Fact-checked by Grok 2 weeks ago

On-base plus slugging

On-base plus slugging (OPS) is a sabermetric statistic used in to evaluate a player's offensive performance by combining their (OBP), which measures how frequently a batter reaches base, with their (SLG), which measures the average number of bases per at-bat. The statistic is calculated simply as OPS = OBP + SLG, providing a single value that approximates a hitter's overall run-producing ability without complex adjustments. Invented by statistician Pete Palmer in the late 1970s, OPS was first introduced as an official statistic in 1979 alongside , and it gained wider prominence through Palmer's work with John Thorn in the 1984 book The Hidden Game of Baseball, where it was presented as a straightforward measure of batting productivity. Palmer developed OPS as a simple yet effective way to balance the importance of reaching base and extra-base power, recognizing that these two components contribute roughly equally to scoring runs in . OPS has become one of the most widely used advanced metrics in analysis due to its strong correlation with team run production and ease of interpretation, often serving as a quick benchmark for player value in , fantasy , and media evaluations. League-average OPS typically hovers around .700 to .750, with values above .800 considered strong, .900 elite, and over 1.000 exceptional for a full season. An adjusted version, OPS+, normalizes the stat for and league effects on a scale where 100 is average, allowing for cross-era and cross-venue comparisons.

Fundamentals

Definition

On-base plus slugging (OPS) is a sabermetric in that quantifies a player's offensive performance by adding their (OBP) to their (SLG), providing a single metric to assess both reaching base and hitting power. This approach unifies two fundamental aspects of hitting into one value, offering a more holistic view of a batter's contribution compared to isolated stats. OPS addresses key limitations in traditional metrics like batting average, which overlooks walks and the differential value of singles versus extra-base hits; by emphasizing OBP for plate discipline and SLG for extra bases, it better captures a hitter's ability to create scoring opportunities through both frequency and quality of contact. In modern baseball, OPS serves as a cornerstone for player evaluation in analytics-driven environments, influencing scouting reports, contract negotiations, and fantasy baseball strategies where it helps predict run production and overall value post-2000s.

Components

On-base percentage (OBP) quantifies a batter's frequency of reaching base safely per plate appearance, accounting for multiple pathways beyond hits alone. It is calculated as the sum of hits (H), bases on balls (BB), and hit by pitch (HBP) divided by the total of at-bats (AB), bases on balls (BB), hit by pitch (HBP), and sacrifice flies (SF), expressed as: \text{OBP} = \frac{\text{H} + \text{BB} + \text{HBP}}{\text{AB} + \text{BB} + \text{HBP} + \text{SF}} This metric uniquely emphasizes non-hit methods of reaching base, such as walks and hit by pitches, which contribute to offensive opportunities without requiring contact with the ball. Slugging percentage (SLG) measures a batter's power output by averaging the earned per at-bat, giving greater weight to extra-base hits that advance runners more effectively. are derived from singles (1B, counting as 1 base), doubles (2B, 2 bases), triples (3B, 3 bases), and home runs (HR, 4 bases), with the formula being total bases divided by at-bats: \text{SLG} = \frac{1\text{B} + 2 \times 2\text{B} + 3 \times 3\text{B} + 4 \times \text{HR}}{\text{AB}} SLG highlights power hitting by assigning quadruple value to home runs compared to singles, reflecting their superior impact on scoring. Together, OBP and SLG form the foundation of on-base plus slugging (OPS), which simply adds the two values to provide a combined view of a player's ability to reach and advance bases.

Calculation

Formula

On-base plus slugging (OPS) is calculated as the sum of a player's on-base percentage (OBP) and slugging percentage (SLG). The precise formula is: \text{OPS} = \text{OBP} + \text{SLG} = \frac{H + \text{BB} + \text{HBP}}{\text{AB} + \text{BB} + \text{HBP} + \text{SF}} + \frac{1\text{B} + (2 \times 2\text{B}) + (3 \times 3\text{B}) + (4 \times \text{HR})}{\text{AB}} where H denotes hits, BB is bases on balls (walks), HBP is hit by pitch, AB is at-bats, SF is sacrifice flies, 1B is singles, 2B is doubles, 3B is triples, and HR is home runs. This simple addition of OBP and SLG approximates a player's overall offensive contribution to run production by equally weighting the ability to reach base and the power to advance bases on hits, without requiring complex multiplicative adjustments that better reflect run scoring but complicate computation. In edge cases, such as when a player has zero at-bats (AB = 0), the SLG component involves division by zero and is thus undefined, rendering OPS incalculable; in practice, major league and minor league databases typically do not report OPS for such players or list it as non-applicable, differing only in qualification thresholds for leaderboards (e.g., MLB requires 3.1 plate appearances per team game, while minor leagues may use varying minimums).

