HABS: Impact of Save Percentage on Wins and Losses

Save-percentage the difference in most games

The new Montreal Canadiens management group have been unwavering in their support of Carey Price. Marc Bergevin has repeated numerous times his view that strong goaltending is key to a successful team. He's also mentioned how difficult top-tier goaltending is to acquire, and how important Price is to the organization in both the short, and long-term.

How important?

The fluctuation in the Montreal Canadiens save-percentage from games the team won to games they lost was incredible.

SAVE PERCENTAGE

The Habs averaged a save percentage of only .892 in games they lost. That same save-percentage improved to an incredible .947 in games the team won. Time spent short-handed likely had an impact on the save-percentage as well, as Montreal averaged 4.04 powerplays against during losses, and 3.52 during wins; save-percentages drop substantially when teams are short-handed.

	LOSS AVG.	WIN AVG.
SAVE PERCENTAGE	0.892	0.947	SAVE PERCENTAGE

 SHOTS FOR / AGAINST

Not surprisingly, Montreal averaged more shots for, and less shots against during games they won. They averaged 0.26 more shots per-game in wins. But, it was shots against that fluctuated the most between wins and losses, as the Habs gave up 1.74 more shots per-game during losses.

	LOSS AVG.	WIN AVG.
SHOTS FOR	27.80	28.06	SHOTS FOR
SHOTS AGAINST	30.90	29.16	SHOTS AGAINST

GOALS FOR / AGAINST

Not surprisingly, the Habs allowed substantially more goals against in losses, and scored significantly more goals during wins. That said, it is the fluctuation that is surprising. Montreal averaged 3.81 goals per-game when they won, and only 1.71 goals per-game in losses. They gave up only 1.58 goals per-game during wins, but averaged 3.25 goals against in losses.

	LOSS AVG.	WIN AVG.
GOALS FOR	1.71	3.81	GOALS FOR
GOALS AGAINST	3.25	1.58	GOALS AGAINST

GAME BY GAME SAVE PERCENTAGE

How much pressure was on the Canadiens goaltending?

Montreal won only 4 games all season when their goaltender's save-percentage fell below .900. In fact, it wasn't until the 40th game of the season that the team first managed this feat. Montreal goaltenders lost nineteen times despite producing save-percentages above .910.

*the graph indicates the save-percentage earned in each Montreal Canadiens game during the 2011-12 season. Lines in green indicate wins, while lines in red indicate losses.

HABS: Quantifying the Impact of Special Teams on Wins/losses

 Getting more shots through to the net is a key powerplay stat

The Montreal Canadiens finished the 2011-12 season with the 18th-best goals for/against ratio at even-strength. In fact, they were a "plus" even-strength team through much of the first-half.

The team absolutely struggled on the powerplay; ending the year with the 28th ranked powerplay, after treading water at 29th and 30th much of the season. Thankfully, the penalty-killing held the fort; finishing second in the league with a success-rate of 88.6%.

Communicating the results is easy. The challenge becomes figuring out what produced those results, and what impact those events had on the win/loss column


POWERPLAY / SHORT-HANDED RISK/REWARD RATING

The Habs produced a substantially better powerplay risk/reward rating during wins. Their powerplay risk/reward rating was 2.09 during losses, and 2.29 during wins. This 0.20 translates to 2 more successful passes, dekes, shots-through, etc. per 2 minute powerplay.

Their short-handed risk/reward rating was also better during wins than it was during losses; jumping from 0.87 to 0.95. The 0.08 translates to just-under 1 more successful blocked shot, intercepted-pass, successful dump-out, etc. per 2 minute powerplay against.

	LOSS AVG.	WIN AVG.
PP RATING	2.09	2.29	PP RATING
SH RATING	0.87	0.95	SH RATING
	LOSS AVG.	WIN AVG.

POWERPLAY GOALS / CHANCES

The powerplay's impact on wins and losses was substantial. The Canadiens averaged just 0.31 powerplay goals per-game during losses, but managed an impressive 0.84 powerplay goals per-game during wins.

Equally interesting is the fact that the Habs actually had more powerplay chances during losses. Montreal averaged 3.75 powerplays per-game during losses, and 3.42 powerplays per-game during wins.

	LOSS AVG.	WIN AVG.
POWERPLAY GOALS FOR	0.31	0.84	POWERPLAY GOALS FOR
POWERPLAY CHANCES FOR	3.75	3.42	POWERPLAY CHANCES FOR
	LOSS AVG.	WIN AVG.

