~11 out of every 100 individual possessions result in a shot attempt, and ~6.6 out of every 100 individual possessions result in an assist on a shot attempt. For example, Kessel had 18 possessions at 5v5, where 4 of them resulted in a shot attempt (.22).  Kessel’s 30% passing accuracy contributed to his 0.0 shot attempt assist per possession.

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The ability to obtain rebounds can be very important to maintaining pressure in the offensive zone, as well as relieving pressure in the defensive zone.  This can also highlight a player’s quickness, and their ability to anticipate the play.  The visual below shows each player’s Offensive and Defensive rebound%’s at 5v5.  Per my tracking to date, league average offensive rebound% is ~8.2%, where the defensive rebound% is ~8.8%.

Conor Sheary posted the highest offensive rebound% at 33.3%, meaning he literally grabbed 1/3 of the offensive rebounds available at 5v5 (4 rebounds/12 available = 33.3%).  This is a crucial aspect to sustaining long possession spells in the offensive zone.  Hainsey   and Dumoulin did not fair so well in the rebounding department.  Of the 22 defensive rebounds available at 5v5, they were not able to get one rebound between them.  This highlights a reason as to why Columbus was able to sustain an offensive zone pressure with the two of them on the ice.  This is also reflected in Hainsey’s 30.2% corsi% and Dumoulin’s 28.2% corsi%.  More rebounds for Columbus, mean more opportunities for shot attempts against.

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Written by RReed

April 16, 2017 at 10:07 AM

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2017 NHL Playoffs log5 Analysis

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2017 NHL Playoffs log5 Analysis
The log5 analysis was developed by Bill James. This method of evaluation is used to determine the predicted winning probability of one team over another. The input for the formula is derived from the final 2016-17 NHL regular season Possession Efficiency Ratings.

As you can see below, the log5 analysis measures the difficulty of each team’s path, taking into consideration potential match ups that could occur. For example, the result of the log5 analysis below is showing that Washington has a 62.4% chance of defeating Toronto in the first round and advancing to the 2nd Round.

Washington then would have a 33.2% chance of defeating Toronto in the first round and then defeating the winner of the Pittsburgh-Columbus series to advance to the Conference Finals.

From there, depending on who Washington would meet in the Conference Finals, they would have a 19.2% chance of winning the first 3 rounds and advancing to the Stanley Cup Finals.  Washington would then have an 11.3% chance to win the first 3 rounds and the Cup final.

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Written by RReed

April 10, 2017 at 9:41 PM

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PIT@SJ Game 6: Microstats

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2016 Cup Final
Pittsburgh 3, San Jose 1

The data below is the results of my tracking.  I am tracking players from an individual possession standpoint.  Essentially documenting what each player does each time they have the puck at even strength (5v5).  The data is then used to help explain Corsi%.  All Corsi% data is obtained from corsica.hockey.

Sheary had the highest Corsi% on the team at 68.4%, posting a Turnover% of 19.4%, which is below the team average of 23.3%.  Turnover% is the percentage of individual possessions which result in a turnover.  Sheary had 6 turnovers on 31 possessions (6/31 = 19.4%).  The team average in Passing Accuracy% was 77.3%, Sheary was above average at 90%, completing 18 of the 20 passes he attempted.

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The average Turnover% for players with a Corsi% of 50% and above was 20.3%.  The Turnover% for players with a Corsi% below 50% was 35%.

Schultz with a 34.8% Corsi%, was is the lowest of the series for him.  This Corsi% was a result of Schultz posting the highest Defensive Zone Turnover rate of 25%, posting 3 defensive zone turnovers on 12 possessions.  25% was the highest on the team by far, with the team average Defensive Zone Turnover rate of 4.4%.

The chart below show each player’s individual Offensive and Defensive Rebound rates.  Sheary posted the 2nd highest Offensive Rebound% at 17.4%.  Hagelin did post the highest Offensive Rebound% at 36.4%, but his 42.3% Turnover% (2nd highest on the team) was able to wash out his well above average offensive rebounding.  Hagelin’s 11 turnovers on 26 possessions (11/26= 42.3%), was almost twice the team average Turnover% of 23.3%.

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Hagelin had the 3rd highest dump in rate on the team at 11.5%, meaning of his 26 possessions, Hagelin dumped the puck in 3 times. (3/26=11.5%).  All 3 of Hagelin’s dump ins resulted in a turnover.  Pittsburgh’s team average dump in success rate was 13.6%, meaning 86.4% of the time Pittsburgh dumped the puck in, it resulted in a turnover.

