What Is Face-Off Win Percentage in Hockey?

Face-off win percentage represents the proportion of faceoffs won by a player or team, calculated as a percentage of total faceoff attempts. In hockey analytics, this metric is abbreviated as FO%, FOW%, or FOPCT depending on the source. While it sounds straightforward, understanding what makes a faceoff "won" and why this metric matters requires deeper exploration.

A faceoff is a restart mechanism in hockey where an official drops the puck between two opposing players (typically centers) to resume play after a stoppage. The team that gains possession of the puck immediately after the drop is credited with winning the faceoff. Importantly, winning a faceoff is not about who touches the puck first with their stick—it's about which team controls the puck in the seconds immediately following the drop.

Face-off win percentage directly influences a team's ability to establish controlled possession at critical moments. When a team wins a faceoff in the offensive zone, they gain an immediate advantage to set up plays and generate scoring chances. Conversely, winning draws in the defensive zone can prevent the opposing team from establishing offensive pressure. This positional advantage is why faceoff performance has long been considered important in hockey strategy and why it remains a popular metric among casual fans, bettors, and analysts.

How Is Face-Off Win Percentage Calculated?

The calculation of face-off win percentage is mathematically simple but contextually nuanced. The basic formula is:

Face-Off Win Percentage = (Faceoffs Won ÷ Total Faceoffs Taken) × 100

For example, if a player wins 120 faceoffs out of 200 attempts, their face-off win percentage is 60% (120 ÷ 200 × 100). This metric applies equally to individual players and entire teams—the calculation method remains consistent regardless of scale.

What Counts as a Faceoff Win?

Understanding what constitutes a faceoff "win" is critical because it differs from casual perceptions. A faceoff is won by the team that gains possession of the puck following the official's drop, not necessarily by the center who touches it first with their stick. This distinction is important because the puck can be directed to a teammate, and that team still receives credit for winning the draw even if the center didn't directly control it.

For example, in the 2017 overtime scenario documented in academic hockey research, Los Angeles Kings center Anze Kopitar won a crucial faceoff by cleanly directing the puck to teammate Tyler Toffoli, who immediately scored. Kopitar was credited with a faceoff win—and a valuable one at that—despite having a poor 34.8% win percentage on the night. This illustrates that not all faceoff wins are equal in terms of value to the team.

Conversely, a faceoff is lost when the opposing team gains possession following the drop. If a loose puck battle ensues and the opposing team ultimately controls it, that's recorded as a loss for the original team's center.

Minimum Thresholds and Statistical Reliability

Official NHL statistics use a minimum threshold of 3.5 faceoffs per team game to qualify a player for faceoff win percentage rankings. This threshold exists because small sample sizes can be misleading. A player who takes only 10 faceoffs in a season and wins 8 of them (80%) shouldn't be ranked above a player with 500 attempts and a 60% win rate, as the first player's performance could easily be statistical variance.

The 3.5 minimum ensures that qualified players have taken at least 280 faceoffs over a typical 82-game season, providing a more reliable statistical picture. This is why you'll often see "qualified faceoff leaders" on stat sites—the designation ensures the data is meaningful.

Where Do Face-Offs Occur and Why Location Matters?

One of the most overlooked aspects of face-off analysis is that location dramatically affects value. A faceoff in the offensive zone is not equivalent to one in the defensive zone, and this contextual difference is where sophisticated hockey analysis diverges from simple percentage-based thinking.

The Five Key Faceoff Zones

Hockey rinks are divided into three zones: offensive, neutral, and defensive. Additionally, faceoffs occur at specific circles and locations within each zone:

• Offensive Zone Faceoffs (left/right circles, slot): Most valuable for the attacking team. Winning here provides immediate setup for scoring chances. Elite centers often have higher win percentages in the offensive zone.

• Defensive Zone Faceoffs (left/right circles, near the goal line): Critical for preventing scoring chances. Winning a defensive zone faceoff can stop momentum and give the team a chance to clear the puck.

