What Is Fip Baseball

MLB stat definition: What is FIP?

The 17th of February, 2011 What exactly is FIP? Fielding Independent Pitching (FIP) is an abbreviation. It is a statistic that is used to evaluate a pitcher’s performance by excluding plays in which the defense attempts to field the ball from the equation.

What is FIP?

FIP is calculated by converting a pitcher’s strikeouts, walks, and home runs allowed into a value that is scaled to his or her earned run average. Consider it to be what the pitcher’s earned run average (ERA) should be if the defense behind him converted batted balls into outs at a rate comparable to that of the major leagues. A good FIP, much like a good ERA, is likely going to be in the 2s or low 3s, which is akin to a good WHIP. Gio Gonzalez (2.82), Felix Hernandez (2.84), and Clayton Kershaw (2.85) were the major-league leaders in FIP in 2012, respectively (2.89).

What is the application of this tool?

  • In the first place, it may be used to determine which pitchers were the most and least effective at the things they controlled during a specific period of time.
  • Generally speaking, pitchers who have greater season-long FIPs than their ERAs are regarded to be more likely to have their performance deteriorate.
  • Nine of the ten had their ERAs climb in 2012, according to the data.
  • a total of 65 points lower than their ERAs saw a reduction in their ERAs in 2012.
  • Fangraphs.com provides an annual breakdown of a pitcher’s FIP.

FIP

ERA Fielding Independent Pitching (FIP) calculates what a pitcher’s ERA would look like over a particular period of time if the pitcher had had league average results on balls in play and league average timing during that time period. In the early 2000s, Voros McCracken conducted research that found that the number of balls that fall into the batter’s box for hits against pitchers does not correspond well between seasons. As a result, pitchers have limited influence over the balls in play, and presuming that short-term changes in BABIP are due to the pitcher is likely to be erroneous.

It is a measure of a pitcher’s performance that excludes the effects of defense, luck, and sequencing.

Certain pitchers have demonstrated the capacity to produce lower ERAs on a continuous basis than their FIP indicates, but overall, FIP accurately reflects the underlying performance of the vast majority of pitchers.

Calculation: The formula for FIP is as follows: Formula for determining the fraction of time in which a person spends in the field = (13*HR + (3*(BB+HBP))-(2*K)/IP plus a constant The constant is used primarily to convert FIP to an ERA scale, and it is often about 3.10 in value.

Because FIP is built in such a way that the league average ERA and the league average FIP are the same, all you need to do to calculate the constant for any given year is the following: FIP Constant = (((13*lgHR)+(3*(lgBB+lgHBP))-(2*lgK))/lgIP) lgERA – (((13*lgHR)+(3*(lgBB+lgHBP))-(2*lgK))/lgIP) lgERA – (((13*lgHR)+(3*(lgBB+lg Having an understanding of how to compute the constant might be especially beneficial when you’re interested in performing some of your own calculations for data spanning numerous seasons.

  • Run prevention is considered in the calculation of the individual weights for home runs, walks/HBP, and strikeouts.
  • Why FIP is important: In the end, we want to employ statistics that will allow us to isolate the performance of the player we are aiming to study, rather than generalized statistics.
  • This is because the number of runs a pitcher allows is also dependent on their defense, luck, and the sequence in which things happened (often called sequencing).
  • The outcome of balls in play has been demonstrated to be almost totally out of the control of pitchers, thus while we care about how often a pitcher allows a ball to be put into play, whether a ground ball goes for a hit or is turned into an out is almost entirely out of their control.
  • We worry about Batting Average on Balls in Play (BABIP) for a variety of reasons, one of which is because pitchers have very little influence over the BABIP they are permitted to allow.
  • The pitcher who plays better defense will allow fewer hits and, as a result, fewer runs, yet the two pitchers were virtually comparable in their performances.
  • A single, a single, a home run and an out are all it takes to allow three runs in a game with two outs.

To put it simply, FIP is an attempt to determine how well a pitcher actually did, regardless of circumstances outside of his control that contribute to statistics such as runs allowed.

However, these pitchers are rather infrequent, and FIP continues to be highly accurate while still remaining exceedingly simple.

However, there are certain limitations.

A pitcher’s FIP (Fielding Independent Pitching) is the same as their ERA (Fielding Independent Runs) when it comes to making comparisons between different players.

