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Fenwick is a hockey possession metric closely related to Corsi, with one key difference: it excludes blocked shots from the calculation, counting only unblocked shot attempts (shots on goal plus shots that missed the net). Named after Matt Fenwick, a blogger who popularized the concept in the 2000s, the metric is based on the reasoning that blocking shots is a team defensive skill that reflects the defending team's positioning and shot-blocking system rather than solely the shooter's intent. By removing blocked shots, Fenwick attempts to measure shot generation quality more precisely — a shot that reaches the net is inherently a better chance than one blocked at the point. In practice, Corsi and Fenwick are highly correlated (typically r>0.95 across a season), and analysts often use them interchangeably, though Fenwick tends to be preferred for evaluating individual offensive players since perimeter shot-blockers can artificially suppress a shooter's Corsi without reflecting genuine poor performance. The Buffalo Sabres under coach Lindy Ruff had some of the highest Fenwick numbers in the NHL in the late 2000s, building a possession-heavy style that was analytically ahead of its time. At the team level, Fenwick For% (FF%) above 52% has historically been a strong predictor of playoff qualification. The Tampa Bay Lightning's back-to-back Stanley Cup championships in 2020 and 2021 were built on both exceptional Fenwick numbers and above-average shooting percentages — the combination of quantity and quality that analytics teams dream of.
Fenwick For% (FF%) = FF / (FF + FA) x 100. FF = Unblocked shot attempts by player's team while player is on ice (shots on goal + missed shots, excluding blocked shots). FA = Unblocked shot attempts by opponent while player is on ice. Example: Player's team generates 18 unblocked shots (FF=18) while allowing 15 unblocked shots (FA=15). FF% = 18/(18+15) x 100 = 54.5%. Compare: if there were also 5 blocked shots each way, Corsi would be (23/46) x 100 = 50.0% — very different result.
- 1Track all shot attempts (shots on goal + missed shots + blocked shots) during even-strength play while the player is on the ice.
- 2Separate blocked shots from the total — record who blocked the shot (defending team) and remove these from the Fenwick calculation.
- 3Sum unblocked shots for (FF) and unblocked shots against (FA) for the player or team.
- 4Divide FF by total unblocked shots (FF + FA) and multiply by 100 for FF%.
- 5Compare FF% to CF% for the same player — a significant gap (more than 2-3%) suggests the team is either blocking many opponent shots (high CF%, lower FF%) or having many of their own shots blocked.
- 6Apply score-state and zone-start adjustments as with Corsi for context-appropriate comparisons.
- 7Use FF% alongside save percentage and shooting percentage to build a complete picture of team performance.
Victor Hedman's Fenwick numbers reflect Tampa Bay's exceptional puck movement system — his FF% is slightly lower than his CF% because Tampa's system includes shot-blocking as a defensive tool.
A team with very high shot-blocking rates (like the New Jersey Devils under Lou Lamoriello) will show CF% higher than FF% because they block many opponent shots that drop out of Fenwick.
This forward's shots are rarely blocked (indicating high shot quality), so Fenwick rates him higher than Corsi — the metric distinction matters for his evaluation.
Teams with FF% above 52% qualify for the NHL playoffs at approximately 65-70% rates historically, making Fenwick a useful but imperfect playoff predictor.
Professionals in engineering and electrical use Ice Hockey Fenwick as part of their standard analytical workflow to verify calculations, reduce arithmetic errors, and produce consistent results that can be documented, audited, and shared with colleagues, clients, or regulatory bodies for compliance purposes.
University professors and instructors incorporate Ice Hockey Fenwick into course materials, homework assignments, and exam preparation resources, allowing students to check manual calculations, build intuition about input-output relationships, and focus on conceptual understanding rather than arithmetic.
Consultants and advisors use Ice Hockey Fenwick to quickly model different scenarios during client meetings, enabling real-time exploration of what-if questions that would otherwise require returning to the office for detailed spreadsheet-based analysis and reporting.
Individual users rely on Ice Hockey Fenwick for personal planning decisions — comparing options, verifying quotes received from service providers, checking third-party calculations, and building confidence that the numbers behind an important decision have been computed correctly and consistently.
During 3-on-3 overtime, shot attempt rates change dramatically due to the open
During 3-on-3 overtime, shot attempt rates change dramatically due to the open ice — Fenwick from overtime is typically tracked separately or excluded from regular Fenwick analysis.
Players who serve primarily as penalty kill specialists will have distorted
Players who serve primarily as penalty kill specialists will have distorted Fenwick numbers since they are deployed in situations designed to suppress their team's shot attempts.