• Neutral Zone Faceoffs (center ice, near the blue line): Less impactful than zone-specific draws. These are often used to restart play after icing calls or other stoppages.

• Slot/Dangerous Area Faceoffs: Faceoffs directly in front of the goal create immediate high-danger situations. These are relatively rare but extremely valuable.

Research published in academic papers on hockey analytics reveals that the directionality of a faceoff win matters significantly. A player who wins the puck and directs it forward into the attacking zone creates more value than one who wins it but has it go backward. Similarly, winning the puck to the inside of the ice (toward the middle) in the offensive zone is more valuable than winning it to the outside (toward the boards).

Strong Side vs. Weak Side Performance

Players have natural strengths and weaknesses depending on which side of the ice they're taking the faceoff. A strong-side faceoff occurs when a player's handedness aligns with the side of the boards—for example, a right-handed player taking a faceoff on the right side. A weak-side faceoff is the opposite.

Most NHL players win a higher percentage of faceoffs on their strong side, typically 2–5% higher. This is because they have better stick control, leverage, and technique on their dominant side. However, elite centers like Nathan MacKinnon have been known to perform equally well on both sides, suggesting that skill and experience can overcome the natural advantage.

Teams increasingly deploy centers on their strong sides when possible, which is why you'll see different centers taking faceoffs depending on the game situation and zone. This strategic deployment is why faceoff win percentage must be contextualized—a center with a 55% win rate on their strong side might be performing at an elite level, while the same percentage on their weak side would be exceptional.

What Counts as a "Good" Face-Off Win Percentage?

Benchmarking faceoff performance requires understanding league averages and position-specific standards.

NHL Benchmarks and League Averages

The NHL league average for faceoff win percentage hovers around 50%, which makes intuitive sense—if every team wins exactly half their faceoffs, the average is 50%. However, individual player performance varies significantly:

• 50–52%: Above average for an NHL player
• 52–55%: Well above average; indicates strong technical skill
• 55–60%: Elite performance; among the top 5–10% of the league
• 60%+: Exceptional; typically reserved for 1–3 players per season

As of the 2025-26 NHL season, Claude Giroux leads the league with a 62.6% faceoff win percentage, while other elite centers like Nico Hischier and Sidney Crosby maintain percentages in the 55–60% range. These elite performers typically take 500+ faceoffs per season, so their percentages are statistically reliable.

It's important to note that faceoff win percentage alone doesn't determine a player's overall value. Many successful teams have centers with below-average faceoff percentages but excellent overall possession metrics (Corsi, expected goals). Conversely, some players with high faceoff win percentages don't translate that into team success.

Position-Specific Standards

Centers are the primary faceoff takers and have the most extensive faceoff statistics tracked. For centers, the benchmarks above apply directly.

Wings occasionally take faceoffs, particularly on power plays or in specific game situations. When wings take faceoffs, they typically have lower win percentages than centers, simply because they're less specialized in this skill. A wing with a 48% faceoff win percentage might be performing acceptably, while the same percentage for a center would be below average.

Defensemen rarely take faceoffs but may do so in emergency situations or during power plays. Their faceoff statistics are typically not tracked or reported due to small sample sizes.

Does Face-Off Win Percentage Actually Predict Winning Games?

This is where the analysis becomes controversial and where research diverges sharply from conventional wisdom. For decades, hockey culture has treated faceoff win percentage as a crucial indicator of team success. However, modern statistical analysis reveals a more nuanced reality.

What the Research Shows

A comprehensive analysis published in Sports Illustrated examined 910 single-game instances where a team won 60% or more of faceoffs during the 2012–2014 seasons. The result: those teams won only 52.3% of their games. In more recent data (2014 onward), teams winning 60%+ of draws won only 50.86% of their games—essentially a coin flip.

This finding is striking because it suggests that dominating faceoffs provides only a marginal advantage in actual game outcomes. To put this in perspective, no team in NHL history with a winning percentage of .523 or worse has reached the Stanley Cup Playoffs, yet many successful teams have faceoff win percentages below 50%.

