What is Fielding Independent Pitching (FIP)?

Fielding Independent Pitching, or FIP, is an advanced pitching statistic. FIP is the most popular form of a school of stats known as Defense-Indepndent Pitching Stats, or DIPS.

DIPS theory first came about in the late 1990s, when sabermetrician Voros McCracken studied the impact that pitchers had on balls in play. To the surprise of many, McCracken found that pitchers had virtually no impact on whether balls in play were fielded or became hits.

FIP, then, measures a pitcher’s performance based only on those things that he can control: strikeouts, home runs, and walks. Those are then weighted and put through a formula that presents FIP on a similar scale to ERA.

How is Fielding Independent Pitching (FIP) used?

FIP is meant to be the DIPS equivalent of ERA, measuring a pitcher’s overall performance scaled to their innings pitched.

Similar to ERA, the most elite performances will be around 2.00 or below while an average FIP will be around 4.00, depending on the season.

FIP is used, just like ERA, to see who were the best pitchers in a given season or range of years. It can also be used to compare players.

Lastly, FIP is often compared to ERA as a way of evaluating pitcher performance. In a short run, such as part of a season or even a full year, a discrepancy between FIP and ERA most likely means that a pitcher is getting lucky or unlucky on balls in play. If you are looking for players who might regress to the mean in either direction, comparing FIP and ERA is a good way to do it.

However, over a longer span, it could be the case that the pitcher is uniquely good or terrible at limited balls in play. While the pitcher doesn’t have a lot of control over balls in play, it might be overstating the case to say they have no control over it. Looking at FIP vs ERA over a large sample size and help us gauge a pitcher’s skill in this area.

How to calculate Fielding Independent Pitching (FIP) [Formula]?

FIP uses a very simple formula:

(13HR + 3BB – 2*K)/IP + C

HR is home runs, BB is walks, K is strikeouts, and IP is innings pitched. Lastly, C is a constant that changes year-by-year to re-center the league-average FIP to match its average ERA.

Interesting Fielding Independent Pitching (FIP) Stats

You can see the all-time career and single-season leaders in FIP on the Baseball Reference website.

 What is Wins Above Replacement?

Wins Above Replacement, popularly known as WAR, is an advanced baseball statistic that accounts for every action a player takes on the field. That means that WAR presents a single number that represents an estimate of a player’s entire overall value: their hitting (or pitching, for pitchers), fielding, baserunning, and more.

WAR attempts to isolate only the factors in a player’s control in order to present the value they would bring to any team, regardless of the lineup around them, the ballpark they play in, or other contextual factors.

How is Wins Above Replacement used?

WAR is used by fans and journalists as a quick way to estimate a player’s total value, compared to a replacement player. 

It is important to note that in WAR, “replacement player” doesn’t refer to the player’s back-up on the roster, or a replacement superstar that a team could trade for. In this case, the “replacement player” is a theoretical idea, referring to the sort of AAA player that a team could call up to their roster for free.

Therefore, replacement level is quite low. A team of replacement-level players could be expected to have around a .294 winning percentage. Average MLB players, on the other hand, are quite valuable, usually rating around 2.0 WAR in a season.

WAR is also used after a player retires, in order to gain an understanding of their entire career. Hall of Fame debates often use WAR as a way of understanding whether a player is worthy of induction.

How to calculate Wins Above Replacement?

There are a few different ways to calculate Wins Above Replacement. Because WAR is not a stat like hits or walks, that corresponds to single game actions clearly laid out in the rule book, it is important for a WAR formula to have a framework that can be applied to every player in order to ensure consistent results.

On Baseball Reference, WAR for hitters is calculated from different component parts. Starting with hitters, WAR takes everything a player did as a batter, including hits, walks, strikeouts, and more, and uses a framework to calculate the player’s overall offensive contribution. It then does the same for the player’s defensive work (using the DRS framework) and baserunning. 