POWERPLAY PASSING/ SHOOTING

Breaking these numbers down into the most important events, we find that getting shots through to the net is essential for a successful powerplay, and by extension was the one powerplay event that had the largest impact on winning or losing.

Montreal players were able to get 55.53% of their powerplay shots through to the net during games they won, but only 45.03 % of their shots through during losses. This translates to one extra shot-on-net for every 10 attempted shots. Which potentially means one extra rebound, and one extra scoring-chance.

Passing also has an impact on powerplay success. During losses, Habs players' were successful with 78.76 % of their offensive-zone passes while on the powerplay, and 82.61 % of their o-zone PP pass-attempts during wins. This translates to one extra completed pass for every 20 attempted passes.

	LOSS AVG.	WIN AVG.
O-ZONE POWERPLAY PASSING SUCCESS-RATE	78.76	82.61	O-ZONE POWERPLAY PASSING SUCCESS-RATE
PP SHOTS THROUGH SUCCESS-RATE	45.03	55.53	PP SHOTS THROUGH SUCCESS-RATE
	LOSS AVG.	WIN AVG.

PENALTY-KILLING

POWERPLAY GOALS AGAINST/CHANCES

The Habs successful penalty-killing paid huge dividends in terms of wins. The Habs allowed 0.63 powerplay goals against per-game during games they lost, but cut that down to only 0.16 PP goals-against per-game during wins. 

Team discipline also had a big impact on the win/loss column. Not surprising, Montreal was short-handed more often in games they lost, than in games they won. Allowing 4.04 powerplay chances against during losses, and 3.52 PP chances against during wins. 

	LOSS AVG.	WIN AVG.
POWERPLAY GOALS AGAINST	0.63	0.16	POWERPLAY GOALS AGAINST
POWERPLAY CHANCED AGAINST	4.04	3.52	POWERPLAY CHANCED AGAINST
	LOSS AVG.	WIN AVG.

SHORT-HANDED DEFENSIVE-PLAY

Breaking the numbers down into some of the more important short-handed events, we find that successfully dumping the puck out of the defensive-zone, and blocking passing-lanes had a direct impact on wins and losses.

Montreal players were successful with only 50.8% of their attempts to block opposition powerplay passes during losses, but improved their success-rate to 54.01 during wins.

Taking advantage of opportunities to dump the puck out of the d-zone while short-handed also played a big role in successfully killing penalties. Canadiens players were successful with 65.6% of their attempts to dump the puck out during losses, and 69.64 % of their short-handed attempts to clear the d-zone during wins.

The higher number of blocked shots during losses are simply the result of more time spent short-handed during these same losses.

	LOSS AVG.	WIN AVG.
SHORT-HANDED SHOTS BLOCKED	3.39	3.06	SHORT-HANDED SHOTS BLOCKED
SHORT-HANDED PASSES BLOCKED/INTERCEPTED	50.88	54.01	SHORT-HANDED PASSES BLOCKED/INTERCEPTED
SHORT-HANDED DUMP-OUT SUCCESS-RATE	65.62	69.64	SHORT-HANDED DUMP-OUT SUCCESS-RATE
	LOSS AVG.	WIN AVG.

How important is getting powerplay shots through to the net?

Erik Cole led all Canadiens players with an impressive 11 powerplay goals. Cole also led all Habs with a 70% success-rate when attempting to get PP shots through to the net. Tomas Plekanec and PK Subban had the second-most powerplay goals with 5, but were successful getting only 45% and 46% of their attempted powerplay shot through, respectively.

HABS: Impact of Quality of Competition on Even-strength Risk/reward Ratings

No one system gives us the all-encompassing information on a player's value; at least not yet. In a constant effort to improve my player rating system, I've looked into more traditional advanced-stats metrics in order to see if there was anything that could by applied to my system.

Fenwick and Corsi numbers take a global picture of what occurs when a player is on the ice (shots attempted for and against), and uses those numbers to rate individual players. My system tries to take the individual player's puck-possession successes and failures (passes, dekes, puck-battles, etc) to get to the same point.

This is a first attempt at seeing what impact Corsi Relative Quality of Competition numbers would have on player's even-strength risk/reward ratings.

 Habs Eye on the Prize's Andrew Berkshire explains Corsi as follows:

Corsi - is a +/- statistic for a player/team that measures all shot attempts, including misses and blocked shots, directed for and against the team/player being measured per 60 minutes.