While FIP can be useful in determining how a pitcher will perform in the future, its use should be approached with caution.

In the long run, the vast majority of pitchers will have ERAs and FIPs that are extremely near to one another, but over the course of a season, these numbers can vary significantly from one another.

For example, pitchers who have the ability to minimize the running game or create fly balls at the price of line drives or ground balls are more likely than the typical player to beat their FIP.

The better bet if you have to choose between betting on an individual pitcher’s ERA or their FIP is to go with the latter.

FIP is an excellent statistic, but as is typically the case, delving deeper into the statistic’s components and other measures of pitcher performance can help you gain a better understanding of how a pitcher is genuinely doing.

Check out the FanGraphs leaderboards to see what the league-average FIP has been for every year since 1901 up to the present. Pitching in a Fielding-Independent Environment (FIP)

Rating FIP
Excellent 3.20
Great 3.50
Above Average 3.80
Average 4.20
Below Average 4.40
Poor 4.70
Awful 5.00

Using the 2016 Run Environment as a guide Defense Independent Pitching Theory was the name of Voros McCracken’s research project (DIPS Theory). It serves as the foundation for most of the pitching analysis that is done today. It can be a difficult notion to grasp and one that is counter-intuitive to the majority of baseball fans. For additional details, please see our pages on DIPs, BABIP, and Luck & Chance. Because there might be a lot of volatility in tiny samples, FIP does a better job of forecasting the future than it does of measuring it in the present.

  • That is not to say that it is not a retrospective statistic; rather, it is to say that it takes more than a handful of innings to be a valid predictor of performance, just as any other statistic would require as well.
  • Fans may use FanGraphs’ FIP- statistic, which is a park and league adjusted version of the statistic, to account for both of these variables.
  • Listed below are some further reading resources: Getting Started with FIP – Big League Stew The Mike Silva Chronicles are a collection of short stories written by Mike Silva.
  • In addition to the Boxscore, the FIP Constant may be calculated as follows: FanGraphs has Oswalt’s FIP and Oswalt’s WHIP.

Baseball Prospectus

View Glossary Entries Using a Specific Field Independent Pitching is a technique that transforms a pitcher’s three genuine outcomes into a statistic that is similar to his earned run average. Using the formula (13*HR+3*(HBP+BB)-2*K)/IP, adding a constant (often about 3.2) to put it on the same scale as earned run average, the earned run average is calculated as A component ERA inspired by Voros McCracken’s work on defense-independent pitching statistics, FIP has gained popularity due to its simplicity of computation – it requires only four easily-found box score stats, only basic arithmetic operations, and only four easily-memorized constants – as well as its ease of use.

Tom Tango and Clay Dreslough were the ones who came up with the idea, with the latter referring to it as the ERA (Defense-Independent Component).

It is important to note that the FIP constant we utilize is league and season specific; for example, a pitcher in the American League would have a different constant than a pitcher in the National League.

Based on the 2011 season, here is an example of the Fielding Independent Pitching spectrum: Roy Halladay’s performance was outstanding.

2.17 Outstanding – David Price Tim Stauffer has a 3.36 grade point average. Carlos Zambrano’s performance was rated as “poor.” 5.68 Horrendous – Bronson Arroyo 4.56 Horrendous Display articles that have been tagged with FIP

FIP appears in the followingBP GlossaryCategories:
  • Baseball Prospectus Exclusive
  • Pitching
  • Sabermetrics
  • Baseball Prospectus Exclusive

Basic Sabermetrics: FIP

Have you ever read an analytical piece on the internet or seen something on television where the writer or speaker used a statistic that you didn’t quite understand? If so, you are not alone. I’m in the same boat. We can utilize statistics and acronyms that everyone doesn’t comprehend without offering context or an explanation when we are at our worst. During our efforts to shift the conversation about baseball to something a little more analytical and objective (at least in some arenas), we’d like to provide some additional information to those who are new to the field of sabermetrics – or who need a refresher *- to help them get a better understanding of the subject.