In addition to those, WAR includes an adjustment for the player’s position. This is because different positions have different offensive standards. For example, in 2024, catchers in the major league produced an OPS of .678, while DHs had an OPS of .742. A player with a .700 OPS would be an above average hitter as a catcher, but below average as a DH. Finally, the player is credited with the value of a replacement-level player, in order to set a league-wide baseline.

For pitchers, the process is the same, but the inputs are slightly different. Baseball Reference’s WAR starts with RA9. This stat is like ERA, but without the earned vs unearned run distinction. It then adjusts for the quality of opponents faced, the defense behind the pitcher, their role (starter or reliever), the ballparks they pitched in and, starting in 2020, any innings pitched in extra innings where the “ghost runner” now starts on second.

Wins Above Replacement Examples

In 2024, Shohei Ohtani’s WAR was calculated by starting with the WAR components. Here are the components and how the broke down:

• Rbat, or the batting component of WAR = 74
• Rfield, or the fielding component of WAR = 0
• Rdp, an adjustment for avoiding grounding into double plays = 3
• Rbaser, or the baserunning component of WAR = 10
• Rpos, an adjustment for position = -16
• Replacement level = 23

That gives Ohtani roughly 93 runs, although the number is lower than that due to rounding. It is generally accepted that 10 runs equal one win, so Ohtani’s WAR was 9.2.

Popular or Interesting Wins Above Replacement Stats

The all-time greatest season by WAR was by Tim Keefe, who had 20.2 WAR in 1883. In the modern era, the best season by a pitcher was Dwight Gooden’s 13.3 in 1985. The best by a position player was Babe Ruth’s 14.1 in 1923 (Ruth did not pitch at all that season).

Career-wise, the most WAR in MLB history is 182.6, a record set by Babe Ruth. In the modern era, the record holder is Barry Bonds with 162.8 

 What is a Magic Number?

Magic Number refers to the number of games that a team in a division or wild card race needs to go their way in order to clinch the winning position.

The Magic Number is the number of games that would need to go a team’s way, including both wins by the team and losses by their nearest rival, in order for them to clinch the spot. Once the Magic Number is 0, the team has clinched.

How is a Magic Number used?

In the back half of the regular season, teams are competing for playoff spots, either by winning their division or clinching a wild card slot. The Magic Number allows teams to visualize how close they are to clinching.

The Magic Number typically becomes a discussion topic in early September, when the Postseason is close and the Magic Number is small enough to be achievable.

How to calculate Magic Number?

The Magic Number is calculated by adding the total number of games remaining in the season, adding one, and then subtracting from this the number of the leading team’s wins and the pursuant team’s losses

As a formula, that looks like:

MN = (G + 1) – (WA + LB)

• G : number of games during the season
• WA : number of wins by the leading team
• LB : number of losses by the pursuing team

Magic Number Calculator

Magic Number Examples

Let’s say the Mariners and Rangers are in a race for the AL West. The Mariners are 80-70 and the Rangers are 78-72. That means both teams have 12 games remaining and the Mariners have a two-game lead.

Seattle’s magic number would be (162+1) – (80+72) or 11.

What is Baseball Game Score?

Game score, a metric created by Bill James, measures a starting pitcher’s effectiveness in a single game. It uses a system of pluses and minuses to create a score. That score can easily be compared to standard benchmarks to determine how well the pitcher performed.

How is Game Score used?

Game score is analyzed on a fairly intuitive scale. A score of 50 reflects an average outing. Conversely, scores of 0 or below (very bad) or 100 or greater (very good) rarely happen.

The average score for a starting pitcher at home is slightly higher than for the road starter, reflecting baseball’s home field advantage. In practice, the difference comes from a better strikeout rate for home starters. Some believe that unconscious bias by home plate umpires causes that difference, giving a few extra strikes per games to the home side.

Game score often correlates closely with pitching wins. However, this correlation breaks down at the very top end of the scale (scores of 90 or more). Many of these very high scores happen in games that go to extra innings, making it much harder for the starting pitcher to pick up the win.

