Fenwick Per Situation Calculator
Calculate fenwick per situation with our free tool. See your stats, compare against averages, and track progress over time.
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Even Strength (5v5) -- Against
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Formula
Fenwick counts all unblocked shot attempts (shots on goal plus missed shots, excluding blocked shots). Fenwick percentage measures the share of unblocked shot attempts belonging to a team.
Last reviewed: December 2025
Worked Examples
Example 1: Even Strength Fenwick Analysis
Example 2: All-Situations Fenwick Breakdown
Background & Theory
The Fenwick (per Situation) applies the following established principles and formulas. Sports statistics and performance metrics represent one of the most data-rich domains of applied mathematics available to the general public. Baseball, in particular, has developed an exceptionally dense vocabulary of calculated metrics. Earned run average (ERA) quantifies a pitcher's effectiveness as (earned runs × 9) / innings pitched, normalising performance to a nine-inning standard regardless of how many complete games were pitched. WHIP, or walks and hits per inning pitched, is computed as (walks + hits) / innings pitched and provides a complementary measure of how frequently a pitcher allows baserunners. Batting average, one of the oldest statistics in the sport, is simply hits / at-bats, though more modern metrics such as on-base percentage and slugging percentage have largely supplanted it as primary performance indicators. The NFL passer rating formula is considerably more complex, combining completion percentage, yards per attempt, touchdown rate, and interception rate into a composite score scaled to a 0–158.3 range. Golf handicap calculation, now governed by the World Handicap System introduced in 2020, uses a Handicap Differential formula applied to the best 8 of a player's most recent 20 score differentials, with adjustments for course rating and slope. The Elo rating system, originally developed by physicist Arpad Elo for chess ranking in the 1960s, has become a widely adopted framework for competitive ranking in sports ranging from football to table tennis. It updates each player's rating after every match based on the margin of expected versus actual result. In endurance sports, pace calculation converts total time to a per-mile or per-kilometre rate, informing training intensity and race strategy. In cycling, power-to-weight ratio (watts per kilogram) is the primary determinant of climbing performance and is central to both professional race analysis and amateur fitness tracking. Fantasy sports scoring systems synthesise multiple individual statistics into aggregate point totals, requiring participants to understand the relative value of different performance categories across sports.
History
The history behind the Fenwick (per Situation) traces back through the following developments. Organised athletic competition has roots extending to ancient Greece, where the Olympic Games were held at Olympia beginning around 776 BCE. These early games were embedded in religious observance and civic identity, featuring events such as sprinting, wrestling, and the pentathlon. The codification of modern sport rules accelerated dramatically in 19th century Britain, where industrialisation created both the leisure time and the institutional infrastructure for organised competition. The Football Association formalised the rules of association football in 1863, and similar governing bodies for cricket, rugby, tennis, and athletics followed in subsequent decades. Pierre de Coubertin, a French educator inspired by the English model of sport as character-building, campaigned to revive the Olympic Games as a modern international institution. The first modern Summer Olympics were held in Athens in 1896, establishing the template for international multi-sport competition that has continued to the present. FIFA, the international governing body for association football, was founded in Paris in 1904 with seven member nations. The serious statistical analysis of baseball, later termed sabermetrics, was pioneered by writers and analysts including Bill James beginning in the late 1970s. James self-published his Baseball Abstract annuals starting in 1977, introducing rigorous empirical methods to a domain previously dominated by traditional counting statistics and subjective scouting. His work influenced a generation of analysts and front-office executives. The publication of Michael Lewis's Moneyball in 2003, documenting the Oakland Athletics' 2002 season and their use of on-base percentage and other undervalued metrics, brought sports analytics to mainstream attention. The subsequent analytics revolution reshaped hiring practices and game strategy across professional sports leagues. Fantasy sports, which require participants to engage directly with statistical outputs, grew from a hobby practised by a few thousand enthusiasts in the 1980s into a multi-billion dollar industry by the 2010s, with tens of millions of participants across football, baseball, basketball, and other sports.
Frequently Asked Questions
Formula
Fenwick For (FF) = Shots on Goal + Missed Shots | FF% = FF / (FF + FA) x 100
Fenwick counts all unblocked shot attempts (shots on goal plus missed shots, excluding blocked shots). Fenwick percentage measures the share of unblocked shot attempts belonging to a team.
Worked Examples
Example 1: Even Strength Fenwick Analysis
Problem: A team has 32 shots on goal and 14 missed shots for, versus 27 shots on goal and 11 missed shots against at even strength over 5 games.