  1. * – – – – – – – – – – – – – – A good approach, at the risk of sounding preachy, is to go back and re-evaluate your knowledge, or at least your perception of it, from time to time.
  2. The purpose of this post is to serve as the first in a series of papers aimed at assisting our readers in better understanding the complicated (and not-so-complex) statistics that we employ in our baseball analysis on this site.
  3. We hope to fill that library with a plethora of knowledge on sabermetrics statistics and concepts over the course of the next few months.
  4. We’ll try our best to address any questions you may have, so please leave them in the comments section of this page.
  5. In the comments section, please include the URL of a resource that you would want us to consider include.
  6. Andrew and Neil explored Fielding Independent Pitching in Episode 1, and they did a fantastic job of doing it.
  7. FIP (Fielding Independent Pitching), which stands for Fielding Independent Pitching, has gained significant popularity over the previous several years as an important metric for measuring pitcher performance.
What is FIP?

Fielding Independent Pitching (also known as FIP) is a measure that is intended to provide us with information about a pitcher’s overall performance. FIP is a measure of occurrences that are directly under the control of a pitcher, such as strikeouts, walks, and home runs. A calculation is then used to scale these occurrences to a figure that is quite similar to the one you would see for the event rate of extinction (ERA). It is a “rate” statistic, which is similar to how many runs a pitcher may give up per nine innings if certain peripherals were taken into consideration.

According to Voros McCracken’s study on Defense-Independent Pitching (DIPs), Tom Tango devised the formula for Fielding Independent Pitching (FIP), which was published in Baseball Prospectus.

How to Calculate FIP

In terms of sabermetric statistics, the formula for FIP is straightforward, at least in terms of its application. It is calculated in the following manner: FIP = ((13*HR) + (3*(BB+HBP)) – (2*K)) / IP + cFIP = ((13*HR) + (3*(BB+HBP)) – (2*K)) / IP + cFIP A quick review of the variables is in order: HR = home runs allowed, BB = walks allowed, HBP = hits by pitches allowed, K = strikeouts, and cFIP = league FIP constant A variable that varies from year to year, the league FIP constant is used to compare FIP throughout the league to the same standard of excellence as ERA.

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That constant was 3.048 in the year 2013.

Those correspond to the average linear weights of the occurrences in question.

Where to Find FIP

FanGraphs’ pitching statistics, which include FIP, are considered to be the gold standard. FIP is displayed on their basic player profiles and leaderboards*, which are updated on a daily basis during the season. Baseball Prospectus is another website where you may find it. * – – – – – – – – – – – – – – Among qualifying starting pitchers in the Major Leagues in 2013, Matt Harvey of the New York Mets held the league lead in FIP with a 2.50 mark. Who was the poorest among the qualifying starters for that particular season?

FIP is a term that is frequently used in baseball literature these days.

Using FIP in Analysis

So, what is the purpose of FIP? Most people believe that it represents what a pitcher’s earned run average “should” be. However, this is not entirely correct. FIP is scaled to ERA, and as such, its most useful application is as a basic description of the items that FIP measures, when placed in an ERA-scaled context. The earned run average (ERA) has additional factors that distort our ability to utilize it as a gauge of a player’s genuine talent level. ERA stats are likely to reflect a pitcher’s defense as well as his or her luck – especially when the sample size is limited.

  • FIP only records those events that are believed to be entirely within the control of the pitcher, reducing the amount of chance involved.
  • According to Tom Tango of The Book Blog: As a result, the goal of FIP is not to eliminate hits that are permitted or other non-HR contact plays, but rather to separate them into their own component (fielding-independent pitching, FIP).
  • And that is a nice outcome of our approach.
  • At the same time, FIP is not a legal document.
  • There are other pitchers that consistently underperform their FIP over extended periods of time.
  • If a pitcher’s FIP is a full run lower than his ERA in the midst of a season, there is a good possibility that the pitcher will have some positive regression and that their ERA will improve as a result of this.
  • Even though a season is a very small sample size, it is possible that regression will not occur – even throughout the duration of the entire season.

At the same time, it’s important looking at whether or not the pitcher has a track record of keeping his FIP below his ERA over a lengthy period of time. Perhaps there is something more at work that has to be taken into consideration, and FIP does not give the entire picture.

Associated Statistics

FIP-:FIP- is a statistic that compares a pitcher’s earned run average (FIP) to the league average (ERA). A FIP of 100 indicates that the player is on par with the league average. A FIP of 120 is a 20 percent decline from the league average. A FIP of 80 is a 20 percent improvement above the league average. Home runs permitted are replaced with home runs that should have been allowed in xFIP: Expected FIP (xFIP) was developed by Dave Studeman of The Hardball Times and is a regressed version of FIP.