Andrew explains Corsi Relative Quality of Competition as follows:
 
Relative Corsi quality of competition - a measure of the average relative Corsi score of the opponents a player faces, weighted against the ice time played against each player


Silversevens.com explains the calculation for Corsi Relative Quality of Competition as follows:

Corsi Rel QoC is the weighted Relative Corsi Number of a player's opponents.

For example, if a player plays 30% of the time against five players with a relative corsi of +1.5, 35% of the time against five players with a relative corsi number of +0.2, and 35% of the time against five players with a relative corsi number of -2.1 then:

Corsi Rel QoC = (0.3 * 5 * 1.5) + (0.35 * 5 * 0.2) + (0.35 * (5 * (-2.1)) = -1.075

The top graph is a visual representation of each Montreal Canadiens even-strength risk/reward rating as calculated using my system, while the graph below that is a visual representation of each player's ES risk/reward rating after including Corsi relative quality of competition into the calculation.

In order for the calculation to work, and for the numbers to make sense, I've divided each Canadiens player's Corsi Rel QoC number by 5. Not only does this help minimize the impact on the original number it also relates better to the reality of my system. Corsi uses team numbers while a player is on the ice. Because of this it multiplies the value by 5 to represent the five skaters on the ice. My system tracks individual events taking place against individual players. As such, it does not need to by multiplied by 5.

The quality of competition numbers used in this calculation can be found here.

DEFENSEMEN

Quality of competition had a big impact on 5 Montreal Canadiens defensemen. Two of those players saw their even-strength risk/reward rating improve substantially, while 3 others saw it drop.

Josh Gorges and PK Subban faced the highest quality of competition. As such, Subban saw his risk/reward rating go from to to 1.78 to 1.92. Josh Gorges also saw his ES rating improve substantially; going from 1.39 to 1.67.

Tomas Kaberle, Frederic St. Denis, and Yannick Weber were all hurt by the inclusion of quality of competition into their risk/reward ratings. Kaberle's rating went from 1.57 to 1.46. This dropped him from third among Habs defensemen to fourth. St. Denis rating went from 1.37 to 1.21, while Weber's dropped from 1.13 to 0.98.

FORWARDS

Quality of competition had a substantial impact on 8 Montreal Canadiens forwards. Six of those players saw their even-strength risk/reward ratings improve substantially, while 2 others saw them drop.

Tomas Plekanec's rating went from an already impressive 1.24 to 1.42. Brian Gionta's rating went from 1.11 to 1.26. Rene Bourque's rating went from 0.67 to 0.80. Travis Moen's number went from 0.88 to 1.02. Ryan White's rating improved from 0.97 to an impressive 1.24, and Lars Eller's rating jumped from a 1.46 to 1.57. Eller had the top rating among forwards prior to the inclusion of quality of competition numbers, as well as after their inclusion.

Petteri Nokelainen and Brad Staubitz both saw their risk/reward ratings drop the most. The inclusion of Quality of competition saw Nokelainen's rating go from 0.90 to 0.69, while Staubitz's rating dropped from 0.50 to 0.34.

Keep in mind this is only an experiment. I will continue to research other forms of advanced stats in the attempt to find the most realistic and representative results possible.

HABS: One-game Scouting Report for Steve Quailer

Steve Quailer was drafted by the Montreal Canadiens in the third round of the 2008 NHL Entry Draft. He's a 6'4", 200 lbs left-handed winger. Quailer was recently signed to his first pro contract, and will likely start the upcoming season as a member of the Hamilton Bulldogs.

Quailer scored 8 goals and added 17 assists though 26 games with Northeastern University last season. This one-game scouting report is from Quailer's final NCAA game on March 3rd, 2012; a 5-3 win over Boston University. He played both wings during the game, and was a big part of both the PK and PP units.


OVERALL GRADE

Quailer produced a well above-average overall grade of 74. He had 2 assists, a plus-2 traditional plus/minus, and 2 shots on goal. His numbers were helped by his work in the offensive-zone, as well as some strong penalty-killing.

*the average grade among forwards is 65

	10
WINS	51	WINS
EVENTS	69	EVENTS
GRADE	74	GRADE
PLAYER	10

EVEN-STRENGTH RISK/REWARD RATING AND RATIO

Quiler earned an even-strength risk/reward rating of 0.80, and an ES ratio of 1.80 successful plays for every 1 unsuccessful play. Sixty-two percent of his even-strength events took place in the offensive-zone, and he engaged in 2.81 ES events per-minute played. 

