Suter vs. Richard: offensive production
My first observation here: why is there a focus on 5v5 situations regarding deployment, faceoffs, ZSR and time on ice in MySports’ table, when the point per game indicated for both players includes every ingame situation (5v5, 4v4, 3v3, PP and BP)?
Suter has 20 points in 16 games. Yet, 9 of his points (1 goal and 8 assists) come from the powerplay. On the other hand, Richard has 13 points at 5v5, but only 3 assists come from the powerplay. As such, let’s compare both players’ production in 5v5 situations:
  5 goals and 6 assists in 16 games for Suter, or 0.69 5v5 point per game. 
 
3 goals and 10 assists in 27 games for Richard, or 0.48 5v5 point per game. 
There’s still a clear advantage for Suter in terms of offensive production. Yet, once adjusted for the 5v5 situation, the difference between the two players is not as important as showed in MySports table.
Die gestrige Folge von Advanced Stats verpasst?🙈 Hier nochmals der spannende Vergleich zwischen @pius_suter und @Trichard71 !😎 https://t.co/X58McWZDTJ
— MySportsCH (@MySports_CH) December 9, 2017
SIHF faceoffs data
At the game and player level, the League provides the following statistics regarding faceoffs:
 
“FOW Total” or FOWT for faceoffs won total 
 
“FOL Total” or FOLT for faceoffs lost total 
 
“FO%” which corresponds to the percentage of faceoffs won or (FOWT/(FOWT + FOLT)) 
At the individual player level, the League does not provide details about the offensive, defensive or neutral zones faceoffs. It only does at the team level, but only in terms of winning percentage:
(Source: sihf.ch)Yet, in the “Players stats” pages, it is possible to find more faceoff details on three different links:
1. 
Faceoffs summary gives a quick recap of faceoffs statistics by player; 
2. 
Faceoffs/zone details the number of faceoffs won or lost by zone and by player; 
3. 
Faceoffs/game details the same information as in the Faceoffs/zone page, but divides it by the number of games played by each player. 
Extracting this data after every game would allow us to obtain all the details at the game and player level by taking the difference in the statistics between two consecutive games. It is also possible to find faceoffs statistics at the team level: Faceoffs summary, Faceoffs/zone and Faceoffs/game.
Now, there are some limits to SIHF faceoff data. In fact, it doesn’t specify:
if the faceoffs were played at the start of a shift or if the player was already on the ice before the faceoff. Remember the ZSR definition from above: “begins when a player starts his shift in a zone (beginning with a faceoff)”.
1.  in which situation the faceoffs were played: 5v5, 4v4, 3v3, PP or BP; 
2. 
if the faceoffs were played at the start of a shift or if the player was already on the ice before the faceoff. Remember the ZSR definition from above: “begins when a player starts his shift in a zone (beginning with a faceoff)”. 
A priori, the interesting part of the above laid out faceoff data is that it can be considered as a proxy to obtain the ZSR. As stated before, faceoffs considered to compute the ZSR are a subset of the total number of faceoffs and the total is the only data the League provides. SIHF data includes midshift faceoffs as well as faceoffs in other ingame situations (4v4, 3v3, PP, BP). With reasonable assumptions, I will show that this available data can be used in Pius Suter’s case.
Finally, there’s one last SIHF page that will be useful for this analysis: time on ice which gives the number of shifts played for every player in the League. At the time of the analysis, Suter had played 474 shifts as compared to Richard’s 840.
Faceoffs – Suter’s case
According to the lineups provided on the SIHF website, Suter has been playing as a center all season long and has played most of his games with Pettersson and Nilsson (evenstrength and powerplay): he started all his games with Pettersson on his right wing and 13 games with Nilsson on his left wing (Suter played with Pestoni instead of Nilsson in the other games). For the powerplay, Suter mainly played with Nilsson, Pettersson, Chris Baltisberger and Geering or Klein on ZSC’s first unit. As such, and without any shift chart available on the SIHF website, I will assume that these players were Suter’s most common teammates on the ice. Furthermore, I will not consider defensemen for an obvious reason: they rarely take faceoffs.
Also, I did not mention boxplay situations as I first decided to focus on the offensive part of the ZSR metric with faceoffs played in the OZ, and those are rarely played in OZ during the boxplay.
Now, let’s have a look at the faceoffs statistics of Suter, Pettersson, Baltisberger, Pestoni and Nilsson per zone:
His most common teammates played a low number of faceoffs (11) in the OZ. Not knowing if Suter was on the ice at that moment, I make the assumption that when he started his shifts in the OZ, he was the player taking all his line’s faceoffs. Remember from the ZSR definition, the metric for one player considers his own faceoffs as well as his teammates’. Even if considered, due to their low magnitude, their 11 faceoffs wouldn’t alter our analysis.
Before commenting on Suter’s numbers, remember again that 5v5 Zone Starts must be seen as a subset of faceoffs. For example, the 60 faceoffs Suter took in the OZ can be considered as a maximum for Offensive Zone Starts (OZS) and the same can be said about the 135 faceoffs taken in the DZ.
Now, taking into account the assumptions I made on Suter and focusing on his numbers, here are some comments:
 
Suter took 31% (=FO OZ/(FO OZ+FO DZ)) of his faceoffs in the OZ (I am only considering OZ and DZ faceoffs, as in the ZSR) 
 