Example

To illustrate the calculation of on-base plus slugging (OPS), consider the 1920 season of with the Yankees, where he recorded 458 at-bats (), 172 hits (), 36 doubles (2B), 9 triples (3B), 54 home runs (HR), 150 walks (), 3 hit-by-pitches (HBP), and 0 sacrifice flies (). First, compute (OBP), which measures how often a batter reaches base: \text{OBP} = \frac{\text{H} + \text{BB} + \text{HBP}}{\text{AB} + \text{BB} + \text{HBP} + \text{SF}} = \frac{172 + 150 + 3}{458 + 150 + 3 + 0} = \frac{325}{611} \approx 0.532. This value indicates Ruth reached base approximately 53.2% of the time he led off a . Next, calculate slugging percentage (SLG), which assesses power by weighting extra-base hits: Begin by determining (TB), where singles contribute 1 base, doubles 2, triples 3, and home runs 4. Singles equal H minus multi-hit types: 172 - 36 - 9 - 54 = 73. Thus, \text{TB} = (73 \times 1) + (36 \times 2) + (9 \times 3) + (54 \times 4) = 73 + 72 + 27 + 216 = 388, and \text{SLG} = \frac{\text{TB}}{\text{AB}} = \frac{388}{458} \approx 0.847. Finally, add the components for : 0.532 + 0.847 = 1.379. Small adjustments in performance can noticeably affect OPS; for instance, if Ruth had hit one additional home run (increasing H by 1 and TB by 4, assuming it replaced an out and did not alter other plate appearances), his revised SLG would be 392 / 458 ≈ 0.856, yielding an OPS of approximately 1.388—an increase of 0.009 that reflects amplified value from power production.

History

Origins

The origins of the components of on-base plus slugging (OPS) trace back to earlier developments in baseball statistics. On-base percentage (OBP), a key element of OPS, was pioneered in the late 1940s and early 1950s by , then general manager of the , and statistician Allan Roth, whom Rickey hired in 1947 as the major leagues' first full-time statistician. Roth's work with the Dodgers quantified how frequently batters reached base, emphasizing its importance for run production over traditional . Rickey advocated for integrating on-base ability with metrics, arguing that these better captured offensive value. In his 1954 Life magazine article "Goodbye to Some Old Ideas," Rickey proposed a for predicting runs scored: O = OBA + (Extra Base × 0.75) + , where OBA is on-base average, Extra Base is ( minus ) per at-bat (similar to later isolated ), and is runs per baserunner. This equation correlated 96.2% with team standings over 20 years of data. While not identical to , Rickey's weighted combination of on-base and measures represented an early structured approach to holistic offensive evaluation, influencing later .

Adoption

On-base plus slugging (OPS) was invented by statistician Pete Palmer in the late 1970s, finalized in 1978 as a simple addition of OBP and (SLG) to approximate run production. Palmer introduced OPS and OBP as official statistics in 1979. It gained prominence through Palmer's collaboration with John Thorn in the 1984 book The Hidden Game of Baseball, where it was presented as an effective measure of batting productivity. The statistic's adoption accelerated in the 1980s and 1990s amid the movement, as analysts promoted advanced metrics over traditional ones like (BA) and runs batted in (). The 2000s saw OPS integrated into (MLB) operations, notably in the ' data-driven approach under general manager , which valued on-base and power contributions. Michael Lewis's 2003 book Moneyball: The Art of Winning an Unfair Game popularized these strategies, raising OPS's profile in mainstream awareness. The rise of fantasy baseball in the early 2000s further embedded OPS in player evaluations. Since 2010, the analytics revolution, including MLB's launch in 2015, has reinforced 's utility alongside metrics like exit velocity and launch angle for player development and lineup decisions. Teams use OPS benchmarks, such as .800 for above-average and .900 for elite production, in trades and promotions. OPS has also been adopted internationally, with leagues like the Korean Baseball Organization (KBO) and (NPB) applying it to evaluate talent against MLB standards.

Interpretation

Scale

Interpreting OPS values requires contextual benchmarks, as the statistic's scale varies by era due to changes in equipment, strategy, and pitching dominance. In modern baseball (post-1990s), an OPS exceeding 1.000 denotes elite performance, typically reserved for top power hitters like candidates; values between 0.900 and 0.999 indicate above-average production; 0.800 to 0.899 represent solid, league-average contributions for everyday players; and below 0.700 signals below-average offense, often associated with bench roles or defensive specialists. These thresholds must be adjusted for historical eras, where offensive environments differed markedly. During the (1901–1919), league-average OPS hovered around 0.650–0.700, reflecting low-scoring games with limited power; for instance, the 1910 major league average was .644, but elite players rarely surpassed 0.900 due to softer balls and expansive parks. The (1920–1941) ushered in higher offense, with 1920 league averages reaching 0.706 overall (AL: 0.734, NL: 0.679), enabling star hitters like to post OPS over 1.000 as a new standard for excellence—Ruth's 1.379 that year dwarfed contemporaries. In the modern post-2000 period, pitching innovations and defensive shifts have deflated scoring, lowering league-average to around 0.780 in high-offense years like but dipping to 0.712 in amid increased and strikeouts. This era-specific deflation means a 0.900 today equates to MVP-caliber impact, comparable to 1.000+ in the 1920s high-offense context. also correlates strongly with run creation; for example, a 0.750 league aligns with about 0.120 runs per , providing a practical of offensive value.