How to calculate Game Score?

Start with 50 points.

Add:

• 1 point for each out (or 3 points per inning)
• 2 points for each inning completed after the 4th
• 1 point for each strikeout

Subtract:

• 2 points for each hit allowed
• 4 points for each earned run allowed
• 2 points for each unearned run allowed
• 1 point for each walk.

The total is the pitcher’s score for that game.

Game Score Calculator

Game Score Examples

Let’s use Kerry Wood‘s May 6, 1998 one-hitter as an example of how to calculate game score. (Hint: it’s the best score in a nine-inning game.)

1. Start with 50 points.
2. Add 1 point for each out. Since Woods pitched all 9 innings, we can add 3 points per inning. 3*9 = 27. 50+27 = 77.
3. Add 2 points for each inning completed after the 4th. Woods pitched all 9 innings, so he pitched 5 innings after the 4th. 5*2 = 10. 77+10 = 87.
4. Add 1 point for each strikeout. Woods had 20 strikeouts. 87+20 = 107.
5. Subtract 2 points for each hit allowed. Woods only allowed 1 hit. 107-2 = 105.
6. Woods did not allow any runs, earned or unearned, so no points will be subtracted for allowing runs.
7. Woods did not walk any batters, so no points will be subtracted for walks, either.

Woods’ score (the best in a nine-inning game) was 105.

Interesting Game Score Stats

Dean Chance recorded the best game score since 1957, with a 116 score in 1964. He threw 14 shutout innings, giving up just 3 hits and striking out 12.

On the other hand, Mike Oquist recorded a -21 score in 1998 for the worst score since 1957. Oquist gave up 14 earned runs in 5 innings. The worst score between 1901 and 2021 was -56 by George LeClair of the Pittsburgh Rebels on August 16, 1914.

From 1957 to 2007, only 40 games recorded a 100+ score. Four of those games belonged to Nolan Ryan.

What is Walks plus Hits per Innings Pitched (WHIP)?

WHIP, or Walks plus Hits per Inning Pitched, is a rate stat used to measure how many base runners a pitcher allows per inning through walks and hits. The stat itself is a core metric for evaluating pitcher performance, without accounting for strikeouts or runs. Hit batters, errors, and runners who reach on a fielder’s choice are not included in WHIP. A strong indicator of an effective pitcher is by looking at their WHIP, as a lower WHIP usually signals better command, cleaner innings, and less erratic pitching. While a higher WHIP signals less command on pitchers and an innings that have hitters constantly reaching base, potentially causing runs against the pitchers team. 

How is WHIP Used?

WHIP is used to evaluate how well a pitcher limits base runners, but several factors can influence the stat. Strong team defense can lower a pitcher’s WHIP by turning borderline hits into outs. On the flip side, poor defense can inflate WHIP even if the pitcher is making quality pitches. Ballpark factors also matter: pitchers in hitter-friendly parks tend to allow more hits, which impacts WHIP. Most importantly, control plays the biggest role. Pitchers with sharp command and low walk rates typically post lower WHIPs, making the stat a clear indicator of consistency and efficiency on the mound. 

WHIP Formula

WHIP = (Walks + Hits) / Innings Pitched

The formula consists of: adding the number of walks and hits a pitcher allows, then divide that by the total innings pitched.

WHIP Calculator

How to use WHIP?

WHIP is useful because it strips out other variables and focuses on the two most important responsibilities for a pitcher: a pitcher’s ability to avoid walks and avoid giving up hits. A WHIP below 1.00 is considered elite, while anything above 1.15 tends to fall into the average range. 

WHIP Examples

Pedro Martinez 2000- 0.737WHIP = (32 + 128) / 217.0 

https://www.baseball-reference.com/players/gl.fcgi?id=martipe02&t=p&year=2000

Clayton Kershaw 2014- 0.857WHIP = (31 +139)/ 198.1

https://www.baseball-reference.com/players/gl.fcgi?id=kershcl01&t=p&year=2014

Justin Verlander 2019- 0.803WHIP = (42+137)/ 223.0 

https://www.baseball-reference.com/players/gl.fcgi?id=verlaju01&t=p&year=2019

What is On Base Plus Slugging?

