What is Fenwick in Hockey? (Definition & Core Concept)

Fenwick is an advanced hockey statistic that measures shot attempt differential at even strength, specifically counting all unblocked shot attempts. Named after Calgary Flames blogger Matt Fenwick, this metric has become one of the most important tools in modern hockey analytics for evaluating team performance and possession control.

In its simplest form, Fenwick represents the total number of unblocked shots your team takes minus the total number of unblocked shots your opponent takes during a game. It's often expressed as Fenwick percentage (FF%) — the percentage of all unblocked shot attempts that belong to one team.

The Basic Definition

Fenwick includes three types of shots:

• Shots on goal (SOG) — shots that reach the goaltender or go in the net
• Missed shots — shots that miss the net entirely
• Post shots — shots that hit the goalpost

Fenwick excludes one critical element:

• Blocked shots — shots that are stopped by a defending player before reaching the goaltender

This distinction is fundamental to understanding Fenwick's philosophy. By excluding blocked shots, Fenwick attempts to measure offensive pressure and scoring chance generation more accurately than its predecessor, Corsi.

How Fenwick Differs from Corsi

The relationship between Fenwick and Corsi is simple: Fenwick is Corsi without blocked shots.

At first glance, this seems like a minor difference. However, it represents a fundamental philosophical debate in hockey analytics. Matt Fenwick's original argument was that blocked shots are either:

1. Not scoring chances at all — A shot that gets blocked never had a realistic chance of going in
2. From worse scoring areas — Shots that get blocked tend to come from lower-quality areas of the ice

By excluding blocked shots, Fenwick rewards players and teams that generate unobstructed shot attempts while not penalizing excellent defensive shot-blocking. This makes Fenwick slightly more selective than Corsi, focusing on the "cleaner" shot attempts that more directly correlate with scoring opportunities.

In practice, most teams' Corsi and Fenwick numbers are quite similar, typically differing by only 2-5 percentage points. However, for teams with exceptional shot-blocking ability (either strong or weak), the difference becomes more pronounced.

Where Did Fenwick Come From? (History & Origin)

Matt Fenwick and the Birth of the Metric

On November 22, 2007, a Calgary Flames blogger named Matt Fenwick published a blog post on the Battle of Alberta blog that would fundamentally shape how hockey analysts evaluate team performance. In this post, Fenwick proposed a simple modification to the existing Corsi statistic — remove blocked shots from the calculation.

His original justification was elegantly concise:

"My argument is basically: The whole (or perhaps best) use of Corsi is to have objective figures that can be used as a proxy for scoring chances. A shot that is blocked is either a) not a scoring chance at all, or b) on average from a worse scoring area than shots/posts/missed shots."

This wasn't a revolutionary idea in isolation — it was a thoughtful refinement of an existing concept. However, the hockey analytics community embraced it, and within a few years, Fenwick became as widely discussed as Corsi itself. The metric eventually became standardized across major hockey analytics platforms and databases.

What's remarkable about Fenwick's adoption is that it happened organically. There was no official NHL endorsement, no media campaign. Instead, it spread through the analytics community because practitioners found it useful. Matt Fenwick never worked for an NHL team or major sports organization — he was simply a dedicated fan with a good idea.

Evolution of Hockey Analytics

Fenwick emerged during a pivotal moment in hockey analytics history. The early 2000s saw the rise of the "advanced stats" movement, driven by independent bloggers and analysts who believed traditional statistics (goals, assists, plus-minus) didn't tell the full story of player and team performance.

Corsi (named after goaltending coach Jim Corsi, though developed by others) was introduced around 2007-2008 as the first widely-adopted shot attempt metric. It quickly became controversial — some argued it was too broad and included "noise" (like blocked shots), while others defended it as a simple, objective measure of possession.

Fenwick arrived as a natural response to these debates. By 2010-2012, both metrics were being used in parallel, with analysts often citing both Corsi and Fenwick to provide a more complete picture. Today, Fenwick is considered the more refined metric by many in the analytics community, though Corsi remains widely used due to its simplicity and larger sample sizes.

The broader context matters: Fenwick's rise coincided with the NHL's gradual acceptance of analytics. Teams like the Los Angeles Kings (2012 Stanley Cup winners) and the Chicago Blackhawks (2013 and 2015 Cup winners) publicly embraced analytics, including metrics like Fenwick. This legitimized the field and accelerated adoption across the league.