Comparisons

OPS provides a marked improvement over traditional batting metrics like batting average (BA) and runs batted in (RBI). Batting average solely accounts for hits relative to at-bats, disregarding walks, hit-by-pitches, and the power of extra-base hits, which limits its ability to capture overall offensive contribution. In contrast, RBI depends heavily on contextual opportunities created by teammates, such as runners on base, making it unreliable for evaluating individual skill. OPS addresses these shortcomings by combining on-base and power elements into a single, player-focused measure. Relative to its own components, (OBP) and (SLG), OPS offers a fuller assessment of a hitter's value. OBP emphasizes reaching base but ignores power output, potentially underrating players who excel in extra-base hits. SLG highlights power through per at-bat but excludes non-hit ways to reach base like walks, overlooking patient approaches that advance runners. By summing these, OPS balances the two without the gaps inherent in using either alone. When evaluated against advanced sabermetric tools like weighted on-base average () and runs created (), OPS serves as a solid approximation of run production but reveals notable flaws. It underweights walks because OBP uses plate appearances as the denominator while SLG uses at-bats, creating an imbalance in the summation; additionally, OPS overvalues singles by treating all hits proportionally in SLG, unlike linear weights that assign run values based on event impact. and , grounded in linear weights, more accurately estimate runs by weighting outcomes (e.g., home runs higher than singles) according to their contribution to scoring, yielding stronger correlations with team runs—such as 's superior predictive power over OPS in run estimator comparisons. OPS differs from isolated power (ISO), a dedicated to raw power measurement. ISO, calculated as SLG minus BA, isolates extra bases from doubles, triples, and home runs per at-bat, excluding singles and on-base events to focus purely on slugging strength. While ISO excels for pinpointing power hitters without dilution from contact skills, OPS incorporates OBP for a broader offensive profile, making it preferable for holistic evaluations but less precise for power-specific analysis. Situational applications of OPS, particularly clutch (high-leverage) versus non-clutch contexts, highlight performance variability under pressure. Clutch OPS measures output in high-leverage situations like late innings with the score close or runners in scoring position, compared to non-clutch OPS in low-stakes scenarios; while such splits can suggest better timing or power in critical moments, analyses indicate these differences largely stem from small-sample randomness rather than repeatable skill, with year-to-year correlations near zero.

Variants

OPS+

OPS+ is an advanced sabermetric statistic that adjusts a player's (OPS) for league-wide offensive levels and the specific effects of their home , enabling fairer comparisons across players, teams, eras, and venues. Unlike raw , which can be inflated or deflated by external factors, OPS+ provides a normalized measure where 100 represents the league average for a given season, scores above 100 indicate superior performance relative to that average, and scores below 100 signify subpar output. This adjustment is particularly valuable in eras with varying offensive environments, such as the low-scoring dead-ball period (pre-1920), where unadjusted stats might undervalue hitters due to widespread pitching dominance and smaller . The calculation of OPS+ begins with the core OPS components—on-base percentage (OBP) and slugging percentage (SLG)—then scales them against park-adjusted league averages. The formula is: \text{OPS+} = 100 \times \left( \frac{\text{OBP}}{\text{lgOBP}^*} + \frac{\text{SLG}}{\text{lgSLG}^*} - 1 \right) where \text{lgOBP}^* and \text{lgSLG}^* are the league-average OBP and SLG, respectively, modified to reflect the run-scoring environment of the player's home ballpark (e.g., via a park factor derived from historical home/away performance splits). Park factors quantify how a stadium influences offense; for instance, Coors Field in Denver typically has a factor exceeding 110 due to high altitude reducing air resistance on batted balls, boosting SLG by promoting more home runs and extra-base hits. If a player's home park suppresses offense (factor below 100), their lgOBP* and lgSLG* are lowered accordingly, crediting them more for their raw production. This methodology ensures OPS+ isolates individual skill from environmental biases. The statistic originated in sabermetric research during the 1980s, building on the foundational work of Pete Palmer, who introduced OPS as "Production+" in The Hidden Game of Baseball (1984); OPS+ extended this by incorporating league and park normalizations to enhance cross-era comparability. In modern applications, park factors for OPS+ increasingly integrate data—capturing metrics like exit velocity, launch angle, and sprint speed—to refine adjustments for how ballparks affect specific batted-ball outcomes, providing more granular accuracy than traditional run-based models. For example, reveals that parks like in suppress home runs by about 20-30% due to deep dimensions and effects, directly influencing OPS+ computations for players based there.

