What is Ice Hockey PDO Calculator?
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PDO (named after the Oilers fan blogger who popularized it, going by the handle 'PDO' online) is hockey's most important luck indicator, measuring the combination of a team's or player's on-ice save percentage and shooting percentage at even strength. The foundational insight is that save percentage and shooting percentage both revert toward league average over large samples — neither can be sustainably extreme for long periods. Therefore, PDO values far from 100 (the league average, defined as 100 times the sum of on-ice save% and on-ice shooting%) indicate unsustainable performance, either positively or negatively. A team with a PDO of 105 has had an extraordinary combination of hot goaltending and high shooting efficiency — but this will likely regress. Sidney Crosby's 2012-13 lockout-shortened season showed a PDO of 107, meaning Pittsburgh's goalie saved at an above-average rate and Crosby's line shot at above-average efficiency — beautiful to watch, but partly unsustainable. Conversely, a PDO of 95 signals a team has been unlucky (poor goaltending and/or terrible shooting luck) and is likely better than their record suggests. Analytically, PDO is used to identify teams that will improve (low PDO) or regress (high PDO) in coming months. The Chicago Blackhawks analytics revolution of the early 2010s used PDO-based analysis to identify undervalued players whose PDO was depressed by bad luck rather than poor skill. Limitations include that truly elite goaltenders can sustain slightly above-average save percentages, and truly elite shooters can sustain slightly above-average shooting percentages — so PDO of ~101-103 for a team with McDavid or Crosby may be legitimately sustainable, not purely lucky.
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Formula
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PDO = (On-Ice Save% + On-Ice Shooting%) x 100. On-Ice Save% = Goals saved / Shots on goal against (while player is on ice). On-Ice Shooting% = Goals scored / Shots on goal for (while player is on ice). League average PDO = 100 (since average SV% + average SH% ≈ 1.00 by definition). Example: Player's team saves 91.5% of shots against and scores on 8.5% of shots for while he is on ice. PDO = (0.915 + 0.085) x 100 = 100.0 (exactly average). If SV%=93.0% and SH%=10.5%: PDO = 103.5 — significantly lucky.Variable Legend
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| Symbol | Name | Unit | Description |
|---|---|---|---|
| PDO | PDO (named after blogger Brian King) | decimal (typically 0.900-1.100) | Sum of on-ice shooting percentage and on-ice save percentage; a measure of puck luck that regresses toward 1.000 over time |
| Sh% | On-ice shooting percentage | percentage (%) | Percentage of shots on goal by the player's team that resulted in goals while the player was on ice |
| Sv% | On-ice save percentage | percentage (%) | Percentage of opponent shots on goal that were saved by the goaltender while the player was on ice |
| GF | Goals for (on-ice) | count | Goals scored by the player's team while the player was on ice |
| GA | Goals against (on-ice) | count | Goals scored by the opponent while the player was on ice |
How to Ice Hockey PDO Calculator
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- 1Identify all even-strength minutes the player was on the ice during the analysis period.
- 2Calculate on-ice shooting percentage: divide goals scored by player's team (while player was on ice) by shots on goal by player's team (while player was on ice).
- 3Calculate on-ice save percentage: divide saves by player's goaltender (while player was on ice) by shots on goal by opponent (while player was on ice).
- 4Sum the two percentages and multiply by 100 to get PDO.
- 5Compare against the league average of 100 — values above 101.5 or below 98.5 are considered meaningful deviations.
- 6Apply a minimum sample threshold (usually 500+ even-strength minutes) before drawing regression conclusions.
- 7Use PDO to forecast whether the player's or team's goal differential is likely to improve or worsen in subsequent games.
Worked Examples
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PDO of 104.7 with only 350 minutes of sample is almost certainly not sustainable; this team's goal differential will likely worsen toward their underlying Corsi numbers.
A player with 95.9 PDO over 600 minutes is almost certainly better than their goal numbers suggest — both components are suppressed below what skill alone can explain.
McDavid's sustained PDO slightly above 100 is partly legitimate since his shooting skill and playmaking genuinely elevate on-ice shooting percentages beyond luck.
A team with excellent Corsi (53.1%) but low PDO (97.2) is generating the right chances but not finishing or getting goaltending luck — a strong buy indicator for remaining schedule.
Real-World Applications
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Professionals in engineering and electrical use Ice Hockey Pdo 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 Pdo 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 Pdo 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 Pdo 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.