On Base Plus Slugging (aka OPS, and sometimes called Offensive Production Statistic) is the sum of on-base percentage (how often a player reaches base) and slugging percentage (how many bases a player records per at-bat). Because OPS combines on-base percentage and slugging percentage, it tells us how good a player is at both batting and getting on base.

There are many variations on OPS, including Gross Production Average, which tries to reflect the different values of getting on base and slugging, and OPS+, which we’ll explore later in this section.

How is OPS used?

OPS is a common statistic used by sabermetricians to judge a player’s overall offensive performance. It was first devised by Pete Palmer as a simple measure of a batter’s offensive contribution that still correlates with more sophisticated measures of offensive production. 

What is a good OPS in baseball?

A good on-base plus slugging percentage is anything above the league average, which is usually between .700 and .750. Anything above .900 is considered elite.

What is OPS+?

Another way of using OPS is considering OPS+ (aka Adjusted OPS or NOPS/Normalized OPS). Some serious fans consider it the best quick way to get a sense of a batter’s quality. 

OPS+ adjusts OPS to account for the ballpark and the league that a player played in. It also “normalizes” the number, so that the median is 100 and better-than-average scores are above 100. This makes it easy to tell what a good OPS+ is.

A single-season OPS+ performance of 140 or higher could be considered a Hall of Fame level performance for that season. In terms of career performance, the top 100 players have a career OPS+ of 138 or higher.

On Base Plus Slugging Formula

The baseball OPS formula is:

OPS = OBP + SLG

OBP is the player’s on-base percentage, and SLG is the player’s slugging percentage.

On Base Plus Slugging Examples

How to calculate On Base Plus Slugging for a season

Let’s use Shohei Ohtani’s 2024 season stats as an example of how to calculate on base plus slugging percentage. In 2024, Ohtani recorded a .390 on-base percentage and .646 slugging percentage. Here’s how to use the baseball OPS formula to calculate Shohei Ohtani’s 2024 OPS:

1. Add Ohtani’s OBP and SLG. .390+.646 = 1.036.

Ohtani had a 1.036 OPS in 2024. That is an excellent OPS, making him an elite hitter for the 2024 season.

How to calculate On Base Plus Slugging for a game

We can also use the OPS formula to calculate OPS in a single game. In the first game of the 2024 World Series, Ohtani recorded a .414 OBP and .489 SLG.

1. Add his one-game OBP and SLG. .414+.489 = .903.

Ohtani had a .903 OPS in the first game of the 2024 World Series.

OPS Calculator

Interesting OPS Stats

You can see the single-season leaders in OPS, or the career leaders in OPS on Baseball Reference.

What is Slugging Percentage?

Slugging percentage (aka SLG, and also called Slugging Average) is the number of total bases a player hits each at bat. It only includes hits (not walks and hit-by-pitches) and assigns extra value to extra-base hits. This makes it a good measure of a player’s power.

How is SLG used?

Unlike batting average, SLG differentiates between kinds of hits. It values doubles more than singles; triples more than doubles; and home runs more than triples. Since extra-base hits are generally better than singles, it’s useful to have a stat that reflects that.

Since the league average in SLG is usually around .400, a good slugging percentage is above .400. The best hitters will have at least a .500 SLG.

Slugging Percentage Formula

The slugging percentage formula is:

SLG = (Singles + (2 × Doubles) + (3 × Triples) + (4 × Home Runs)) ÷ At Bats

SLG Examples

Using Slugging Percentage Formula #1

Let’s look a a real-life example to learn how to use the first slugging percentage formula. During the 2024 season, Aaron Judge recorded 180 hits, 36 doubles, 1 triple, and 58 home runs in 559 at bats. First, we need to find how many singles Judge hit.