OPS+ Leaders

The single-season OPS+ leaders showcase peak offensive dominance, adjusted for , league, and era factors to allow fair comparisons across history. These marks reflect extraordinary hitting relative to contemporaries, with the highest values often from the Negro Leagues due to limited data reconstruction but high-impact performances in segregated play. These statistics include Negro Leagues data, officially integrated into MLB records on May 29, 2024, following MLB's recognition of those leagues as major leagues. holds the top two spots, underscoring the talent in the Negro Leagues during the 1930s and 1940s. Barry Bonds dominates the modern MLB era with three of the top five spots from 2001 to 2004, a period marked by his record-setting power and on-base skills amid debates over performance-enhancing substances. His 2004 season set the MLB record for highest OPS+ at 263, achieved in just 617 plate appearances while battling injuries. Babe Ruth's entries from the early (post-1919) revolutionized hitting, with his 255 in 1920 coming in the season he hit 54 home runs, shattering previous records and shifting baseball's strategic focus toward power. Other notable peaks include Mule Suttles' 253 in 1930 for the St. Louis Stars in the Negro Leagues, a dead-ball era outlier in power hitting despite the style's emphasis on contact. Earlier dead-ball examples, like Ty Cobb's 168 in 1911, stand out for their era but fall short of live-ball or Negro Leagues benchmarks due to lower overall scoring environments. Negro Leagues stars like Gibson exemplify incomplete historical records, with estimates for his 1943 season placing it as the all-time high at 281 based on verified games and statistical modeling.
RankPlayerOPS+YearLeaguePANotes
12811943Negro Leagues302; highest all-time, post-integration era outlier in segregated play.
22731937Negro Leagues183; limited PA but dominant in high-scoring Negro National League.
32682002MLB (NL)612 Giants; record 68 HR, .436 OBP.
42632004MLB (NL)617 Giants; MLB single-season record for OPS+ (1.422 OPS).
52592001MLB (NL)664 Giants; 73 HR (MLB single-season record).
62551920MLB (AL)617 Yankees; 54 HR, ushered in live-ball power surge.
72531930Negro Leagues197St. Louis Stars; power hitter in contact-oriented era.
82391923MLB (AL)697 Yankees; .393 BA, led AL in HR (41) and RBI (130).
92391921MLB (AL)693 Yankees; 59 HR, early dominance post-dead-ball.
102351941MLB (AL)684Boston Red Sox; .406 BA, last .400 season in .

Leaders

OPS Leaders

The all-time career leaders in on-base plus slugging (OPS) among players with at least 3,000 plate appearances highlight the exceptional hitters who combined high on-base percentages with significant power, predominantly from the starting in 1920, when rule changes and equipment improvements boosted offensive production. This era's stars, such as and , dominate the rankings due to the favorable hitting conditions, including the use of a more resilient that traveled farther upon contact. The integration of Negro Leagues statistics since 2020 has elevated players like , , and into the top tier, reflecting their dominance in segregated professional . The following table presents the top 10 career OPS leaders, showcasing unadjusted historical performance across eras (as of the end of the 2025 season):
RankPlayerPA
11.163610,628
21.11559,792
31.07989,665
41.06393,885
51.051212,606
61.03769,677
71.03254,279
81.02993,623
91.02825,002
101.01696,098
These figures are drawn from official MLB records, with the minimum 3,000 plate appearances qualifier ensuring focus on sustained careers rather than brief peaks. In more recent decades, modern players have cracked the upper echelons despite pitching-dominant eras and advanced defensive shifts; for instance, entered the top 10 all-time with a career of 1.028 by the end of the 2025 season. remains in the top 100 all-time with a career of .976 by the end of the 2025 season, underscoring his elite blend of contact, power, and plate discipline. Positionally, the rankings reveal challenges at premium defensive spots: among shortstops, holds the highest career at .963 over 12,427 plate appearances (primarily at for the first half of his career), far surpassing traditional greats like (.863). This positional lens highlights how offensive output varies by defensive demands, with outfielders and first basemen generally leading due to fewer restrictions on swing mechanics.

Situational Leaders

In postseason play, several players have distinguished themselves with exceptional OPS figures, demonstrating their ability to perform under the intense pressure of playoff . Lou Gehrig leads all players with a career postseason OPS of 1.214 over 10 series, showcasing his dominance in 34 games where he hit .361 with 10 home runs. follows closely with a 1.211 OPS in 41 postseason games, tying Gehrig for the highest mark among players with at least 100 plate appearances. David Ortiz recorded a 1.089 OPS across three appearances (2004, 2007, and 2013), batting .455 with a .558 and contributing 14 RBIs in 14 games during those championship runs. Clutch performance with runners in scoring position (RISP) is another key situational metric where OPS reveals a player's effectiveness in driving in runs. ranks among the all-time leaders with a career 1.014 OPS in 1,763 plate appearances with RISP, significantly higher than his overall .996 OPS, highlighting his knack for delivering in high-leverage spots like the 2004 ALCS where he posted a 1.150 OPS. Other notable performers include (1.022 OPS with RISP over 1,200 PA) and Sr. (1.012 OPS), who consistently elevated their production when opportunities to score were critical. Situational splits, such as home versus away performance, further illustrate variability in OPS under different environments. exhibited a home OPS of 1.067 compared to 1.037 away across his career, attributed to factors like ballpark effects at and . Recent trends show two-way star adapting to postseason pressures; in his 2024 debut (NLDS vs. ), he posted a strong performance, and his overall career postseason mark stands at .940 as of the end of the 2024 season, improving further with a 1.096 OPS in the 2025 postseason. These examples underscore how OPS can fluctuate in specific contexts, providing deeper insight into player reliability beyond regular-season totals.