How Do You Calculate Fenwick? (Formula & Examples)

The Fenwick Formula Explained

Calculating Fenwick is straightforward — it requires only basic addition and subtraction. Here's the core formula:

Fenwick For (FF) = Shots on Goal For + Missed Shots For
Fenwick Against (FA) = Shots on Goal Against + Missed Shots Against
Fenwick Differential (F+/-) = FF – FA
Fenwick For Percentage (FF%) = (FF ÷ (FF + FA)) × 100%

Let's break down what each component means:

Key Point: All statistics are measured at even strength (5-on-5 play) only. Power plays and penalty kills are excluded, as they distort the natural flow of the game and don't reflect true team ability.

Real-World Example Walkthrough

Let's work through a complete example using realistic NHL game statistics:

Scenario: The Colorado Avalanche play the Vegas Golden Knights. Here are the even-strength shot statistics:

Colorado Avalanche (For):

• Shots on Goal: 26
• Missed Shots: 14
• Blocked Shots: 8 (not counted in Fenwick)

Vegas Golden Knights (Against):

• Shots on Goal: 19
• Missed Shots: 7
• Blocked Shots: 11 (not counted in Fenwick)

Calculation:

1. Colorado Fenwick For (FF) = 26 + 14 = 40
2. Vegas Fenwick Against (FA) = 19 + 7 = 26
3. Colorado Fenwick Differential (F+/-) = 40 – 26 = +14
4. Colorado Fenwick For Percentage (FF%) = (40 ÷ (40 + 26)) × 100 = (40 ÷ 66) × 100 = 60.6%

Interpretation: Colorado had 60.6% of the unblocked shot attempts in the game, meaning they controlled the puck significantly better than Vegas. The +14 differential is substantial — in a typical game, a +10 or better differential is considered strong.

Notice that blocked shots (8 for Colorado, 11 for Vegas) don't factor into the calculation at all. This is intentional — Vegas blocked more shots, but that doesn't improve their Fenwick, because those blocked shots never represented true scoring chances anyway.

Fenwick for Individual Players

Fenwick isn't just a team statistic — it can also be calculated for individual players by measuring shot attempts while that player is on the ice.

Player On-Ice Fenwick For (FF) = Unblocked shots by player's team while player is on ice
Player On-Ice Fenwick Against (FA) = Unblocked shots by opponent while player is on ice
Player Fenwick For Percentage (FF%) = (FF ÷ (FF + FA)) × 100%
Relative Fenwick (FF% Rel) = Player's FF% on ice – Player's FF% off ice

This reveals a player's individual impact on possession. A player with a positive relative Fenwick means the team's Fenwick percentage is higher when he's on the ice than when he's off the ice — a sign of good possession play. Conversely, a negative relative Fenwick suggests the team struggles to maintain possession when that player is playing.

For example, if a player has a +5% relative Fenwick, it means his team's FF% is 5 percentage points higher when he's playing versus when he's not. Over an 82-game season, this compounds into a significant impact.

What Does Fenwick Percentage Mean? (Interpretation)

The 50% Threshold

In hockey analytics, 50% is the magic number for Fenwick. A Fenwick percentage of exactly 50% means perfect parity — your team and opponent generated equal unblocked shot attempts. Anything above 50% indicates possession advantage; anything below indicates possession disadvantage.

What does a 50%+ Fenwick percentage mean?

Research shows a strong correlation between maintaining a Fenwick percentage above 50% and playoff success:

• 12-16 of the 16 playoff teams per year have a Fenwick percentage above 50% or rank in the top 16
• Teams with sustained high Fenwick percentages (52%+) are significantly more likely to make the playoffs
• The correlation is even stronger when looking at Fenwick Close (close-game situations)

However, it's important to understand that correlation doesn't guarantee causation. A high Fenwick percentage doesn't guarantee playoff success — other factors like goaltending, special teams, and luck play critical roles. But it's one of the strongest predictive indicators available.

The Los Angeles Kings Example (2011-12 Season):

This is a famous case study in hockey analytics. Early in the 2011-12 season:

• Minnesota Wild: Leading the NHL with 45 points through 33 games, but had a Fenwick percentage of 42.6%
• Los Angeles Kings: In 11th place in the Western Conference with 14-14-4 record, but had a Fenwick percentage of 51.3%

By season's end, the narrative reversed completely:

• Minnesota: Finished 35-36-11 with 81 points (missed playoffs)
• Los Angeles: Finished 40-27-15 with 95 points (made playoffs and won the Stanley Cup)

This example demonstrates Fenwick's predictive power. The Kings' superior possession metrics suggested they were the better team, despite early standings suggesting otherwise. Their high Fenwick percentage was sustainable and predictive of future success.