PFIP: Predictive FIP (pFIP), developed by Glenn DuPaul over at The Hardball Times, is another modified FIP statistic that attempts to better precisely forecast future performance by reweighting the multipliers for the peripheral events and adjusting the constant from one season to the next.

This one attempts to account for the caliber of opposing batters in order to offer a FIP-scaled measure that takes into consideration the degree of difficulty of the game.

For More Information

The FanGraphs Library (also known as FIP) is a collection of fan-created graphs. The Book Wiki is a collaborative effort between. FANGraphs provided all of the statistics used in this article. Beyond the Box Score is managed by Bryan Grosnick, who is also the managing editor. You can follow him on Twitter, where he goes by the handle @bgrosnick.

More from Beyond the Box Score:

Follow @btbscore and @SBNationMLB on Twitter.

  • Shortstops
  • Shutdowns and meltdowns in 2013
  • And other observations from the market The year as a series of blunders
  • Wheeling and dealing in the first episode of The Shift
  • The significance of acquiring Nick Punto’s services

Stat to the Future: Move over, ERA, it’s time for FIP

While playing fantasy baseball, you may have heard experts discuss how a hot pitcher from the previous season is “due for regression based on their peripherals.” If you’ve ever played fantasy baseball, you may have heard experts discuss how a hot pitcher from the previous season is “due for regression based on their peripherals.” While there are many factors to consider when evaluating players who might cool off after winning the Cy Young Award or great pitchers who have had mediocre seasons, one of the most straightforward is a metric known as Fielding Independent Pitching, or FIP, which is short for Fielding Independent Pitching.

It has the appearance of a comic book sound effect: When Spider-Man shoots a web towards the Green Goblin, a bright bubble appears, stating: “FIP!” This is true of many other sabermetric statistics as well (in fact, you could probably say the same about most of them).

What is FIP?

FIP (Fielding Independent Pitching) is a statistic that is used to eliminate the impacts of fielding from the equation and only include the components of the game that the pitcher has control over, such as the strike zone. In order to evaluate a pitcher’s ability only on the basis of his or her ability to throw, it is necessary to remove fielders from the equation. Consider the following scenario: a pitcher allows three fly balls to the outfield. If the outfield behind the pitcher has outstanding range and all three fly balls are caught, the pitcher will be able to exit the inning with no earned runs on his or her record.

While identical fly balls and pitchers are involved, it is possible that due to the defense, the pitcher will wind up with two runs credited to their record, rather than none.

FIP is unaffected by balls in play, which are typically out of the pitcher’s control (although there is an exception to this rule, which I’ll address later in this article).

These outcomes are weighted according to their significance and then divided by the number of innings pitched, after which a FIP constant is applied. The FIP constant is calculated based on the league-wide FIP and the league-wide ERA, and it is the same for all pitchers in the league.

How to use FIP

If you’re acquainted with earned run average (ERA), then FIP is straightforward to understand: both FIP and ERA function on the same scale, with 5.00 being horrible, 4.00 being about average, 3.00 being good, and anything below 3.00 being in the Cy Young range. If you were to compare the FIP of a large number of pitchers to their ERA, you would discover that many of them have ERAs that are very near to their respective FIPs. John Smoltz finished his career with an earned run average of 3.33 and a fielding percentage of 3.24.

  • Pedro Martinez ended with an ERA of 2.93 and a WHIP of 2.91 in two seasons.
  • As a result, why not utilize FIP rather than ERA if they are basically equivalent in the long run?
  • Ordinarily, looking at an individual pitcher’s ERA and FIP over the course of a season will give you a sense of whether pitchers are over or underperforming.
  • It looked like Santiago was overperforming since he had done a bad job on the areas of the game that pitchers are expected to control: a FIP of 3.96 shows that he didn’t get many strikeouts and allowed a lot of walks, home runs, and HR/FB ratios, among other things.

Pitchers are not often able to maintain such a huge disparity between their ERA and FIP for extended periods of time, so it was no surprise that Santiago pitched to a substantially higher ERA in the second half of 2015 than he did in the first half of the year (5.47 in the second half as opposed to 2.33 in the first half).