Special Cases
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Goaltenders who play for high-PDO teams can have their individual save
Goaltenders who play for high-PDO teams can have their individual save percentage inflated by defense quality, making it difficult to separate goaltender skill from PDO luck at the individual level.
Expansion teams in early seasons often show PDO extremes due to smaller
Expansion teams in early seasons often show PDO extremes due to smaller samples, making regression predictions less reliable until at least 300+ team even-strength minutes accumulate.
Players who are consistently sheltered (deployed in offensive zone against weak
Players who are consistently sheltered (deployed in offensive zone against weak competition) may sustain artificially elevated PDO for longer periods than players in tougher deployment.
NHL Team PDO Ranges and Outcomes — 2022-23 Season
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| PDO Range | Typical Record | Sustainability | Action | Expected Direction |
|---|---|---|---|---|
| 104+ | Excellent but lucky | Very Low | Trade sell window | Strong regression |
| 102-104 | Good, partly lucky | Low | Monitor closely | Moderate regression |
| 99-102 | Reflects true skill | High | Steady state | Stable |
| 97-99 | Below record quality | Low | Buy opportunity | Moderate improvement |
| <97 | Unlucky record | Very Low | Strong buy | Strong improvement |
Frequently Asked Questions
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What is the PDO regression timeline?
Research shows PDO typically regresses significantly over 30-40 game windows. A team with PDO above 103 in the first 20 games will most likely show 100-101 PDO in games 21-82. The regression is faster for shooting percentage (30 games) than for goaltending (50 games, since goaltender skill has more persistence).
How do NHL teams use PDO?
Analytics departments track PDO to identify teams that are better or worse than their record suggests. Teams in the trade market use low-PDO analysis to find undervalued players to acquire, and identify high-PDO teams willing to sell at peak value. This is analogous to buying low and selling high on the stock market.
What is a good PDO score in ice hockey?
A good PDO score in ice hockey is typically considered to be around 1000 or higher, with the average PDO score being 1000. This means that a team's on-ice save percentage and shooting percentage at even strength are balanced, indicating a stable performance. For example, if a team has an on-ice save percentage of 92% and a shooting percentage of 8%, their PDO score would be 1000 (0.92 + 0.08 = 1.00 or 1000).
How does PDO affect a team's winning percentage?
PDO has a significant impact on a team's winning percentage, as it measures the combination of a team's on-ice save percentage and shooting percentage at even strength. A high PDO score indicates that a team is getting lucky and is likely to regress to the mean, while a low PDO score indicates that a team is due for an improvement. For instance, a team with a PDO score of 1050 is likely to have a higher winning percentage than a team with a PDO score of 950, assuming all other factors are equal.
Can PDO be used to evaluate individual player performance?
Yes, PDO can be used to evaluate individual player performance, particularly in terms of their on-ice shooting and save percentage. For example, a player with a high PDO score may be getting lucky with their shooting percentage, while a player with a low PDO score may be due for an improvement. The formula for individual PDO is the same as for teams: on-ice save percentage + on-ice shooting percentage, and a score of 1000 is considered average. By tracking a player's PDO over time, coaches and analysts can gain insights into their performance and make informed decisions about their lineup and strategy.
Common Mistakes to Avoid
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- !Using PDO from fewer than 300 even-strength minutes — with small samples, PDO fluctuates wildly and produces misleading regression predictions.
- !Assuming low PDO always means a team will improve — if a team's Corsi numbers are also poor, their underlying shot generation is genuinely bad and no amount of PDO regression will save them.
- !Treating PDO as a skill metric — it is primarily a luck indicator. Players with career PDO consistently far from 100 are extremely rare exceptions (elite shooters or elite goaltenders), not the norm.
Pro Tip
Use PDO in combination with Corsi to build a 2x2 analysis matrix: High Corsi + Low PDO = Strong buy (unlucky good team); Low Corsi + High PDO = Strong sell (lucky bad team); High Corsi + High PDO = Sell now; Low Corsi + Low PDO = Avoid. This framework guided the Chicago Blackhawks and Carolina Hurricanes analytics departments to multiple playoff runs and Cup contention.
Did you know?
The 2013-14 Colorado Avalanche were one of the most famous PDO-driven success stories: they started the season at over 103 PDO and finished with the best record in the Western Conference. Their Corsi was mediocre (~49%), and the following season they crashed out of playoff contention — a near-perfect case study in PDO regression that analytics blogs had predicted months in advance.
References
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