Fenwick Close vs. Overall Fenwick

One critical refinement to Fenwick analysis is Fenwick Close — measuring Fenwick only in close-game situations.

Fenwick Close Definition:

• Periods 1 & 2: Score differential of 1 goal or less
• Period 3: Tied game only

Why does this matter? Score effects are a well-documented phenomenon in hockey:

• Trailing teams naturally generate more shot attempts because they're pressing to score and catch up
• Leading teams sit back defensively, absorb pressure, and generate fewer shot attempts
• This creates artificial inflation/deflation of Fenwick percentages

By looking only at close-game situations, we remove score effects and get a clearer picture of a team's true possession ability. Teams with high Fenwick Close percentages are demonstrably better at controlling the puck when the game is competitive and both teams are playing "normal" hockey.

Research Finding: Among playoff teams, the correlation between Fenwick Close and success is even stronger than overall Fenwick, because it isolates true possession skill from score effects.

Relative Fenwick and Team Impact

When analyzing individual players, Relative Fenwick (FF% Rel) is more meaningful than absolute Fenwick, because it accounts for team quality.

A star player on a dominant possession team might have a 55% FF%, but that doesn't tell you much about his individual skill — the team might be 55% anyway. However, if that same player has a +3% relative Fenwick, it means he personally elevates the team's possession by 3 percentage points.

Conversely, a player on a weak team with a 48% FF% might actually be driving possession — his relative Fenwick might be +2%, meaning the team is 2% better with him on the ice.

Why Does Fenwick Matter? (Application & Relevance)

Fenwick as a Possession Proxy

At its core, Fenwick is a possession metric. It measures how much of the game one team controls the puck in the offensive zone.

The logic chain is straightforward:

1. Possession = Puck Control — The team with more unblocked shot attempts has the puck more often in the offensive zone
2. Puck Control = Scoring Chances — More time in the offensive zone = more scoring opportunities
3. Scoring Chances = Goals — More opportunities eventually lead to more goals
4. Goals = Winning — Teams that score more goals win more games

This chain isn't guaranteed — a team could dominate possession but lose due to poor finishing or exceptional goaltending from the opponent. But over a large sample size (a full season), the relationship holds strong.

Modern NHL thinking, influenced by coaches like Darryl Sutter of the Los Angeles Kings, emphasizes possession as the foundation of winning:

"The game's changed. They think there's defending in today's game. Nah, it's how much you have the puck. Teams that play around in their own zone, they're defending, but they're generally getting scored on."

This philosophy — that defense is really just possession — has become mainstream. Teams that control the puck don't have to defend as much, because the opponent doesn't have the puck.

Predicting Team Success

Fenwick's predictive validity has been extensively researched. While no single metric perfectly predicts outcomes, Fenwick is among the strongest:

What the research shows:

• Team Fenwick percentage correlates significantly with playoff qualification — Teams with sustained FF% above 50% make the playoffs at a much higher rate than those below 50%
• Fenwick Close is even more predictive — Because it removes score effects, it's a purer measure of team quality
• The correlation strengthens over time — Early-season Fenwick can be noisy, but by season's midpoint, it becomes highly predictive

Important caveat: Fenwick is not destiny. Other factors matter:

• Goaltending — A team with great Fenwick but poor goaltending will underperform
• Shooting percentage — Teams that convert their chances at high rates can win despite lower Fenwick
• Special teams — Power play and penalty kill performance can swing games regardless of Fenwick
• Luck (PDO) — Short-term results always include randomness

The best analysts use Fenwick as one tool among many, not as a sole predictor.

Practical Applications for Bettors and Analysts

For those using advanced stats in sports betting and team analysis, Fenwick is invaluable:

For Bettors:

• Line Shopping: Teams with significantly higher Fenwick than their opponent's are often undervalued, especially if the market hasn't adjusted for possession metrics
• Regression Identification: A team with poor Fenwick but good record is likely due for regression — unsustainable luck is masking underlying weakness
• Player Props: Players with strong on-ice Fenwick relative to their team are valuable — they're genuinely driving possession and opportunity creation

For Analysts:

• Team Evaluation: Fenwick provides objective evidence of which team controls the game, independent of score or goaltending performance
• Trade Analysis: A player with high relative Fenwick on a weak team might flourish on a stronger team, or vice versa
• Coaching Evaluation: Coaches can be evaluated on their team's ability to generate possession metrics, which is more controllable than goals or wins

For General Managers:

• Contract Decisions: A player with consistently positive relative Fenwick is likely to be valuable regardless of goal totals, because he's generating opportunity
• System Fit: Players with high Fenwick in one system might struggle in another, based on how their style aligns with possession-based systems

What Are the Limitations of Fenwick? (Critical Analysis)

What Fenwick Doesn't Measure

Fenwick is powerful, but it has blind spots. Understanding these limitations is crucial to using the metric correctly.