Criticism

Limitations

One primary limitation of OPS lies in its equal weighting of (OBP) and (SLG), which fails to reflect their differing contributions to run production. Specifically, one point of OBP is approximately twice as valuable as one point of SLG in generating runs, yet OPS treats them as equivalent, thereby undervaluing the importance of reaching base compared to extra-base power. For instance, a walk is worth about 0.7 times a in run value, but the metric does not differentiate these outcomes proportionally within its components. Additionally, OPS provides no adjustment for baserunning contributions, such as stolen bases or advancing on hits, nor does it account for defensive performance, limiting its scope to pure hitting events. This omission means OPS cannot fully capture a player's overall offensive value in contexts where speed or positioning on the bases influences scoring opportunities. Raw OPS can lead to misleading comparisons by not adjusting for park effects; it underrates hitters in pitcher-friendly parks, where offense is suppressed, and overrates those in hitter-friendly parks, where stats are inflated, without park adjustments. Furthermore, without era-specific normalization, OPS exhibits bias across historical periods; for example, in the Dead Ball Era (roughly 1900-1919), low-scoring conditions depressed OPS values, complicating direct comparisons to modern hitters. Studies indicate that while OPS correlates strongly with runs scored at approximately 0.90 or higher, more refined metrics like achieve correlations of 0.95 or better by better aligning event weights to run values. The rise of defensive shifts post-2015 further exacerbated OPS's shortcomings, particularly by reducing SLG through fewer infield hits on ground balls—shifts increased over 10-fold from 2010 to 2016, contributing to a measurable decline in league-wide SLG during this period. However, MLB's ban on defensive shifts starting in 2023 has curtailed their use, contributing to a recovery in league-wide SLG to .414 in 2023 from .395 in 2022, thereby mitigating this particular limitation.

Alternatives

While OPS provides a simple combined measure of on-base and power production, several advanced metrics offer more precise evaluations of offensive contribution by incorporating linear weights, contextual adjustments, or quality-of-contact data. One primary alternative is , developed by sabermetrician Tom Tango and detailed in the 2007 book The Book: Playing the Percentages in Baseball. quantifies a hitter's overall offensive value by assigning run-value weights to each type of outcome, such as walks, singles, doubles, and home runs, rather than treating all equally as in . For example, the formula for the season is wOBA = (0.696 × uBB + 0.726 × HBP + 0.883 × 1B + 1.244 × 2B + 1.569 × 3B + 2.004 × HR) / PA, where uBB denotes unintentional walks and PA is ; these coefficients are updated annually based on run expectancy data to reflect current league conditions. This approach makes wOBA superior to for estimating , as it directly correlates with actual scoring (r² ≈ 0.94 for team wOBA vs. runs per game) by valuing events proportionally to their impact on advancing runners, unlike OPS's equal weighting of and . Building on , weighted runs created plus (wRC+) extends the metric into a park- and league-adjusted index scaled to 100, where 100 represents average performance and values above or below indicate proportional run creation relative to league norms. Introduced by in 2009, wRC+ refines wOBA by normalizing for ballpark dimensions and era-specific run environments, enabling fairer cross-player and cross-season comparisons that OPS lacks due to its unadjusted nature. For instance, a wRC+ of 120 signifies 20% above-average run production after adjustments, providing a comprehensive view of hitting effectiveness. OPS derivatives, such as weighted OPS+ (wOPS+), attempt to enhance by applying similar linear weighting and adjustments, though they remain less favored than wOBA-based metrics for their continued reliance on unweighted components. For isolating pure power separate from —addressing OPS's conflation of contact and extra-base ability—isolated power (ISO) serves as a complementary tool, calculated as SLG minus AVG to measure average extra bases per at-bat from doubles, triples, and home runs. Popularized in sabermetric literature since the early , ISO highlights raw power hitters (e.g., values above 0.200 indicate strong extra-base production) without the influence of singles, offering a focused alternative when evaluating slugging's power element. Modern analytics introduce expected slugging (xSLG) from MLB's Statcast system, launched in 2015, which estimates a batter's slugging based on batted-ball quality metrics like exit velocity, launch angle, and sprint speed, rather than outcome-dependent SLG. xSLG mitigates luck and defensive variance in traditional SLG (and thus OPS), better revealing underlying power talent; for example, it projects outcomes as if every fair ball resulted in its "expected" hit type. These alternatives, particularly and wRC+, form the foundation of (WAR) calculations across major platforms like and Baseball-Reference, where batting runs are derived from wOBA to translate offensive production into estimated wins contributed.

