Archive for September, 2012

With no hockey to write about, I figured I’d share my other hobby: homebrewing!

I started homebrewing back in about March–right around the time I started this blog incidentally. I’ve done about five or six batches, some have turned out well, others…not so much. On the bright side, I do know how NOT to install an airlock >_>

Mostly I had done ales prior to this batch, and I just wanted to do something different. I wasn’t working with a particular recipe, I just went to the local shop and pulled together some ingredients that looked good for a pilsner.


4 lbs pilsner liquid malt extract

Steeping Grain

8 oz 15L roasted barley


2 oz Czech Saaz hops total
-0.5 for 60 mins
-0.5 for 10 mins
-0.5 for 5 mins
-0.5 at flameout

Other Ingredients

2 oz sweet orange peel (dried) for 5 mins
1 oz Coriander for 5 mins
1 Whirlfloc tablet for 5 mins


White Labs WLP800 Pilsner Lager Yeast
1.030 OG

I’ll update with some photos and certainly an update when it’s ready to drink! The last batch I did was an Irish Red ale, and I had some problems with carbonation that really have me scratching my head…one bottle fizzed over for literally 10 minutes, and was like club soda, the next was completely flat. Not sure what happened.
I don’t know if anyone else out there is a homebrewer but I’d love to hear if you are, and perhaps you can help me with my carbomation/conditioning mystery :D thanks for reading!

Starting with the Philadelphia Flyers and recently adding the Minnesota Wild, we have learned quite a bit about the nature of zone entries as they relate to offense generated in the NHL. We now know that for both top- and bottom-scoring teams, uncontrolled entries (dump-in and tip-in) generate on average 0.3 Fenwick shots per entry, while controlled entries (carry-in and pass-in) generate 0.6 shots per. We have also observed that there is almost no difference in the shots generated by third line grinders and top line snipers across the different entry types.

However, while cracking into this area of analysis has produced some very remarkable findings, there are many more questions to be answered about zone entries and how they translate to offense. Here are some specific questions for the Wild that I hope to answer as I continue to research this part of the game, and preliminary ideas of how to tackle them:

 Team Zone Entry Distribution Over Time

We know that the dump-and-chase game is less productive than the straightforward zone entry, and we have seen that the Flyers utilize the dump-in less than the Wild. But to what extent does a different coaching staff dictate the proportion of zone entries? With this past season being the first with Mike Yeo behind the bench, I would want to look at the 2010-11 season under Todd Richards to see if a mostly similar roster showed a similar controlled/uncontrolled ratio, and if the shot output was the same. For that matter, it would be interesting to see how closely Dany Heatley and Devin Setoguchi’s entry ratios compare from year-to-year, and whether and how they differed playing under different coaches.

 Team Zone Entry Variance Within Season

To this point, we have looked at season-aggregated data and average shots per entry. Research using Flyers data has revealed that some things will take more than a season’s worth of data. But I want to know what the amount of variance there is within-season for number of zone entries and controlled/uncontrolled entry ratio, potentially giving us a glimpse at the strategy and game planning.

 Zone Entry Ratio Between Opponents

With just one season of data, I am thinking about looking at just division opponents to see if there are patterns in how the Wild play teams like the Canucks or Flames, and if they differ significantly from the overall season data. I do worry about small sample size, with just three home and three road games per division opponent per year.

 Big Lead/Big Trail Statistics

One of the main dismissals of advanced stats in hockey goes something like, “Corsi is stupid because when teams are winning the game they sit back and let the other team take more shots.” Researchers have answered this by examining close game situations, big leads and big trails, and I want to dive into zone entries the same way. When the Wild get up by two goals, to what extent do they shift their strategy to a dump-and-chase? This will be great to look across teams, because it will give us a better idea of coaching philosophies of the teams.

 Within-Game Zone Entries

This is still a half-formed idea, but it seems to me from the eyeball test while watching the games that in the early minutes of a period or a game, both teams are much more likely to execute a dump-in. Score effects will likely trump time effects, but this may be something to look into.

Bottom Line: Not Enough Hours in the Day

Ultimately, the answers to these questions will come with more data: going forward we can continue to track games (if and when we ever get them back) and going back to previous seasons would give us a lot more context. We could see how teams change their strategy over time, and how players develop their skills as they progress through their careers. We could see if patterns emerge as to how teams play their division opponents, and if they are able to adapt their strategy (entry ratio) within a season. However, for now the only way this data can be collected is by a human being putting two eyeballs on a screen, and at 90-minutes a pop the data will be slow to come in. I am wondering how many games it would take from a previous season to get a representative sample. There is pretty much no way to get a computer to code zone entries, and going forward it could be done with a series of cameras in the arena, but that’s just not going to happen any time soon, though perhaps if they have success with it in the NBA it may transfer over. When I get my genius grant, maybe I’ll work on training rhesus monkeys to code zone entries, but for now, I’ll just have to keep using that elbow grease.

If you have additional ideas or research questions, please feel free to shoot them at me on Twitter, @Hashtag_Hockey or in the comments section below. Thanks for reading!