1. Shot Quality

Fenwick counts all unblocked shots equally. A shot from the slot (high-danger area) counts the same as a shot from the point (low-danger area). This is a fundamental limitation — not all shots are created equal.

A team could have 60% Fenwick but generate poor-quality chances, while their opponent generates fewer but more dangerous chances. This is why Expected Goals (xG) was developed as a complementary metric — it weights shots by their likelihood of going in based on location, angle, and other factors.

2. Goaltending

Fenwick measures shot generation, not shot prevention. A team with 45% Fenwick but an elite goaltender might win games, while a team with 55% Fenwick and a poor goaltender might lose. The metric is blind to save percentage.

This is why analysts look at PDO (a combination of shooting percentage and save percentage) alongside Fenwick — to understand whether a team's record is driven by possession or goaltending luck.

3. Defensive Skill (Shot Blocking)

By excluding blocked shots, Fenwick implicitly assumes shot blocking isn't a skill. But blocking shots is a skill — some players and teams are exceptionally good at it. By not counting blocked shots, Fenwick may undervalue strong defensive teams that excel at shot suppression without allowing unblocked attempts.

This is a philosophical trade-off. Some analysts prefer Corsi (which includes blocked shots) for this reason, while others argue that blocked shots are too noisy and unreliable to count.

4. Luck and Randomness

All statistics are subject to short-term variance. A team might have 52% Fenwick but lose a game due to unlucky bounces, post hits, or goaltending performance. Fenwick is a predictor, not a guarantee.

Sample Size and Stability

Here's a critical point: Fenwick requires a larger sample size than Corsi to be reliable.

Why? Because Fenwick has fewer events (blocked shots are excluded), the sample is smaller. This means:

• Single games: Fenwick is very noisy — a team might have 60% Fenwick in one game and 40% in the next, even if they're the same quality team
• 5-10 games: Still unreliable — small sample sizes create variance
• 20-30 games: More stable, but still subject to randomness
• 50+ games: Generally reliable — at this point, Fenwick becomes predictive
• Full season (82 games): Highly reliable — this is the gold standard

This is why serious analysts emphasize Fenwick Close over overall Fenwick — it removes some noise by excluding blowout situations where teams aren't playing normally.

Common Misconceptions About Fenwick

Misconception 1: "High Fenwick guarantees wins"

False. Fenwick is a strong predictor, but it's not destiny. Goaltending, special teams, and luck matter. A team with 55% Fenwick might win 48% of games due to poor goaltending.

Misconception 2: "Low Fenwick means a team is bad"

False. A team with 48% Fenwick might still win if they have elite goaltending and efficient special teams. The Kings won the Cup with lower Fenwick than some other teams because their goaltending was exceptional.

Misconception 3: "Fenwick is more important than goals"

False. Goals are what win games. Fenwick is a proxy for goal-generating opportunity. If a team has low Fenwick but high goal totals, the goals are what matter in the standings — though the low Fenwick suggests unsustainability.

Misconception 4: "Fenwick eliminates the need for other metrics"

False. Fenwick is one tool. The best analysis combines Fenwick with Expected Goals, PDO, special teams metrics, and other data.

How Does Fenwick Compare to Other Metrics? (Related Concepts)

Fenwick vs. Expected Goals (xG)

Fenwick and Expected Goals are complementary, not competing metrics:

Example: Team A has 50 shots (45% Fenwick), Team B has 40 shots (55% Fenwick). Team A's shots are from high-danger areas (high xG). Team B's shots are from low-danger areas (low xG). In this case, Team A's lower Fenwick is misleading — their shots are more dangerous.

The best analysis uses both: Fenwick tells you who controls the puck; xG tells you who generates dangerous chances.

Fenwick vs. High-Danger Chances

High-Danger Chances (HDC) are an even more selective metric than Fenwick. They count only shots from the most dangerous areas (typically defined as the slot and prime scoring areas).

High-Danger Chances are more predictive of goals than Fenwick, but they require larger sample sizes to be reliable. A player might have 52% Fenwick but 48% HDC — the HDC is the better predictor of whether he's actually generating scoring chances.