References

  1. [1]
    On-base Plus Slugging (OPS) | Glossary - MLB.com
    OPS combines on-base percentage and slugging percentage, representing a hitter's ability to reach base, hit for average, and for power.
  2. [2]
    On Base Plus Slugging (OPS) - Baseball-Reference.com
    On base plus slugging is the sum of on-base percentage and slugging percentage. It's a common statistic used to judge offensive performance.
  3. [3]
    Why OPS Works - Society for American Baseball Research
    Nov 14, 2019 · Pete Palmer, the inventor of OPS (on-base plus slugging), explains how the offensive statistic was developed and why it remains robustly in use ...
  4. [4]
    What is OPS in baseball? Explaining one of MLB's advanced statistics
    Oct 2, 2022 · OPS stands for “on-base plus slugging.” This metric exists to combine on-base percentage and slugging percentage into one number.
  5. [5]
    What is OPS in baseball? Explaining meaning behind slugging, on ...
    Aug 19, 2025 · OPS stands for on-base percentage plus slugging percentage. A hitter's OPS is his on-base percentage and slugging percentage added together.
  6. [6]
    OPS and OPS+ - Sabermetrics Library - FanGraphs
    Feb 16, 2010 · On-base Plus Slugging (OPS) is exactly what it sounds like: the sum of a player's on-base percentage and their slugging percentage.
  7. [7]
    Baseball Prospectus Basics: OPS
    Mar 5, 2004 · As we mentioned earlier in the series, OPS winds up doing a pretty decent job of mimicking a description of overall offensive value. So it works ...
  8. [8]
    You Down in OPS? | RotoGraphs Fantasy Baseball - FanGraphs
    May 9, 2018 · Now, it's time to use OPS to help predict the individual categories. The process I used for this study was to simply see how much various ...
  9. [9]
    On-Base Percentage (OBP) - Baseball-Reference.com
    On-base percentage is a measure of how often a batter reaches base. It recognizes various different ways batters can get on base.
  10. [10]
    ESPN.com: MLB - MLB Stats Glossary
    Aug 28, 2025 · OBP, On-base percentage (H + BB + HBP) divided by (AB + BB + HBP + SF) ; OPS, On-base percentage plus slugging percentage. See OBP, above, and ...
  11. [11]
    OBP - Sabermetrics Library - FanGraphs
    Feb 16, 2010 · On-Base Percentage (OBP) measures the most important thing a batter can do at the plate: not make an out. Since a team only gets 27 outs per ...
  12. [12]
    Slugging Percentage (SLG) - Baseball-Reference.com
    Slugging percentage (SLG) is the number of total bases a player hits per at bat. It assigns extra value to extra-base hits.
  13. [13]
  14. [14]
    On-base Percentage (OBP) | Glossary - MLB.com
    Origin: On-base percentage was a statistic invented in the 1940s-50s by Dodgers executive Branch Rickey and statistician Allan Roth. It did not become an ...
  15. [15]
    Slugging Percentage (SLG) | Glossary - MLB.com
    Slugging percentage represents the total number of bases a player records per at-bat. Unlike on-base percentage, slugging percentage deals only with hits.
  16. [16]
    SABR 50 at 50: Analytics – Society for American Baseball Research
    Batter's Run Average / OPS (1974)​​ Eventually, they agreed that using addition instead of multiplication (OBP + SLG) would make an easier calculation without ...
  17. [17]
    Babe Ruth Stats, Height, Weight, Position, Rookie Status & More
    Babe Ruth. Positions: Outfielder and Pitcher. Bats: Left • Throws: Left. 6-2, 215lb (188cm, 97kg). Born: February 6, 1895 in Baltimore, MD us.Babe Ruth · 1935 Boston Braves Statistics · 1923 Awards Voting
  18. [18]
    Goodby to Some Old Baseball Ideas
    GOODBY TO SOME OLD BASEBALL IDEAS. The 'Brain' of the game unveils formula that statistically disproves cherished myths and demonstrates what really wins. by ...
  19. [19]
    KEEPING SCORE; Looking Beyond Batting Average
    Aug 1, 2004 · The first term is what we now call on-base percentage. The second, which Rickey called isolated power, is a modification of slugging percentage.Missing: origins | Show results with:origins
  20. [20]
    Bill James - BR Bullpen - Baseball-Reference.com
    He is currently employed by the Boston Red Sox as a Senior Baseball Operations Advisor. He began writing The Bill James Baseball Abstract in the 1970s, and ...
  21. [21]
    An Examination of the Moneyball Theory: A Baseball Statistical ...
    Jan 2, 2005 · His main two statistics included on-base percentage (OBP) and slugging percentage. These two stats combined to form a new statistic called on- ...