In 2016, Michael Pineda threw to a 5.38 ERA and 3.77 FIP in the first half of the season, thus it wasn’t unrealistic to anticipate Pineda to throw to a lower ERA in the second half of the season.

Warnings about FIP

We’ve already discussed the faults with ERA, but there are a few concerns with FIP that we should mention as well. For example, FIP does a terrible job of judging pitchers who throw ground balls or fly balls and do not strike out a large number of hitters. A ground-ball or fly-ball pitcher is primarily reliant on the support of their defense to keep them in the game. Their approach is to get batters to make weak contact so that they may be readily fielded by the defense. Despite the fact that it is a smart plan, FIP penalizes them for depending on their defense.

  • FIP may also be used to penalize pitchers by holding them accountable for home runs when there is a significant element of good fortune involved.
  • When it comes to fly balls, there’s a statistic called HR/FB percent that indicates what proportion of fly balls that are allowed by a pitcher end up leaving the park.
  • Most pitchers have an HR/FB percent of approximately 10 percent, while an unlucky pitcher may have an HR/FB percent of 16 percent (like Clayton Kershaw is doing this season).
  • Kershaw’s unluckiness is irrelevant to FIP, and as a result, he is undervalued as a result.
  • FIP is a highly useful statistic that, when utilized correctly, can be incredibly successful in determining a pitcher’s skill level and projecting how good of a pitcher they will be in the future if they are currently on the mound.

Do you have any queries concerning statistics, sabermetrics, or advanced analytics? Please contact us. Do you want to argue the merits of the case? Send a tweet to @John Edwards_ to get your statistics doubt dispelled.

MLB Advanced Stats: What is FIP/xFIP?

FIP (Fielding Independent Pitching) is a measure of a pitcher’s performance on the mound that is similar to ERA.

FIP Definition

FIP, on the other hand, only counts occurrences over which pitchers have complete control, including as strikeouts, walks, home runs, and balls in play. When a ball is hit into play, fielding is practically meaningless, as pitchers have little influence over what happens after the ball is hit into play. Instead, the FIP calculates what a pitcher’s ERA would look like if he had league-average defense and luck over his whole career. If a pitcher has a high average number of balls put in play, his FIP is likely to be lower than his ERA, which is a good thing.

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What About xFIP?

There is a comparable statistic to FIP called xFIP, which stands for Expected Fielding Independent Pitching and is used in the same way as FIP. Although, like FIP, xFIP is a more accurate predictor of a pitcher’s ability in the future than ERA, the two numbers differ in the manner in which they take home runs into consideration. Instead of using the number of home runs allowed in its equation, FIP employs the home run rate, which is determined by dividing the season’s Home Run to Fly Ball (HR/FB) rate by the number of home runs allowed in the calculation.

Despite their differences, both are intended to provide a more realistic picture of a pitcher’s performance than traditional measures such as the earned run average (ERA).

FIP and xFIP in Betting

If you’re looking for value from a betting standpoint, FIP and xFIP may be quite helpful when seeking to separate a pitcher’s underlying performance in order to uncover value game to game. The fact that it doesn’t take fielding or chance into consideration makes it particularly suited for exploiting certain imbalances on the pitch. The wOBA is used in our Sean Zerillo’s model and projections for betting on Major League Baseball games, which you can learn more about by clicking here. What would you say is the overall quality of this article?

Why We Need to Be Cautious Using FIP

Peanut butter and jelly, biscuits and gravy, burgers and fries. ERA and FIP are all delicious combinations. It is now almost always seen alongside the most conventional technique of rating an individual pitcher, the earned run average (ERA), a measure that was earlier mostly unknown. In fact, some baseball commentators are going a step farther and referring to FIP as the only measure of success instead of ERA. In all likelihood, we are witnessing the transition from ERA to FIP as the “go-to” pitching metric.

Wrong.

It’s past time to put the brakes on the FIP train and re-examine exactly what FIP is and how it should be utilized in the most effective manner possible.

In the words of Fangraphs, Fielding Irrespective Pitching (FIP) is “a statistic that assesses a pitcher’s run prevention independent of the performance of the defense.” Essentially, the goal behind FIP is to track the outcomes of a plate appearance that can only be controlled by the pitcher himself, such as strikeouts, walks, hit by pitches, and home runs, among other things.