Extremely high or low team Fenwick numbers (above 56% or below 44%) may reflect
Extremely high or low team Fenwick numbers (above 56% or below 44%) may reflect small-sample variance rather than genuine ability differences, especially early in a season.
| Team | FF% (5v5) | Points | Playoff Result | Rank |
|---|---|---|---|---|
| Boston Bruins | 55.2% | 135 | 2nd Round | 1st |
| Tampa Bay Lightning | 53.8% | 101 | 1st Round Exit | 4th |
| Carolina Hurricanes | 53.1% | 113 | 2nd Round | 6th |
| Vegas Golden Knights | 52.4% | 111 | Stanley Cup Champions | 9th |
| Anaheim Ducks | 44.8% | 58 | No Playoffs | 32nd |
Is Fenwick or Corsi a better hockey metric?
In the context of Ice Hockey Fenwick, this depends on the specific inputs, assumptions, and goals of the user. The underlying formula provides a deterministic relationship between inputs and output, but real-world application requires interpreting the result within the broader context of engineering and electrical practice. Professionals typically cross-reference calculator output with industry benchmarks, historical data, and regulatory requirements. For the most reliable results, ensure inputs are sourced from verified data, understand which assumptions the formula makes, and consider running multiple scenarios to bracket the range of likely outcomes.
What is the difference between Fenwick and expected goals?
Ice Hockey Fenwick is a specialized calculation tool designed to help users compute and analyze key metrics in the engineering and electrical domain. It takes specific numeric inputs — typically drawn from real-world data such as measurements, rates, or quantities — and applies a validated mathematical formula to produce actionable results. The tool is valuable because it eliminates manual calculation errors, provides instant feedback when exploring different scenarios, and serves as both a decision-support instrument for professionals and a learning aid for students studying the underlying principles.
Who invented Fenwick?
In the context of Ice Hockey Fenwick, this depends on the specific inputs, assumptions, and goals of the user. The underlying formula provides a deterministic relationship between inputs and output, but real-world application requires interpreting the result within the broader context of engineering and electrical practice. Professionals typically cross-reference calculator output with industry benchmarks, historical data, and regulatory requirements. For the most reliable results, ensure inputs are sourced from verified data, understand which assumptions the formula makes, and consider running multiple scenarios to bracket the range of likely outcomes.
Does Fenwick predict future performance better than goals?
In the context of Ice Hockey Fenwick, this depends on the specific inputs, assumptions, and goals of the user. The underlying formula provides a deterministic relationship between inputs and output, but real-world application requires interpreting the result within the broader context of engineering and electrical practice. Professionals typically cross-reference calculator output with industry benchmarks, historical data, and regulatory requirements. For the most reliable results, ensure inputs are sourced from verified data, understand which assumptions the formula makes, and consider running multiple scenarios to bracket the range of likely outcomes.
What is 'Fenwick Close' in hockey analytics?
In the context of Ice Hockey Fenwick, this depends on the specific inputs, assumptions, and goals of the user. The underlying formula provides a deterministic relationship between inputs and output, but real-world application requires interpreting the result within the broader context of engineering and electrical practice. Professionals typically cross-reference calculator output with industry benchmarks, historical data, and regulatory requirements. For the most reliable results, ensure inputs are sourced from verified data, understand which assumptions the formula makes, and consider running multiple scenarios to bracket the range of likely outcomes.
How do I find Fenwick stats for NHL players?
In the context of Ice Hockey Fenwick, this depends on the specific inputs, assumptions, and goals of the user. The underlying formula provides a deterministic relationship between inputs and output, but real-world application requires interpreting the result within the broader context of engineering and electrical practice. Professionals typically cross-reference calculator output with industry benchmarks, historical data, and regulatory requirements. For the most reliable results, ensure inputs are sourced from verified data, understand which assumptions the formula makes, and consider running multiple scenarios to bracket the range of likely outcomes.
Do playoff teams have better Fenwick numbers?
In the context of Ice Hockey Fenwick, this depends on the specific inputs, assumptions, and goals of the user. The underlying formula provides a deterministic relationship between inputs and output, but real-world application requires interpreting the result within the broader context of engineering and electrical practice. Professionals typically cross-reference calculator output with industry benchmarks, historical data, and regulatory requirements. For the most reliable results, ensure inputs are sourced from verified data, understand which assumptions the formula makes, and consider running multiple scenarios to bracket the range of likely outcomes.
Pro Tip
When comparing Corsi and Fenwick for the same player, calculate the 'blocked shot differential' — if a player's FF% is significantly higher than their CF%, it means the opposing team is blocking many of their shots. This could indicate the player is taking too many perimeter shots that are predictable and easy to block, rather than finding shooting lanes. Use this gap as a shooting quality diagnostic.
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The 2009-10 Chicago Blackhawks, who won the Stanley Cup, were one of the first analytically studied championship teams — their Fenwick numbers were so superior to their opponents' that several pioneering hockey analysts predicted their championship before it happened, one of the early validations of possession metrics as meaningful predictors.