  22. [22]
  23. [23]
  24. [24]
  25. [25]
    What is a good ops in baseball? - HotBot
    Jul 18, 2024 · OPS is a measure of offensive performance combining OBP and SLG. League average is .720-.760; .900+ is excellent, .830-.899 is great.Components Of Ops · On-Base Percentage (obp) · Limitations Of OpsMissing: benchmarks | Show results with:benchmarks
  26. [26]
    League Ops In 1920 | StatMuse
    league ops in 1920 ; 1. NL .679 ; 2. AL .734.
  27. [27]
    MLB Players League Average Ops | StatMuse
    mlb players league average ops. The Boston Reds had an OPS of .774 in the PL all-time. TEAM, OPS, G, W%, W ... 1,910. 349 .278 .343 .393. 8. Burghers .718. 128 .
  28. [28]
    2024 League Average Ops - StatMuse
    2024 league average ops ; 1. NL .719. 2024. 2,430 ; 2. AL .703. 2024. 2,428.
  29. [29]
    Run Estimation for the Masses | The Hardball Times - FanGraphs
    Jan 12, 2006 · OPS can actually be thought of as a linear approximation or simplification of a statistic called “Batter Run Average” or BRA that was developed ...
  30. [30]
    Stats To Avoid: Runs Batted In (RBI) | Sabermetrics Library
    Oct 24, 2014 · Clutch numbers and offensive metrics with men on base or men in scoring position correlate very poorly from year to year and you are much ...Missing: non- | Show results with:non-
  31. [31]
    It's okay to be mystified by linear weights | The Hardball Times
    Mar 9, 2010 · People won't finish it knowing that wOBA is superior to OPS because of denominator problems and linear weights. But they just might leave ...
  32. [32]
    The great run estimator shootout (part 1) - The Hardball Times
    Apr 9, 2009 · Let's put ten different methods of measuring a player's offensive production through the wringer, and see which one comes out on top.
  33. [33]
    wRC and wRC+ | Sabermetrics Library
    Feb 16, 2010 · wRC is an improved version of Bill James' Runs Created (RC) statistic, which attempted to quantify a player's total offensive value and measure it by runs.
  34. [34]
    Sabermetrics Library - ISO
    Feb 15, 2010 · Isolated Power (ISO) is a measure of a hitter's raw power and tells you how often a player hits for extra bases.
  35. [35]
    How to Argue About Clutchness - FanGraphs Baseball
    Aug 7, 2024 · So the better hitters walk more and have a higher OBP, but the clutch ones hit for more power. And if you drill down on individual performance, ...Missing: OPS | Show results with:OPS
  36. [36]
    LI | Sabermetrics Library - FanGraphs
    Feb 17, 2010 · “Clutch hitting” is generally the result of small sample sizes and random variation. A player shown to be very clutch one season does not ...Missing: situational non-
  37. [37]
    On-base Plus Slugging Plus (OPS+) | Glossary - MLB.com
    On-base Plus Slugging Plus (OPS+). Definition. OPS+ takes a player's on-base plus slugging percentage and normalizes the number across the entire league.
  38. [38]
    Batting Stats Glossary - Baseball-Reference.com
    Take OPS+ = 100 * (OBP/lgOBP* + SLG/lgSLG* - 1) Note, in my database, I don't store lgSLG, but store lgTB and similarly for lgOBP and lg(Times on Base), this ...
  39. [39]
    Ballpark Factor | Glossary - MLB.com
    Ballpark factor, at its most basic, takes the runs scored by Team X (and its competitors) in Team X's home ballpark and divides the figure by the runs scored ...
  40. [40]
    Park Factors - Sabermetrics Library - FanGraphs
    Feb 27, 2010 · We apply something called a park factor to even out the differences. These park factors are imperfect for a variety of reasons, but what they're after is on ...
  41. [41]
    Park factors measured by Statcast - MLB.com
    Apr 29, 2021 · Any time you see a stat with a “+” on the end (like OPS+ or ERA+, for example) that means it's been adjusted not only to set league average to ...
  42. [42]
    Statcast Park Factors | baseballsavant.com - MLB.com
    Statcast park effects show the observed effect of each displayed stat based on the events in the selected park. Each number is set so that “100” is average ...Park Factors Leaderboard · Coors Field · T-Mobile Park · Pitch Timer InfractionsMissing: post- | Show results with:post-
  43. [43]
    Barry Bonds Stats, Height, Weight, Position, Rookie Status & More
    Check out the latest Stats, Height, Weight, Position, Rookie Status & More of Barry Bonds. Get info about his position, age, height, weight, draft status, ...Barry Bonds · Bobby Bonds · RISP