  • When opposed to the earned run average (ERA), the fielding-independent pitching (FIP) statistic performs a far better job of analyzing how well a pitcher did rather than merely calculating how many earned runs were scored while the pitcher was on the hill.
  • When ERA is used as a measure of predicted regression, positive or negative, FIP is used as a measure of expected regression, positive or negative.
  • a sharply hit ball down the line that landed foul by inches or a shot to straight-away center that the center fielder caught with his back against the wall).
  • Since its inception, the Fielding Independent Pitching (FIP) statistic has shown to be extremely accurate in projecting a pitcher’s development or decrease, frequently at a common review point throughout the season, such as after the first month or at the All-Star break.
  • For example, FIP has been misused to compare pitchers, evaluate pitchers’ career progressions, project performance in future seasons, replace BABIP, defend pitchers who do not belong in the major leagues, and evaluate relievers, to name a few of the ways in which it has been misunderstood.
  • When comparing pitchers, FIP should not be used because the logic goes as follows: Pitcher A has a lower FIP than Pitcher B, which implies that he is the better pitcher.
  • Because FIP attempts to compensate for variety in defense, luck, and sequence of events that an individual pitcher experiences, to compare two pitchers who are not pitching with the same defense, luck, and sequence of events is irrational.

When comparing pitchers from different teams it becomes even more obvious why FIP cannot come into play.

When comparing a pitcher of near equal caliber from the Diamondbacks to a pitcher on the Phillies, the pitcher on the Phillies will almost certainly have the lower FIP, but that does not mean he is the better pitcher.

For example, pitchers like Max Scherzer and Clayton Kershaw are going to have very low FIPs because they are strikeout pitchers who will set down 8-10 guys on strikes on an average day on the bump.

While the FIP model would argue that Hendricks and Godley are the beneficiaries of good defense behind them, although this may be partially true, it also takes skill and outstanding control to be able to induce weak contact.

Why FIP Cannot Be Used To Evaluate Pitchers’ Careers: The Logic: Pitcher A had a career FIP of 3.50 therefore he had a very good career.

Because no pitcher will pitch on a team with the exact same roster for the entire span of his career, and most pitchers will pitch for at least two different teams, FIP becomes meaningless when applying it to a pitcher’s career.

The odds that a pitcher pitches 15 years without ever getting a favorable bounce, or without ever getting help from a fabulous defensive play behind them, or without ever getting out of a jam are essentially zero.

However, if this is not the case, it is irrational to suggest that the career ERA of the pitcher at hand was somehow “skewed” due to a difference in ERA and FIP.

Why This Logic Is Flawed: One of the common misconceptions about FIP in general is that it is a projection, but FIP is, on the contrary, a predictive statistic.

However, to evaluate a pitcher after a full season and use FIP to project his performance next season does not make sense.

Because the elements that the pitcher could not control vary from season to season and will normally balance out over a long period of time, any significant difference in FIP for a full season is almost certainly due to the percentages of outs generated by the pitcher on balls in play versus via strikeouts.

  1. Hendricks’s K/9 was only 8.05 and his HR/9 was only 0.71 – this would explain why his FIP was so significantly higher than his ERA.
  2. While the fact that his ERA next season was 3.03 might seem contradictory to my argument, if we look at some of his other statistics we can see that the jump in ERA had nothing to do with his defense, luck, or sequencing.
  3. That is exactly why every pitcher that has one season with a sub-3.00 ERA is not enshrined in the Hall of Fame – maintaining that kind of success as a pitcher is hard.
  4. When a pitcher has the kind of ERA-FIP discrepancy that Hendricks had in 2016, it is not reasonable to use FIP as a projection of how he will perform in future seasons.
  5. Why FIP Cannot Be Used to Replace BABIP The Logic: Because FIP can tell us if a pitcher is predicted to improve or decline, there is no need for BABIP which serves the same purpose.
  6. Just like the best pitchers of all-time tend to have a career BABIP of.300 or lower, the best hitters of all-time tend to have a career BABIP of.300 or higher.
  7. The reason for Cabrera’s high BABIP is simply that he is one of the greatest hitters of all-time that has hit the ball hard throughout his career which makes it much harder for the defense to field.

The fact that BABIP solely takes into account the variety of balls in play from a pitcher, while FIP counts every ball in play as the same shows how these two statistics are extremely different and should be treated as such.