Using Fenwick with Other Metrics

The most sophisticated analysis combines multiple metrics:

Fenwick + PDO:

• Fenwick shows possession
• PDO (shooting % + save %) shows luck
• Together, they explain whether a team's record is driven by possession or goaltending

Fenwick + xG:

• Fenwick shows volume
• xG shows quality
• Together, they show both quantity and quality of chances

Fenwick + Special Teams:

• Fenwick shows 5-on-5 play
• Special teams metrics show power play and penalty kill
• Together, they explain overall team performance

Example Analysis: A team has 51% Fenwick (slightly above average), 0.98 PDO (slightly below average), and elite special teams. This suggests:

• The team controls the puck slightly better than average
• They're getting slightly unlucky with goaltending and shooting
• But their special teams are carrying them to wins
• This is unsustainable — regression is likely unless they improve goaltending or even-strength performance

Frequently Asked Questions About Fenwick

What is Fenwick in hockey?

Fenwick is an advanced hockey statistic that measures unblocked shot attempt differential at even strength. It counts shots on goal and missed shots, but excludes blocked shots. Named after Calgary Flames blogger Matt Fenwick, it's used to evaluate team possession and predict playoff success. A Fenwick percentage above 50% indicates a team controls the puck better than their opponent.

How do you calculate Fenwick?

Fenwick is calculated by adding a team's shots on goal and missed shots (Fenwick For), then subtracting the opponent's shots on goal and missed shots (Fenwick Against). The formula is: FF% = (FF ÷ (FF + FA)) × 100%. For example, if your team takes 40 unblocked shots and the opponent takes 30, your Fenwick percentage is 57.1% (40 ÷ 70 × 100).

What's the difference between Fenwick and Corsi?

The only difference is that Corsi includes blocked shots, while Fenwick excludes them. Corsi counts all shot attempts (shots on goal, missed shots, and blocked shots), while Fenwick counts only unblocked shots. This makes Fenwick more selective, focusing on shots that actually reached the offensive zone without being blocked.

Why is Fenwick important?

Fenwick is important because it's one of the strongest predictors of team success and playoff qualification. Teams with sustained Fenwick percentages above 50% are significantly more likely to make the playoffs. It provides objective evidence of possession control, independent of goals or goaltending performance, making it valuable for team evaluation, player analysis, and sports betting.

What does Fenwick percentage mean?

Fenwick percentage (FF%) represents the proportion of unblocked shot attempts that belong to one team. A Fenwick percentage of 50% means equal possession; above 50% indicates possession advantage; below 50% indicates possession disadvantage. A percentage above 52% is considered strong, and teams with 50%+ Fenwick Close (in tight games) make the playoffs at high rates.

Is Fenwick a good predictor of team success?

Yes, Fenwick is one of the strongest predictive metrics available. Research shows 12-16 of the 16 playoff teams per year have Fenwick percentages above 50%. However, it's not a guarantee — goaltending, special teams, and luck also matter. Teams with high Fenwick but poor goaltending can underperform, and vice versa.

What is Fenwick Close?

Fenwick Close measures Fenwick only in close-game situations (score differential of 1 goal or less in periods 1-2, tied games in period 3). It's more predictive than overall Fenwick because it removes "score effects" — the tendency of trailing teams to generate more shots. Fenwick Close is a purer measure of a team's true possession ability.

What are the limitations of Fenwick?

Fenwick doesn't measure shot quality (all shots count equally), goaltending performance, or the skill of shot-blocking. It's also subject to variance in small sample sizes — single games or short stretches can be noisy. Additionally, a team with high Fenwick but poor goaltending might underperform, while a team with low Fenwick but elite goaltending might overperform.

How does Fenwick compare to Expected Goals (xG)?

Fenwick measures shot volume and possession, while Expected Goals measures shot quality and danger. Fenwick counts all unblocked shots equally; xG weights shots by their probability of going in based on location and angle. Together, they provide a complete picture: Fenwick shows who controls the puck, xG shows who generates dangerous chances.

Can you calculate Fenwick for individual players?

Yes. Player on-ice Fenwick measures unblocked shot attempts while a specific player is on the ice. Relative Fenwick (FF% Rel) compares a player's on-ice Fenwick percentage to their off-ice percentage, showing how much they personally impact possession. A positive relative Fenwick means the team's possession improves when that player is playing.

Related Terms

• Corsi — All shot attempts including blocked shots
• Expected Goals — Probability-weighted shot quality metric
• Hockey xG — Expected goals specific to hockey analytics
• PDO — Combined shooting and save percentage metric
• High Danger Chances — Shots from the most dangerous scoring areas