  44. [44]
    Mule Suttles Black Baseball Leagues Statistics
    OPS+. 172. Mule Suttles Overview; More Suttles Pages. Black Baseball Stats ... 2025 MLB Batting, 2025 MLB Pitching, Career WAR Leaders, Single-Season Home ...
  45. [45]
    Career Leaders & Records for On-Base Plus Slugging
    Career OPS Leaders:1.Babe Ruth+/1.1636/10628, 2.Ted Williams+/1.1155/9792, 3.Lou Gehrig+/1.0798/9665, 4.Oscar Charleston+/1.0639/3885, 5.
  46. [46]
    Career Leaders for On Base Plus Slugging - Baseball Almanac
    The on base percentage statistic was originally created by Branch Rickey and Allan Roth in the 1950s as a means to measure the percentage of times a player ...
  47. [47]
    Mike Trout Stats, Height, Weight, Position, Rookie Status & More
    Mike Trout · 3x MVP · Rookie of the Year · 11x All-Star · 9x Silver Slugger · 2x AS MVP · ML PoY · Wilson Overall Def Player.
  48. [48]
    Shortstop Ops Career Leaders - StatMuse
    Alex Rodriguez has the highest career OPS by a shortstop, with an OPS of .963. Interpreted as: shortstop ops with a minimum of 3000 PA career leaders. NAME, OPS ...
  49. [49]
    David Ortiz Stats, Height, Weight, Position, Rookie Status & More
    SUMMARY. Career. WAR. 55.0. AB. 8640. H. 2472. HR. 541. BA .286. R. 1419. RBI. 1768. SB. 17. OBP .380. SLG .552. OPS .931. OPS+. 141. David Ortiz Overview; More ...
  50. [50]
    The Outsiders: No. 20, Manny Ramírez - The Athletic
    Dec 28, 2020 · I've never seen a player who loved driving in runs more than Manny. Highest career OPS with runners in scoring position (min. 1,000 PAs).
  51. [51]
    Taking a Closer Look at Hitting with Runners in Scoring Position
    Jun 22, 2014 · 1. OPS with an R2 of .9132 (91% of the OPS x-values fit the formula: y = 2059.2x – 791.27) · 2. ISO with an R2 of .5801 (58% of the ISO x-values ...
  52. [52]
    Shohei Ohtani Postseason Ops - StatMuse
    Shohei Ohtani has an OPS of .940 in the postseason in his career. · More Dodgers Stats · MLB 2025 Batting Leaders · MLB 2025 Pitching Leaders · MLB Fantasy 2025.
  53. [53]
    Examining Perceptions of Baseball's Eras: A Statistical Comparison
    Oct 25, 2018 · The current study uses On-Base Plus Slugging Percentage (OPS) to measure both hitting and pitching's contributions to winning percentage because ...
  54. [54]
    Prospectus Feature: OPS and wOBA, Briefly Revisited
    Jul 10, 2018 · Put simply, team OPS does better measure team hitting production than team wOBA: the descriptive performance is comfortably outside the margin ...
  55. [55]
    The MLB's 2023 Rule Changes: A First Analysis of Their Impact on ...
    Aug 22, 2024 · The trends in wOBA, BA, OBP, and SLG from 2016 to 2024 show a clear decline, aligning with the rise in defensive shifts and the analysis in ...
  56. [56]
    wOBA | Sabermetrics Library
    Feb 15, 2010 · OPS undervalues getting on base relative to hitting for extra bases and does not properly weigh each type of extra base hit.Missing: limitations | Show results with:limitations
  57. [57]
    wRC+ and Lessons of Context - Sabermetrics Library - FanGraphs
    Jul 25, 2014 · Weighted Runs Created Plus (wRC+), which is an all-encompassing hitting statistic that weights each offensive action properly (like wOBA), but also adjusts ...
  58. [58]
    What is wRC+? - FanGraphs Baseball
    Dec 13, 2009 · It's park and league adjusted and it's on a very similar scale as OPS+. The difference is that it uses wRC, which is based on wOBA. For ...
  59. [59]
    Isolated Power (ISO) | Glossary - MLB.com
    ISO measures the raw power of a hitter by taking only extra-base hits -- and the type of extra-base hit -- into account.Missing: comparison | Show results with:comparison
  60. [60]
    Expected Slugging Percentage (xSLG) | Glossary - MLB.com
    Expected Slugging Percentage (xSLG) is formulated using exit velocity, launch angle and, on certain types of batted balls, Sprint Speed.
  61. [61]
    Statcast Expected wOBA, xBA, xSLG | baseballsavant.com - MLB.com
    Expected Outcome stats help to remove defense and ballpark from the equation to express the skill shown at the moment of batted ball contact.Missing: alternative | Show results with:alternative
  62. [62]
    Position Player WAR Calculations and Details | Baseball-Reference ...
    ... different multipliers to the leagues, but centered on 20.5 for ... Minor League Stats, College Baseball Stats, Black Baseball Stats, Nippon Pro Baseball ...