However, his FIP is 6.55 so he’s clearly just been the subject of terrible luck, lousy defense, etc.

Unfortunately, in the case of pitchers who are experiencing epic struggles, the use of FIP becomes extremely limited.

It is automatically assumed by the FIP model that bad defense, bad luck, and bad sequencing are all impacting a pitcher’s performance to some level whenever he is giving up hits at a significantly greater rate than he is getting outs on balls in play, even though this is extremely unusual.

Last season, the demotion of Jon Gray to AAA was criticized because he had a 5.97 RA9 but only a 3.10 FIP.

While many people used his FIP to justify his poor performance, his 2.72 BB/9, 36.1 Hard percent, and 1.41 HR/9 were much more indicative of why he was struggling, although it should be noted that pitching in Coors Field almost always results in a higher HR/9 than normal.

Even though Gray shown glimpses of brilliance during the previous season, it was his inconsistency that led to his demotion, not any sort of “poor luck” as some who mentioned his FIP would have you believe.

Why This Line of Reasoning Is Incorrect: Tradition dictates that every starter will open the game with no runs on the board for the opposing team, every starter will start the game against the other side’s leadoff hitter, every starter will start the game with no runners on base for the opposing team, and so on.

  • However, when it comes to relievers, there is no such consistency to be seen.
  • Despite the fact that there are two drastically different situations in which a pitcher may find himself, FIP continues to treat every ball in play in the same manner.
  • In the same way, a double in the first scenario would have little impact on the team’s chances of winning, but a double in the second scenario would have a significantly greater impact on their chances of winning.
  • However, because FIP takes into account all balls in play in the same way, this statistic can be biased substantially in favor of relievers.
  • In reality, during the course of Rivera’s career, the average difference between his ERA and his FIP was 0.58.
  • More recently, Blake Treinen posted a 1.82 earned run average after having a 0.78 earned run average last season, making him probably the finest reliever in the game.
  • The fact that the scenario in which a reliever enters the game can change so greatly, and that he is throwing substantially less innings each season than starters, it is unreasonable to apply the same FIP statistic to relievers as we do to starters is illustrated by this chart.
  • There is one takeaway from all of this: we must be extremely cautious in how we utilize FIP because of various faults in the statistical model that make it impossible to employ in some scenarios.
  • The FIP of a pitcher may be incredibly valuable in predicting regression and determining whether or not a pitcher’s production is sustainable.

As with any baseball statistic, it does not convey the entire story and should never be relied upon in isolation. If you like this post or have any questions or comments, please feel free to contact me through Twitter (@zorianbaseball) or Facebook.

What Is FIP in Baseball? The Ultimate Guide to the Statistic

If you spend a lot of time around baseball, one of the things you’re going to hear is that you want pitchers to have low earned run averages. It appears to be straightforward, doesn’t it? Well, maybe not, because different pitchers throw in front of various caliber defenses and in ballparks with varying pitching circumstances, leading to the development of another statistic to assess pitchers: the Fielding Independent Pitching (FIP). So, what exactly is Fielding Independent Pitching (FIP) in baseball?

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The statistic attempts to exclude all other sorts of outcomes in order to account for a pitcher’s excellent or bad luck on the field.

Please don’t be concerned; we will go into further information about FIP later on in this article.

Why Is FIP Used?

So far, we’ve learned that FIP only takes into account the number of home runs and unintentional walks a pitcher allows, as well as the number of hitters he hits, while also taking into account the number of batters he strikes out. But why do they exclusively utilize these numbers in their presentations? Due to the fact that home runs, walks, and strikeouts are the so-called “three real outcomes,” which are so named because the only elements involved are the pitcher and hitter, FIP only considers a small range of data.

Hit-by-pitches are included in the FIP calculation in addition to the three real outcomes since, like walks, the batter ends up on first base and is completely the product of the pitcher’s wildness.

Specifically, according to Fangraphs, researchers revealed that a pitcher’s luck, which is determined by whether or not a hit ball is fielded (which is beyond of his control), may vary dramatically from season to season, even within the same league.

To put it another way, the researchers discovered that a pitcher’s opponent batting average on balls in play, often known as BABIP, might be extremely inconsistent.

How Do You Calculate FIP?