The data below breaks down each player’s Passes by zone.  Crosby completed 18 Passes, 12 in the Offensive Zone, 0 in the Neutral Zone, and 6 in the Defensive Zone.  His Passing Accuracy% was slightly below team average at 72% (team average was 77.3%).  Crosby had 6 failed attempts in the offensive zone, and 1 failed attempt in the neutral zone.  Crosby completed the 2nd most passes in the offensive zone, only Sheary completed more (13).

Kessel had the lowest Passing Accuracy% at 33.3%, while completing 4 passes on 12 attempts.  Kessel’s Passing Accuracy% in the Offensive Zone alone was 14.3%, completing 1 offensive zone pass on 7 attempts.  As you can see below, completing passes in the offensive zone increases your offensive zone time, thus the opportunities for shot attempts and increased Corsi%.

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The spider chart below shows the distribution of Crosby’s 18 completed passes in Game 6. Crosby completed 18 passes, 6 were to Sheary, 3 to Letang, 3 to Dumoulin, 2 to Hornqvist, and 1 each to Kessel, Cullen, Schultz, and Lovejoy.  Sheary was the recipient of 33% of Crosby’s completed passes at even strength(5v5).

crosby gm6 passes

 

Written by RReed

June 15, 2016 at 8:02 AM

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SJ@PIT Game 5: Microstats

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2016 Cup Final
San Jose 4, Pittsburgh 2

The data displayed below is the results of tracking for Game 5.  I document what each player does per each individual possession at even strength(5v5).  The data is then interpreted to help help explain Corsi%.  All Corsi% data was obtained from corsica.hockey.

This was a pretty impressive performance by Pittsburgh, dominating the play despite losing 4-2.  Average Corsi% for all Pittsburgh players was 69.5%.  Maatta led the way in Corsi% at 84.2%.  Maatta had the 4th most individual possessions on the team at 38.  Maatta’s Passing Accuracy% was above the team average of 79.2%, and had a below average Turnover% of 18.4%. (team average was 23.2%).  Despite getting shelled in past games Maatta only had 2 defensive rebounds available while he was on the ice, and was able to obtain 1 of them for a 50% Defensive Rebound%.

Cullen posted the lowest Corsi% at 22.2%, and was tied for the highest Turnover% (turnovers per individual possessions) at 40%.  Cullen only had 5 possession at 5v5 and had 2 turnovers.  Both of these turnover occurred in the defensive zone for a 40% defensive zone turnover rate.  The 4th line which is composed of Fehr, Kuhnhackl, and Cullen were able to grab only 1 defensive rebound for a 7.1% Defensive Rebound% average between them.  The Team average for Defensive Rebound% was 12.7%.

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Hagelin and Hornqvist were the most efficient at generating SOG per each individual possession at 30% and 25% respectively.  The team average in SOG per individual possession was 8.4%.  Malkin completed the most offensive zone passes (15), next closest was Crosby with 11.  Pittsburgh attempted 25 dump ins at 5v5, and were able to recover 2 of them for a 8% success rate.  When Pittsburgh dumped the puck in, it resulted in a turnover 92% of the time.

Below shows the Offensive and Defensive Rebound% breakdown for each player.  Overall the Offensive Rebound% average was 10%, and the Defensive Rebound% 12.7%.  Defensive Rebound% were high throughout the team, but a small sample size due to the lack of san jose possession in Pittsburgh’s defensive zone.

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The breakdown below shows each players Passing Accuracy% and passes completed to a specific zone.  Malkin completed 24 passes on 43 Possessions, 15 in the Offensive zone, 4 in the Neutral zone, and 5 in the Defensive zone.  Average Passing Accuracy overall was 79.2%.

In the Offensive zone only, the average Passing Accuracy% was 76.6%.  Malkin’s Passing Accuracy% in just the Offensive zone was 93.8% (15/16), which is incredibly impressive.  Overall Malkin’s Passing Accuracy% was 85.7%, where he completed 24 passes, but had 1 failed attempt in the offensive zone, 2 failed attempts in the neutral zone, and 1 failed attempt in the defensive zone.

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Written by RReed

June 12, 2016 at 7:06 PM

Posted in Uncategorized