Using this 31% as a proxy for the ZSR does not seem to be appropriate, Suter’s ZSR being 67.57% according to MySports. By looking at this proxy and its value (31%), you would conclude that Suter is starting way more in the DZ than in the OZ, even if FO OZ and FO DZ need some adjustments to reach the ZSR. 
  The 60 faceoffs Suter took in the OZ can be considered as a maximum for OZS; 
 
The 135 faceoffs Suter took in the DZ can be considered as a maximum for DZS. 
Knowing the ZSR formula (OZS/(OZS + DZS)), Suter’s ZSR of 67.57% and the maximum of OZS of 60, it is possible to deduce the two single fractions that correspond to a ZSR of 67.57%:
  50/(50+24), with OZS = 50 and DZS = 24 (scenario 1); 
 
25/(25+12), with OZS = 25 and DZS = 12 (scenario 2). 
In the first scenario, it means that the adjustment for the 60 OZ faceoffs in the OZ is 10 (17%) and the adjustment for the 135 DZ faceoffs in the DZ is 111 (82%). In the second scenario, it means that the adjustment for the 60 OZ faceoffs in the OZ is 35 (58%) and adjustment for the 135 DZ faceoffs in the DZ is 123 (91%).
Getting back to Suter’s numbers:
 
He played a total of 474 shifts. He either started in the offensive zone 11% of the time (50/474; scenario 1) or 5% of the time (25/474; scenario 2) depending on the importance of the adjustments. 
Again, some observations:
  Does 11% or 5% of his total shifts starting in the offensive zone matter that much in terms of offensive production as compared to Richard’s? According to Micah Blake McCurdy, a forward starts on average 13% of his shifts in the OZ. What it means for Suter’s ZSR: it’s not the high numbers of faceoffs taken in the OZ that drives his ZSR, but his low number of faceoffs in the DZ. Here, it could have been interesting to see MySports include more context and details around the ZSR metric (team averages, teammate comparisons, other factors impacting offensive production, etc) to better understand it. 

  There is an important difference between:  
1.  the proxy of 31% and the ZSR of 67.57%;  
2. 
the adjustments needed for both OZS and DZS to obtain the ZSR of 67.57%: OZ faceoffs have to be adjusted by 17% (10 faceoffs) or 58% (35 faceoffs) and DZ faceoffs have to be adjusted by 82% (111 faceoffs) or 91% (123 faceoffs). 
As stated a few times before, OZS and DZS are a subset of faceoffs. As such, faceoffs need to be adjusted for midshift faceoffs or for other ingame situations (PP, BP, 4v4, 3v3):
If the DZ adjustments are caused by midshift faceoffs, it means that Suter either started his shifts on the fly or with a previous faceoff and that his line lost possession of the puck and needed to take a faceoff in front of their goalie.
Yet, Suter plays in one of the best possession teams and certainly one of the best lines in the League in terms of offensive talent and production. As such, it seems rather counterintuitive that his line lost so many times possession of the puck midshift.
If the adjustments are caused by other ingame situations (4v4, 3v3, PP, BP), it means that most of them were taken in the DZ. Yet, in the games Suter played, the ZSC Lions played 76% of the time at evenstrength, 12% on the powerplay and 12% on the boxplay. For Suter, he played 68% of the time at evenstrength, 18% on the powerplay and 13% on the boxplay.
Again, it seems rather counterintuitive that he got that much more faceoffs in the DZ as he got more powerplay time than boxplay time. His playing time induces more OZ faceoffs and starts, not more defensive ones.
1.  If the DZ adjustments are caused by midshift faceoffs, it means that Suter either started his shifts on the fly or with a previous faceoff and that his line lost possession of the puck and needed to take a faceoff in front of their goalie. Yet, Suter plays in one of the best possession teams and certainly one of the best lines in the League in terms of offensive talent and production. As such, it seems rather counterintuitive that his line lost so many times possession of the puck midshift. 
2. 
If the adjustments are caused by other ingame situations (4v4, 3v3, PP, BP), it means that most of them were taken in the DZ. Yet, in the games Suter played, the ZSC Lions played 76% of the time at evenstrength, 12% on the powerplay and 12% on the boxplay. For Suter, he played 68% of the time at evenstrength, 18% on the powerplay and 13% on the boxplay. 
Now, instead of focusing only on his most common teammates’ faceoff statistics, here is the data for the 10 ZSC players that took the most faceoffs:
The top7 players in the list are mostly used as centers (debatable for Shore). Among them, Suter is the center taking the fewest faceoffs in the OZ as compared to DZ. (On a different note, it seems strange to have FO DZ > FO OZ for one of the best possession team in the League).
All in all, something is missing here to justify the difference between the ZSR of 67.57% and the proxy with the available data. Furthermore, the needed adjustments in Pius Suter’s case seem too significant for the DZ faceoffs.
Faceoffs – Richard’s case
Now, I will not dig into Richard’s stats at the same level of details as for Suter. Here are his faceoffs statistics:
The same observation as for Suter: there is also an important gap between what could be used as a proxy for ZSR (63%) and his real ZSR of 41.54%, as given by MySports. Looking at this proxy, you would conclude that Richard is beginning more in the OZ than in the DZ.
In the third and last part tomorrow, I will draw conclusions from both the MySports and my own analysis and outline the issues with the restricted amount of statistics currently available to the general public. For a definition of the metric Zone Start Ratio, check out yesterday's Part I.