The Pittsburgh Penguins, winners of 267 games since 2010 (the most in the league), have lost more faceoffs than they've won over that span. The New York Rangers, fifth in points-percentage since 2010, have one of the worst faceoff win percentages in the league at 48.6%. Meanwhile, the Boston Bruins and San Jose Sharks—both in the top 10 for faceoff wins since 2010—rank only seventh and eighth in overall points-percentage.

This data suggests that while faceoffs might have some impact, they're far less predictive of success than other metrics like shot attempts (Corsi), expected goals (xG), or overall possession metrics.

The "Not All Wins Are Created Equal" Problem

The weakness of raw faceoff win percentage as a predictive metric lies in its inability to capture quality. Academic research from SPORTLOGiQ, published in 2019, analyzed over 71,000 faceoffs and subsequent plays from the 2017-18 NHL season. The key finding: not all faceoff wins are equal.

The research identified several dimensions of faceoff quality:

1. Cleanliness: A "clean" win is one where the center directly controls the puck and passes it to a teammate in a controlled manner. A "dirty" win involves a loose puck battle where possession is contested.

2. Directionality: The direction the puck is won toward matters significantly. Winning the puck forward into the attacking zone is more valuable than winning it backward. Similarly, winning it to high-value areas of the ice creates more scoring chances.

3. Subsequent Play: The most important metric isn't whether you won the faceoff—it's whether that win led to a shot, a zone entry, or a dangerous play. A faceoff win that results in the puck being turned over 10 seconds later has minimal value.

For example, Anze Kopitar's game-winning faceoff in overtime was statistically a win, but it was also a clean win (direct to teammate), directionally optimal (to high-danger area), and immediately resulted in a shot. His 34.8% win percentage on the night didn't capture the true value of that draw.

This research suggests that bettors and analysts focusing solely on season-long faceoff win percentage are missing crucial context. A player or team with a 52% win percentage that consists mostly of clean, directional wins in high-value areas might be far more effective than a 58% win rate with many contested, backward-directed wins.

Common Misconceptions About Faceoff Importance

The hockey community has perpetuated several myths about faceoff importance:

Myth 1: "You can't win games without winning faceoffs."
Reality: Many successful teams win games despite losing faceoffs. The correlation is weak enough that other factors (goaltending, shot quality, defensive play) matter far more.

Myth 2: "A high faceoff win percentage guarantees possession advantage."
Reality: Possession advantage depends on directionality, cleanness, and subsequent plays—not raw percentage. A 50% win rate with quality wins can be more valuable than 55% with poor-quality wins.

Myth 3: "Faceoff performance is the best predictor of team success."
Reality: Metrics like Corsi (shot attempts), expected goals (xG), and goaltending save percentage are far more predictive of wins than faceoff win percentage.

Myth 4: "All faceoff locations are equally important."
Reality: Offensive zone faceoffs are significantly more valuable than defensive zone draws. A team dominating offensive zone draws while losing defensive zone draws might have a better overall position than the opposite.

Myth 5: "Faceoff specialists are always valuable."
Reality: A center who wins 58% of faceoffs but has poor possession metrics (Corsi) and doesn't create scoring chances may be less valuable than a center with a 50% faceoff win rate who excels in other areas.

Faceoff win percentage does matter in specific situations, particularly in overtime (where 3-on-3 play makes possession critical), on power plays (where setup is crucial), and in crucial late-game moments. However, as a season-long predictor or general indicator of team quality, it's significantly overvalued by casual fans and bettors.

Face-Off Win Percentage vs. Other Hockey Metrics

To understand where faceoff win percentage fits in the broader analytics landscape, it's useful to compare it to other commonly cited metrics.

Faceoff % vs. Corsi and Fenwick

Corsi and Fenwick are possession metrics based on shot attempts, while faceoff win percentage is based on puck restarts. They measure different things and serve different purposes:

Corsi measures the percentage of shot attempts (shots on goal, missed shots, and blocked shots) a team generates while controlling for the opponent's attempts. A team with a 52% Corsi has a slight possession advantage. Corsi is highly predictive of long-term success because it captures overall puck control and play direction.