1. Subtract doubles, triples, and home runs from total hits. 180-(36+1+58) = 85.

Judge hit 85 singles. Now, let’s plug that into the slugging percentage formula.

1. Multiply Judge’s extra-base hits by their respective values. 2*36 = 72. 3*1 = 3. 4*58 = 232.
2. Add up the total bases from Judge’s hits. 85+72+3+232 = 392.
3. Divide Judge’s total bases by his at bats. 392/559 = .701.

Judge had a .701 SLG in 2024.

Slugging Percentage Calculator

Interesting SLG Stats

You can see the single-season leaders in SLG, or the career leaders in SLG on Baseball Reference.

What is On-Base Percentage?

On-base percentage (aka OBP, On Base Average, OBA) measures how often a batter reaches base. Unlike batting average, which only values hits, OBP recognizes that batters can get on base in many different ways.

How is OBP used?

On-base percentage reflects a player’s overall offensive skill. It gained popularity after Moneyball, which demonstrated that OBP was an underrated tool for roster-building.

OBP, when combined with slugging percentage (SLG), produces on-base plus slugging (OPS), a measure of how good a player is at both hitting and getting on base.

OBP vs. Batting Average

On-base percentage tells a more complete story, in comparison to batting average. A player with a low batting average could still have value offensively if he gets on base in other ways, like drawing walks or getting hit by pitches. OBP will thus reflect that player’s offensive skill better than batting average can.

What is a good OBP?

Typically, league average on-base percentage is around .320, and anything above .340 is considered a good OBP. Elite batters may record OBPs over .400, and the best batters might even have OBPs above .450. For example, Barry Bonds had a single-season record .609 on-base percentage in 2004.

On-Base Percentage Formula

OBP is approximately equal to times on base divided by plate appearances. However, the full on-base percentage formula is more complex:

OBP = (Hits + Walks + Hit by Pitch) ÷ (At Bats + Walks + Hit by Pitch + Sacrifice Flies)

Note that batters are not credited with reaching base on an error or fielder’s choice. This is because in those situations, the batter gets on base because of a defensive decision or miscue – not his own batting. Batters also are not charged with an opportunity if they make a sacrifice bunt.

OBP examples

How to calculate On-Base Percentage for a season?

Let’s look at Kyle Schwarber’s 2023 season as an example of how to calculate OBP. This is a good scenario for OBP because Schwarber’s 2023 batting average (.197) was not very high. So was he really ineffective offensively, or was he just not getting many hits? To find out, let’s calculate his 2023 OBP.

1. Add Schwarber’s hits, walks, and HBP. 115+126+6 = 247.
2. Add Schwarber’s at bats, walks, HBP, and sacrifice flies. 585+126+6+3 = 720.
3. Divide. 247/720 = .343.

So despite his batting average, Schwarber had a good OBP (.343) in 2023.

How to calculate On-Base Percentage for a career?

To calculate OBP for a career, let’s look at Ted Williams, who has the highest career OBP in Baseball Reference’s database.

1. Add Williams’ career hits, walks, and HBP. 2654+2021+39 = 4714.
2. Add Williams’ career at bats, walks, HBP, and sacrifice flies. 7706+2021+39+20 = 9786.
3. Divide. 4714/9786 = .482.

Ted Williams’ .482 career OBP is the highest in Baseball Reference’s records.

On-Base Percentage Calculator

Interesting OBP stats

You can see the single-season leaders in OBP, or the career leaders in OBP on Baseball Reference.

 What is Batting Average?

Batting average is a measure of the percentage of at bats where a player obtained a hit. It does not include walks, hit by pitch, or sacrifices.

How is Batting Average used?

For many years, batting average was one of the most popular baseball stats, often used as a stand-in for a hitters overall skill. At the end of each season, the batting title is awarded to the player who leads the league in batting average, and the stat often appears on scoreboards and baseball cards.