Abstract (tl;dr version)

The present research examines the first sixty games of the 2011-12 Minnesota Wild hockey season, and looks at zone entries (controlled vs. uncontrolled) in terms of shots generated. It was found that controlled entries like carrying or passing the puck into the offensive zone generate twice as many shots as uncontrolled entries such as a dump-in or tip-in. Controlled entries generate an average of 0.6 shots per entry, while uncontrolled entries generate an average of 0.3 shots. Individual Wild players are examined, and implications on coaching and strategy are discussed. If you are familiar with previous research on zone entries, click here to jump to the results.


I would like to thank Eric T and Geoff Detweiler from for getting me started on this project, sharing their spreadsheets, and patiently answering all manner of “What the heck am I doing?” e-mails. Thanks guys!


In the world of sports analytics, the game of hockey is a different beast than others like baseball or football. In those sports, the game is segmented into discrete events that can be easily studied: the pitch and the at-bat in baseball and the play or the series or the drive in football—these are easily identifiable events that have a distinct start and end. Hockey is a fluid game, with players changing lines on the fly and the action moving up and down the ice uninterrupted, sometimes for several minutes at a time. For hockey researchers, this presents a problem because it limits the amount of data we can collect—until now we have pretty much been limited to recording simple events like shots on goal. But recently some of the brightest minds in the field have developed new technology to calculate a wealth of new statistics and exponentially enhance our understanding of the game. I have been fortunate enough to come along for the ride.

Hockey is fundamentally a game of possession—it is almost impossible to score a goal if you don’t control the puck. But there isn’t a good way to measure or quantify possession right now—in football they track time of possession, but in that sport either one team or the other controls the ball.  In hockey, there are times when no team controls the puck, and the game can stall in the neutral zone or along the boards where players battle for possession (perhaps Schrodinger would suggest that in these instances, bothteams have possession, but that’s a different discussion.)

If Schrodinger was a hockey fan

The present research uses zone entry as a surrogate for possession, because thanks to the play-by-play data that the NHL makes available for each game and some very nifty spreadsheet wizardry, we can extrapolate shot and goal data based on zone entry type and timestamp.


I want to make sure anyone can understand this article, even those who may not be familiar with the rules of hockey, so here are some definitions if you need them.

Defensive Zone/Neutral Zone/Offensive Zone: The ice is divided into three equal parts—a team’s defensive zone is where their own goalie is (what they’re trying to protect,) the offensive zone is where the opponent’s goalie is (where they’re trying to score,) and the neutral zone is the middle of the ice between the two blue lines (see diagram.)

Controlled Zone Entry: A player skates with the puck from the neutral zone into his team’s offensive zone, or a player passes the puck across the blue line to his teammate as he is skating into the offensive zone.

Uncontrolled Zone Entry: A player “dumps the puck in” to the offensive zone by flipping it though the air or sending a hard shot along the ice, where his teammates try to regain possession of the puck before the opponents do. Or, a player who is positioned at the blue line receives a pass from his teammate, and he redirects it or “tips it in” to the offensive zone, where again his teammates battle for possession.

Fenwick: Shots + Missed Shots = Fenwick. Hockey researchers prefer to look at more than just shots on goal to provide a more robust analysis of the game. Fenwick totals are understood to be the sum of shots on goal and missed shots by any player on the ice.


Dependent (Outcome) Variables

In addition to goals, the present research uses shots and missed shots (Fenwick, see Definitions above) as a broader representation of a team or player’s offensive ability. The same way baseball researchers are interested in hits as well as runs; and football researchers care about yards as well as touchdowns, hockey nerds use shots to measure offense. The same way that hits lead to runs and gaining yards result in touchdowns, more shots are more opportunities for goals. To quote the great philosopher Wayne Gretzky, “You miss 100% of the shots you don’t take.” The key reason to study shots (and more broadly missed shots and sometimes blocked shots) instead of just goals is that…well, goals are hard to come by! In hockey, there is a man whose job it is to stand in front of the goal, and his entire paycheck is dependent on how many times he can place his body between the net and the puck so that little bit of rubber crashes into him instead of going into the goal. And there are a lot of very talented goalies in the NHL that can make it very frustrating for guys like Boston’s Milan Lucic. So, because goals are a generally rare occurrence and shots are more bountiful, we get better measurements when we use Fenwick.

Research Questions

Is there a difference between controlled entries and uncontrolled entries in terms of the number of Fenwick shots generated and goals scored as a result of each? Or…is it better to carry the puck into the offensive zone, or dump it in?


To collect this data, I used the NHL’s Game Center Vault feature <link> which allows me to go back and watch all the games from the 2011-12 season.* While watching each game, I made an entry into an Excel spreadsheet recording the following information: time, entry type (see table below,) player number if it was the Wild, or just “Opp” if it was the opponent, and team strength/opponent strength. That is, 5-5 for even strength, 5-4 if the Wild were on a power play, or 4-5 if the Wild were killing a penalty. Only 5-vs-5 data were included for data analysis. For this research, I did not record a “dump and change” as an uncontrolled entry when a player flipped the puck in and immediately went for a line change.