Fenwick is similar to Corsi but excludes blocked shots, which some analysts argue provides a cleaner picture of uncontested possession.

Expected Goals (xG) takes shot analysis further by assigning probability values to each shot based on location and type. A shot from the slot has a higher xG value than a shot from the point.

The key distinction: Faceoff win percentage tells you who won the restart, but Corsi, Fenwick, and xG tell you what happened after. A team can win 55% of faceoffs but generate fewer quality shots and scoring chances than a team winning 48% of draws. This is why advanced analysts prioritize Corsi and xG over faceoff win percentage.

Faceoff Differential as an Advanced Metric

An improvement over raw faceoff win percentage is faceoff differential (also called FO +/-), calculated as:

Faceoff Differential = Faceoffs Won – Faceoffs Lost

This metric accounts for both sides of the draw and can be more meaningful than win percentage. A team with a +50 faceoff differential over a season (50 more wins than losses) has a clear advantage in puck restarts. However, faceoff differential still suffers from the same weakness as win percentage—it doesn't capture quality or context.

Research suggests that it takes approximately 75 faceoff wins above replacement level to gain a +1 goal differential over a season. This underscores how marginal the impact of faceoff dominance actually is compared to other factors.

How to Use Face-Off Win Percentage for Hockey Betting

For bettors, understanding when and how to use faceoff statistics is crucial to avoiding overvaluation of this metric.

When Faceoff % Matters in Betting

Faceoff win percentage becomes more relevant in specific betting scenarios:

Overtime betting is where faceoff statistics gain real value. In 3-on-3 overtime, the team that wins the faceoff and converts it into possession has a significant advantage in generating a scoring chance. If one team has an elite faceoff specialist and the other doesn't, this becomes a meaningful edge for bettors to exploit.

Power play performance is another area where faceoff statistics matter. Teams that win offensive zone faceoffs on the power play set up their formation and can generate more dangerous chances. A team with an elite faceoff specialist on the power play might have an edge in power play goal probability.

Matchup-specific analysis is valuable when comparing specific centers. If a team's elite faceoff specialist (55%+ win rate) is facing a weaker faceoff taker, this could provide a slight edge in controlling play, particularly in crucial late-game moments.

Red Flags: When to Ignore Faceoff Percentage

Conversely, bettors should be skeptical of faceoff statistics in many scenarios:

• Small sample sizes: A player with 50 faceoffs and a 58% win rate in a given month might be due for regression. Season-long data is more reliable.

• Isolated stat analysis: Never bet based solely on faceoff win percentage. Combine it with Corsi, xG, goaltending metrics, and team context.

• Overweighting against other factors: A team with a 48% faceoff win percentage but a 52% Corsi and strong goaltending might be a better bet than one with 54% faceoff wins and poor underlying metrics.

• Single-game unpredictability: Even elite faceoff specialists have off nights. Kopitar's example illustrates that a single game's faceoff performance can be misleading.

• Season-long records: Historical data shows that faceoff win percentage has minimal predictive power for season outcomes. Bettors should rely on more predictive metrics.

The bottom line for bettors: Use faceoff statistics as one data point among many, not as a primary predictor. The teams and bettors who outperform the market typically focus on metrics with stronger correlations to outcomes, like expected goals, goaltending performance, and team possession metrics.

Historical Context: How the Faceoff Stat Evolved

Understanding the history of faceoff statistics provides context for why this metric remains popular despite its limitations.

Origins of Faceoff Tracking

Faceoff statistics were first formally tracked in the NHL during the 1997-98 season. Before this, faceoff performance was monitored informally by teams and coaches but wasn't part of the official statistical record. This relatively recent addition to hockey statistics explains why faceoff lore was built on anecdotal evidence and coaching intuition rather than rigorous data.

Early tracking was done manually by official scorers at each game, which introduced human error and inconsistency. Different scorers might interpret borderline faceoff outcomes differently, leading to variations in how faceoff wins and losses were recorded.