*the average ES risk/reward among forwards is 1.10
*the average ES ratio among forwards is 1.87     

	10
POS	27	POS
NEG	15	NEG
RATIO	1.80	RATIO
	10
POS/MIN	1.81	POS/MIN
NEG/MIN	1.00	NEG/MIN
	10
EVENTS/ MIN	2.81	EVENTS/ MIN
RISK/REWARD	0.80	RISK/REWARD
	10

OFFENSIVE-ZONE RISK/REWARD RATING AND RATIO

Quailer had an offensive-zone risk/reward rating of 0.67, and an o-zone ratio of 2.25 successful plays for every 1 unsuccessful play. He won 3 of 4 o-zone puck-battles, recovered 4 loose-pucks, and completed an impressive 6 of 7 pass-attempts. He was also successful with 3 of 5 attempts to beat opposing players 1on1 (deke), and engaged in 1.74 offensive-zone events per-minute played. 

*the average offensive-zone risk/reward among forwards is 0.39
*the average offensive-zone ratio among forwards is 1.62  

	10
OZ POS	18	OZ POS
OZ NEG	8	OZ NEG
RATIO	2.25	RATIO
	10
POS/MIN	1.20	POS/MIN
NEG/MIN	0.54	NEG/MIN
	10
EVENTS/ MIN	1.74	EVENTS/ MIN
RISK/REWARD	0.67	RISK/REWARD
	10

DEFENSIVE-ZONE RISK/REWARD RATING AND RATIO

Quailer produced a defensive-zone risk/reward rating of 0.07, and a d-zone ratio of 1.25 successful plays for every 1 unsuccessful play. He lost his only d-zone puck-battle, and recovered 2 loose-pucks. He blocked 1 shot, intercepted 1 pass, and engaged in 0.60 defensive-zone events per-minute played.

*the average defensive-zone risk/reward among forwards is 0.38
*the average defensive-zone ratio among forwards is 1.95    

	10
DZ POS	5	DZ POS
DZ NEG	4	DZ NEG
RATIO	1.25	RATIO
	10
POS/MIN	0.33	POS/MIN
NEG/MIN	0.27	NEG/MIN
	10
EVENTS/ MIN	0.60	EVENTS/ MIN
RISK/REWARD	0.07	RISK/REWARD
	10

NEUTRAL-ZONE RISK/REWARD RATING AND RATIO

Quailer had a neutral-zone risk/reward rating of 0.07, and a neutral-zone ratio of 1.33 successful plays for every 1 unsuccessful play.  He lost his only puck-battle, and recovered 2 loose-pucks. He failed with his only attempt to dump the puck deep into the offensive-zone, and engaged in 0.47 neutral-zone events per-minute played.

*the average neutral-zone risk/reward among forwards is 0.30
*the average neutral-zone ratio among forwards is 2.14     

	10
NZ POS	4	NZ POS
NZ NEG	3	NZ NEG
RATIO	1.33	RATIO
	10
POS/MIN	0.27	POS/MIN
NEG/MIN	0.20	NEG/MIN
	10
EV/ MIN	0.47	EV/ MIN
RISK/REWARD	0.07	RISK/REWARD
	10

POWERPLAY RISK/REWARD RATING AND RATIO

Quailer had a low powerplay risk/reward rating of 0.86, and a PP ratio of 1.43 successful plays for every 1 unsuccessful play. He won his only puck-battle, and recovered 2 loose-pucks. He was successful with only 4 of 7 pass-attempts, and engaged in 4.86 powerplay events per-minute of powerplay ice-time. 

	10
POS	10	POS
NEG	7	NEG
RATIO	1.43	RATIO
	10
POS/MIN	2.86	POS/MIN
NEG/MIN	2.00	NEG/MIN
	10
EVENTS/ MIN	4.86	EVENTS/ MIN
RISK/REWARD	0.86	RISK/REWARD
	10

SHORT-HANDED RISK/REWARD RATING AND RATIO

 Quailer had a solid short-handed risk/reward rating of 1.43, and an impressive SH ratio of 3.5 successful plays for every 1 unsuccessful play. He lost his only PK puck-battle, and recovered 2 loose-pucks. He blocked 1 shot, intercepted 1 pass, and engaged in 2.57 short-handed events per-minute of short-handed ice-time.

	10
POS	7	POS
NEG	2	NEG
RATIO	3.5	GAMES
	10
POS/MIN	2.00	POS/MIN
NEG/MIN	0.57	NEG/MIN
	10
EVENTS/ MIN	2.57	EVENTS/ MIN
RISK/REWARD	1.43	RISK/REWARD
	10