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Corsi is the foundational possession metric in modern hockey analytics, measuring the total shot attempt differential (for versus against) while a player is on the ice, at even strength. Named after Buffalo Sabres goaltender coach Jim Corsi, who used a broader shot-tracking method than the official NHL statistics to evaluate goaltender workload, the metric was popularized by bloggers in the early 2000s and subsequently adopted by NHL teams. A Corsi For% (CF%) of 50% means a player's team takes exactly as many shot attempts as they allow when that player is on the ice — essentially a coin flip possession. Sidney Crosby at his peak regularly posted CF% numbers above 56–58%, meaning his team generated roughly 56 shot attempts for every 44 allowed while he was playing — a massive sustained territorial dominance. The key insight behind Corsi is that shot attempts serve as a proxy for puck possession, and sustained puck possession is the most reliable predictor of winning at even strength. Unlike official NHL plus/minus, Corsi controls for shooting luck, goaltender performance, and score effects. Teams like the early 2000s Detroit Red Wings and the 2016-17 Pittsburgh Penguins built dynasties partly on exceptional possession metrics. Limitations include that Corsi doesn't distinguish between high-danger chances and shot attempts from the perimeter, treats all shot attempts equally regardless of shot quality, and is influenced by zone starts (players who start more offensive zone faceoffs will have higher Corsi). Score effects — where losing teams shoot more in desperation — can also distort individual Corsi numbers for players on teams that frequently lead or trail.
Corsi For% (CF%) = CF / (CF + CA) x 100. CF = Shot attempts by player's team while player is on ice (at even strength). CA = Shot attempts by opponent while player is on ice (at even strength). Shot attempts include shots on goal, blocked shots, and missed shots. Example: McDavid on ice for 24 shot attempts by Edmonton (CF=24) and 18 by opponent (CA=18). CF% = 24/(24+18) x 100 = 57.1%. Corsi+/- = CF - CA = 24 - 18 = +6.
- 1Track every shot attempt (shot on goal, blocked shot, missed shot) by both teams during even-strength play.
- 2Identify which players are on the ice for each shot attempt using real-time player tracking or shift data.
- 3Accumulate shot attempts for (CF) and against (CA) for each player across a game, season, or defined period.
- 4Divide CF by total shot attempts (CF + CA) and multiply by 100 to get CF%.
- 5Apply score-state filtering: separate Corsi during tied games (most neutral), while leading, and while trailing to control for score effects.
- 6Apply zone-start adjustment if comparing players with very different offensive vs. defensive zone faceoff percentages.
- 7Benchmark against league average (50%) and positional averages to contextualize the number.
McDavid's 56.8% CF% means Edmonton controlled 57 of every 100 shot attempts with him on the ice, a dominant possession figure for a full season.
A defensive forward with few offensive zone starts may show a raw CF% below 50% but be performing above average once zone starts are accounted for.
5v5 Corsi (excluding powerplay and penalty kill) is the cleanest measure of even-strength possession ability, removing special teams noise.
A team CF% of 53.7% over a full season is strongly predictive of playoff success; historically, teams above 53% CF% win approximately 60% of games.
Professionals in engineering and electrical use Ice Hockey Corsi 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 Corsi 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 Corsi 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 Corsi 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.
Goaltenders are traditionally excluded from individual Corsi analysis since
Goaltenders are traditionally excluded from individual Corsi analysis since they are on the ice for all situations and their Corsi reflects team performance more than individual contribution.
Outdoor games (Winter Classic, Stadium Series) often show abnormal Corsi
Outdoor games (Winter Classic, Stadium Series) often show abnormal Corsi numbers due to ice quality, wind, and unusual shooting conditions — these games may warrant exclusion from season-long analysis.
Short-handed situations (penalty kill) are typically excluded from Corsi
Short-handed situations (penalty kill) are typically excluded from Corsi evaluation because the intentional defensive posture during penalty killing would severely distort possession metrics.
| Player | Team | CF% (5v5) | Zone Start% (Off) | Position |
|---|---|---|---|---|
| Connor McDavid | Edmonton Oilers | 57.2% | 62% | Center |
| Nathan MacKinnon | Colorado Avalanche | 55.8% | 59% | Center |
| Nicklas Backstrom | Washington Capitals | 55.1% | 55% | Center |
| Mikko Rantanen | Colorado Avalanche | 55.5% | 58% | Right Wing |
| Adam Henrique | Anaheim Ducks | 44.8% | 38% | Center (defensive) |
What is a good Corsi For% in the NHL?
Ice Hockey Corsi 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.
What is the difference between Corsi and Fenwick?
In the context of Ice Hockey Corsi, 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 Corsi replace plus/minus?
In the context of Ice Hockey Corsi, 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 does zone start affect Corsi?
In the context of Ice Hockey Corsi, 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 score effects in hockey analytics?
In the context of Ice Hockey Corsi, 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.
Is Corsi a good predictor of future wins?
A good or normal result from Ice Hockey Corsi depends heavily on the specific context — industry benchmarks, personal goals, regulatory thresholds, and the assumptions embedded in the inputs. In engineering and electrical applications, practitioners typically compare results against published reference ranges, historical performance data, or regulatory standards. Rather than viewing any single number as universally good or bad, users should interpret the output relative to their specific situation, consider the margin of error in their inputs, and compare across multiple scenarios to understand the range of plausible outcomes.
Do NHL teams actually use Corsi in decision-making?
In the context of Ice Hockey Corsi, 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.
Sfat Pro
For the most accurate player Corsi assessment, filter to 5v5 situations only, apply zone-start adjustment using the formula: Adjusted CF% = CF% - (0.5 x (OZ_starts% - 50%)), and use a minimum of 500 even-strength minutes in the sample. This removes most of the confounding variables and gives a much cleaner picture of possession contribution.
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The Edmonton Oilers, despite having Connor McDavid — arguably the best player in the world — have historically struggled with team Corsi numbers because McDavid's individual brilliance masked poor possession from supporting lines. This illustrates the paradox that a single elite player's Corsi can look excellent while the team's overall possession is mediocre.