The entry type codes are as follows:

Controlled Entries: C = Carry in, P = Pass in

Uncontrolled Entries: D = Dump in, T = Tip in, X = Other

Here is a sample of data entry from one of the games:

Once the data were entered, I imported official NHL play-by-play data into a separate worksheet. The NHL website makes this data available for each game <link>. The original researchers wrote macros to do the rest of the work—based on the time stamps, the macros figure out how many shots and goals occurred during each zone entry. Finally, the outcome data for each game is copied and pasted into another file that aggregates season totals. “I love technology/ but not as much as you, you see…”

*Actually, not all the games—one contest has been missing from the Vault, the November 3rd matchup between the Wild and the Vancouver Canucks is not available. I have notified the good folks over at about this several times, but they haven’t fixed it yet.


This write-up analyzes the first 60 games of the Minnesota Wild 2011-12 season. To this point, 11,105 entries have been recorded for the Wild and their opponents.

Team-Level Results

On average, the Wild enter the offensive zone 46.4 times per 60 minutes at even-strength, while their opponents gain the zone 52.7 times. While it is always better to spend more time in your offensive zone than your defensive zone, the Wild are known to play a defensive style so this discrepancy does not seem too alarming. However, over the course of an 82-game season, as that difference adds up cumulatively, the Wild are getting a lot less chances to score than their opponents.

The Wild get 0.42 shots per entry (uncontrolled and controlled combined,) while their opponents get 0.45 shots/entry. Minnesota’s entry ratio is 44% controlled, while their opponents are split 50-50 between controlled and uncontrolled. The Wild get 0.58 shots per controlled entry and their opponents get 0.60, while uncontrolled entries lead to 0.29 and 0.30 shots respectively. The number of shots generated for the different categories of zone entry are remarkably similar, and these findings are consistent with research on other teams (links to other studies will be provided at the end of this article.)

The Wild get 0.34 shots per offensive zone faceoff (both won and lost) and 0.29 shots per defensive zone entry. I have not checked these specific figures with other researchers but 0.34 per OZF seems low.

Player-Level Results

Due to the volume of injuries the Wild sustained last year, sheer numbers of zone entries do not accurately reflect individual player performance. When I have completed the entire season, I will provide a more thorough analysis of player’s contributions. For now, I will just give some simple stats.

Discussion/Future Research

Based on this research and that of other teams, we can definitively say that controlled entries lead to more shots on goal, by a ratio of two-to-one. Teams get 0.6 shots per carry-in or pass-in, and 0.3 shots per dump-in or tip-in. It is interesting to note that these figures hold true for top liners like Dany Heatley and Mikko Koivu, as well as grinders or players with a defense-first reputation like Darroll Powe. Often, such players are coached to focus on playing a dump-and-chase game and an aggressive forecheck, but in terms of pure shot production, they are just as effective at creating shots from controlled entries.

Hockey is like poker, in that if you do the same thing all the time, your opponent will catch on and adjust to negate your tactics. Dump-and-chase and strong forechecking are necessary to a well-rounded strategy for any team, but based on the data that we have available, it should be understood that such tactics lead to vastly decreased opportunities for shots, and therefore goals. But anyone who has watched a game of hockey knows there are times when a controlled entry is just not possible–sometimes the only option for a player is to whack the puck into the zone. Obviously, an uncontrolled zone entry is preferable to no zone entry, but the data suggest that coaching players who are stereotyped as “grinders” or “energy guys” to dump the puck in reflexively may be hindering the team’s offensive chances. While watching these games, it seemed to me like Nick Johnson couldn’t wait to flip the puck deep into the opponent’s zone, and even when he had a chance to carry it in he would opt for a dump in.

The data on Marek Zidlicky presents a good case for using shot-based metrics instead of goal-based. Zidlicky had exactly ZERO goals this season in a Wild sweater, but his controlled entry ratio was better than any other defenseman, and the team got more shots from his controlled entries than other blueliners. His departure from the team became inevitable, but the numbers here suggest that though he didn’t get the point production that was expected from him, he was still effective at creating shots.

I am very excited to be nearing the completion of this dataset, as I will be able to do quite a bit more with the numbers when I have a complete season. The information presented here is just the tip of the iceberg, and there are lots more opportunities for analysis, including: examining differences in home/away games, tracking zone entries when the team is leading, trailing, leading or trailing big (2+ goals), looking at division opponents, who are usually more familiar with team strategies…the list goes on and on. Moving forward, if and when there is a 2012-13 season, I will continue to track entries, but I am thinking about expanding the “Other” category to specify things like defensive zone turnovers, in an effort to quantify forechecking. If you have your own questions or thoughts, please do not hesitate to post a comment here, or you can get in touch with me via Twitter (@Hashtag_Hockey) or e-mail (

Thanks very much for reading, and until next time, remember to hit that blue line and keep going…always and forever…always and forever.

Links to Broadstreet Hockey Flyers Zone Entry Articles

Flyers Zone Entries 1: Opening Statement

Flyers Zone Entries 2: Individual Puck Handling

Flyers Zone Entries 3: Off-puck Contributions

Flyers Zone Entries 4: Team -level Results