Modern Analytics Revolution

The analytics revolution in hockey, which accelerated in the 2010s, brought scientific scrutiny to faceoff statistics. Early analysts assumed that faceoff win percentage would be a strong predictor of success, but data quickly revealed otherwise. Academic papers and independent research by organizations like SPORTLOGiQ, Evolving Hockey, and others demonstrated that:

1. Raw faceoff win percentage has weak correlation to wins
2. Context (zone, directionality, cleanliness) matters more than percentage
3. Other metrics (Corsi, xG) are far more predictive

This research has gradually shifted how sophisticated analysts and teams view faceoff statistics. Modern NHL teams still track faceoff performance and deploy centers strategically, but they no longer treat faceoff win percentage as a primary success indicator.

The evolution reflects a broader pattern in sports analytics: metrics that seem intuitively important often prove less predictive than expected once examined rigorously. This is why the hockey community has gradually shifted focus from faceoff win percentage to more nuanced metrics that capture possession quality and shot danger.

Frequently Asked Questions

Q: What is a good faceoff win percentage in the NHL?

A: A faceoff win percentage above 52% is generally considered above average, while 55%+ is elite. However, context matters significantly. A 50% win rate in the offensive zone may be more valuable than a 60% rate in the defensive zone. Additionally, the quality of wins—whether they're clean, directional, and lead to subsequent play—matters more than raw percentage.

Q: How is a faceoff won or lost?

A: A faceoff is won by the team that gains possession of the puck first after the official drops it. It's not about who touches the puck with their stick first, but which team controls the puck in the immediate aftermath of the drop. The team that secures possession is credited with the win, while the other team records a loss.

Q: Does faceoff win percentage predict game outcomes?

A: Research shows a weak correlation. Teams winning 60%+ of faceoffs win only about 52% of their games—barely better than a coin flip. Other metrics like expected goals (xG), Corsi, and goaltending save percentage are far more predictive of game outcomes. Faceoff win percentage matters most in specific situations like overtime or power plays.

Q: Why do some players perform better on their strong side in faceoffs?

A: Players typically have better stick control, leverage, and technique on their dominant side, allowing them to win more draws. A right-handed player will generally perform better on the right side, while a left-handed player excels on the left. However, elite centers can perform equally well on both sides through skill development and experience.

Q: What's the difference between faceoff win percentage and faceoff differential?

A: Faceoff win percentage is wins ÷ total attempts × 100. Faceoff differential is wins minus losses, which accounts for both sides of the draw. Differential can be a more nuanced metric because it shows net faceoff advantage, though both metrics have limitations in predicting overall team success.

Q: Are faceoffs important in overtime hockey?

A: Yes. In overtime, particularly 3-on-3 play, faceoff location becomes critical. Winning the faceoff in the attacking zone provides an immediate possession advantage and opportunity for a scoring chance. Faceoff win percentage is one of the few scenarios where it's genuinely predictive of near-term outcomes.

Q: How do bettors use faceoff statistics?

A: Sophisticated bettors use faceoff metrics as one of many data points, focusing on matchup-specific advantages (elite center vs. weaker opponent) and situational context (overtime, power plays) rather than season-long percentages. They avoid overweighting faceoff statistics and prioritize more predictive metrics like expected goals and team possession rates.

Q: What's the relationship between faceoff wins and scoring?

A: The relationship is indirect and context-dependent. Winning a faceoff provides an opportunity for possession, but that possession must be converted into a scoring chance. Research shows it takes approximately 75 faceoff wins above replacement level to generate a +1 goal differential—a marginal impact compared to other factors.

Related Terms

• Corsi — Shot attempt metric measuring overall possession quality
• Fenwick — Unblocked shot attempt metric; refinement of Corsi
• Possession — Overall puck control and territory advantage
• Expected Goals (xG) — Probability-weighted measure of shot quality
• Faceoff Differential — Wins minus losses in faceoff battles