Solution: Fenwick For (FF) = 32 + 14 = 46\nFenwick Against (FA) = 27 + 11 = 38\nFenwick % = 46 / (46 + 38) = 46 / 84 = 54.76%\nFenwick For per game = 46 / 5 = 9.2\nFenwick Against per game = 38 / 5 = 7.6
Result: FF% = 54.8% (above average, strong possession team)
Example 2: All-Situations Fenwick Breakdown
Problem: At even strength: 30 FF, 25 FA. On power play: 10 FF. On penalty kill: 8 FA.
Solution: Total Fenwick For = 30 (ES) + 10 (PP) = 40\nTotal Fenwick Against = 25 (ES) + 8 (PK) = 33\nTotal FF% = 40 / (40 + 33) = 40 / 73 = 54.79%\nES FF% = 30 / (30 + 25) = 30 / 55 = 54.55%\nFenwick Differential = 40 - 33 = +7
Result: Total FF% = 54.8% | ES FF% = 54.5% | Differential = +7
Frequently Asked Questions
What is Fenwick in hockey and how is it calculated?
Fenwick is an advanced hockey statistic that measures shot attempt differential by counting all unblocked shot attempts, which includes both shots on goal and missed shots but excludes blocked shots. It was named after blogger Matt Fenwick who popularized this metric in hockey analytics circles. The basic formula is Fenwick For (FF) = Shots on Goal + Missed Shots, and Fenwick Against (FA) follows the same logic for the opposing team. Fenwick percentage (FF%) is calculated as FF / (FF + FA) multiplied by 100, where a value above 50% indicates a team is generating more unblocked shot attempts than its opponent.
Why does Fenwick exclude blocked shots from its calculation?
Fenwick excludes blocked shots because blocking is considered a repeatable defensive skill that can distort possession metrics. When a team blocks many shots, it inflates the Corsi against number even though the blocking team may actually be controlling play well. By removing blocked shots from the equation, Fenwick provides a cleaner measure of actual shot generation and territorial dominance. Some analysts believe Fenwick is a better predictor of future goal scoring than Corsi because it strips out the noise introduced by shot blocking tendencies and focuses on genuine offensive pressure.
What is the difference between Fenwick and Corsi?
Corsi counts all shot attempts including shots on goal, missed shots, and blocked shots, while Fenwick only counts shots on goal and missed shots, deliberately excluding blocked shots. Both metrics aim to measure puck possession and territorial control, but they differ in philosophy regarding blocked shots. Corsi treats every shot attempt equally as evidence of offensive zone time, whereas Fenwick argues that blocked shots reflect defensive positioning skill rather than true possession. In practice, the two metrics correlate highly (typically above 0.95), but Fenwick can reveal differences when teams have unusually high or low shot blocking rates.
How do you interpret Fenwick percentage by game situation?
Fenwick percentage varies significantly by game situation, which is why situational analysis matters. At even strength (5-on-5), a Fenwick percentage above 52% is considered strong, indicating the team consistently outgenerates opponents in unblocked shot attempts. On the power play, Fenwick For should be substantially higher since the team has a man advantage and more offensive zone time. On the penalty kill, a lower Fenwick Against is desirable, showing the shorthanded team limits opponent chances. Analysts often focus on even-strength Fenwick because special teams situations are heavily influenced by strategy rather than pure talent.
What is a good Fenwick percentage for an NHL team?
In the NHL, the league-average Fenwick percentage is exactly 50% by definition since every shot attempt for one team is a shot attempt against another. Teams with a Fenwick percentage consistently above 52% at even strength are considered elite possession teams, while teams below 48% are typically struggling to control play. Historically, dominant teams like the 2013-2014 Los Angeles Kings posted even-strength Fenwick percentages around 55%, which is exceptional. Individual player Fenwick percentages can range more widely, with top possession forwards often exceeding 55% and shutdown defensemen sometimes falling below 48%.
How does Fenwick Relative work and why is it useful?
Fenwick Relative (sometimes written as FF% Rel) measures a player or line combination performance relative to their own team when they are off the ice. It is calculated by subtracting the team Fenwick percentage when the player is off the ice from the Fenwick percentage when the player is on the ice. A positive Fenwick Relative means the team generates a better shot attempt share when that player is playing. This metric is valuable because it accounts for team quality, allowing fair comparisons between players on strong and weak teams. A player with a 54% Fenwick on a dominant team might have a lower Relative than a player with 50% on a bad team.
References
Reviewed by Sher, Sports Science & Nutrition Specialist · Editorial policy