However, in recent years, the rise of sabermetrics and advanced stats has led to a decrease in the emphasis on batting average. Today, more stat-savvy fans look at statistics like on-base percentage or on-base plus slugging as better measures of a hitter’s overall skill. Those stats incorporate the ability to take a walk, as well as accounting for the added value of home runs.

This goes along with changes to the game itself. In early baseball, hitters very rarely worked, and many did not see working the count or playing for walks as a good strategy. Additionally, home runs were rare during baseball’s Deadball Era. As walks and home runs have become more prominent, fans’ understanding of batting average has changed too.

How to calculate Batting Average?

How to calculate batting average? It is an extremely easy formula. You simply divide a player’s number of hits by his total number of at bats. The formula looks like this:

H / AB = AVG

So if a player had 100 hits in 400 at bats, they would have a batting average of .250

Batting Average Examples

The best career batting average belongs to Ty Cobb, who had a .366 batting average over his career. That’s 4,189 hits in 11,440 ABs. Ranking second is Oscar Charleston with .364.

In a single season, the best is .471 by Tetelo Vargas in the 1943 NNL. For the AL/NL, the record holder is Hugh Duffy, who hit .440 in 1894. Overall, there have been 58 qualified seasons where a player hit .400, none in the last 75 years. 

A .400 batting average is one of the craziest things a hitter could achieve, and there’s often excitement and interest around a player who managed to take a .400 average into June.

Batting Average Calculator

Interesting Batting Average Stats

See the batting average leaders on Baseball Reference

What is Total Bases?

Total bases are a key statistic in baseball that measure the number of bases a player gains through hits. It is a straightforward calculation that assigns a value based on the type of hit a player records.

Unlike other offensive statistics, total bases focus only on the bases a player earns through clean hits. Walks, stolen bases, hit-by-pitches, and reaching base on errors are not factored into this metric. Total bases strictly measure the outcome of a batter’s ability to hit and how much offensive advancement they create through those hits.

How is Total Bases Used?

Total bases are used to measure a player’s overall offensive output, focusing on both consistency and power. The statistic is a key component in calculating slugging percentage (SLG), where total bases are divided by at-bats to gauge a player’s ability to hit for extra bases. High total base counts are often tied to MVP seasons and standout performances. They provide a clear, simple way to evaluate offensive impact without the influence of walks or errors, making them essential for comparing hitters across different eras and styles of play.

Total Base Formula

Total Bases (TB) = (1 × Singles) + (2 × Doubles) + (3 × Triples) + (4 × Home Runs)

How to calculate Total Base?

Each hit is weighted by the number of bases it produces. Singles add one base, doubles add two, triples add three, and home runs add four.

Beyond individual performance, total bases also have team value. Coaches and analysts use total base numbers to help determine a player’s role in the lineup. Hitters with high total base counts are often placed in the middle of the order, where their ability to produce extra-base hits can drive in runs and shift games.

Total Base Examples

Aaron Judge (June 8th, 2025 – Yankees vs Boston Red Soxs)

Game Line: 3 Hits, 2 Home Runs, 1 Single – 9 Total Bases 

Total Bases (9) = (1 ×1) + (2 × 0) + (3 × 0) + (4 ×2)

https://www.baseball-reference.com/boxes/NYA/NYA202506080.shtml

Shawn Green (May 23rd, 2002 – Dodgers vs Brewers)

Game Line: 6 Hits, 1 single, 1 double, 4 Home Runs – 19 Total Bases

Total Bases (19) = (1 ×1) + (2 × 1) + (3 × Triples) + (4 ×4)

https://www.baseball-reference.com/boxes/MIL/MIL200205230.shtml

Albert Pujols (October 22nd, 2011 – Cardinals v Rangers Game 3 WS)

Game Line: 5 Hits, 2 singles, 3 Home Runs – 14 Total Bases 

Total Bases (14) = (1 ×2) + (2 × Doubles) + (3 × Triples) + (4 ×3)

https://www.baseball-reference.com/boxes/TEX/TEX201110220.shtml

Total Bases Calculator