Now that FIP has been described and appears to be very basic, how do you go about calculating it? As a result, it’s a little more complicated than a regular ERA calculation, because it requires eliminating components from a traditional stat line as well as correcting for league average each season. A pitcher’s FIP is calculated as follows: FIP = ((13*HR)+(*(unintentional BB+HBP))-(2*strikes out))/innings thrown + league constant + league constant. Another equation will be required in order to determine the constant: In baseball, the FIP Constant is calculated as follows: league ERA minus (13*league home runs) minus (3*(league walks+league home run batters) minus (two*league strikeouts)) divided by the number of league innings pitched.

  1. Let’s take this one step at a time.
  2. Since for the multipliers (for example, 13*home runs or 2* strikeouts), they are allocated depending on the influence they make on a game, as a home run will normally have a greater impact than a walk or a strikeout will.
  3. Because this number, once again, only takes into account the three genuine outcomes (as well as HBP), it is not nearly as volatile as most other statistics, with no discernible peaks and troughs seen over shorter time periods.
  4. We can complete the calculation by using the Fangraphs table for the league constant (3.214), which looks like this: In baseball, FIP is calculated as ((13*19 home runs)+[3*(43 unintentional BB+7 HBP))-(2*255 strikeouts))/204 innings thrown plus the league constant of 3.214.

As a consequence, his FIP is at 2.67, which is lower than his actual ERA of 2.43.

What Is Considered a Good FIP?

In a similar vein to the traditional ERA, a pitcher wants to have a low FIP since it is a good predictor of future success in the field. In addition, FIP may be rated on a scale comparable to that of ERA in terms of what is considered excellent and bad. A FIP below 4.00 is typically considered good, whereas a FIP above 5.00 is considered terrible, and a FIP of 3.00 or below is considered great. FIP is also created such that the leaguewide FIP equals the league ERA, which is why the constantly changing constant must be factored in when comparing years to years.

  1. This is due to the fact that the FIP is designed to better reflect leaguewide pitching circumstances in a particular year.
  2. The result has been that, from 2000 to 2019, the league’s top FIP leaders have had statistics ranging from 1.81 (Clayton Kershaw, 2014) to 3.26 (Corey Kluber, 2016), while the league’s top ERA leaders have had figures ranging from 1.66 (Zack Greinke, 2015) to 3.05 (Alex Wood, 2018).
  3. Because FIP is intended to be more stable on an individual level from year to year, but ERA may be wildly fluctuating owing to a number of circumstances, it is usual for pitchers to lead in either ERA or FIP, but not both, throughout a season.
  4. A pitcher’s ERA may be greatly impacted by chance, and as a result, it is more likely to fluctuate from year to year.
  5. Since the rates of strikeouts and home runs have both increased in recent years, those are the two rates that have been the most closely monitored recently.

What Is xFIP?

As previously stated, a rapid increase in a pitcher’s home run rate might have a negative impact on his or her FIP. As a result, the extremely brilliant folks who come up with new numbers have made a few of adjustments to FIP to account for circumstances that can distort it, possibly in a deceptive manner. Expected FIP is an extra metric that should be considered (xFIP). It is a measure of FIP that compares a pitcher’s rate of home runs to fly balls (HR/FB or home run rate) with that of the league average in order to calculate the expected FIP if the pitcher’s home run rate mirrored that of the league average.

  • Pitchers who allow a substantial variation in the number of home runs they allow from one season to the next or who pitch in tiny ballparks where balls that would normally stay in the yard leave the yard on a regular basis may find xFIP to be particularly valuable.
  • It is nearly identical to the FIP formula (including the constant), with the exception that the pitcher’s raw total of home runs is replaced by ((13*(Fly balls * league HR/FB percent))) in the xFIP formula.
  • So Yu Darvish of the Chicago Cubs, who allowed a Major League Baseball-worst 22.8 percent of his fly balls to leave the yard, produced an exorbitantly high xFIP of 3.39, but his actual FIP was a far more modest 4.18.
  • However, xFIP is not without flaws, since it does not take into consideration the quality of contact produced by pitchers in their pitches.
  • While the list of hardest contact does not have nearly as strong an association with HR/FB rates as the list of hardest contact, four of the six pitchers who allowed the hardest contact did had HR/FB rates that were higher than the league average.

While xFIP may be used to equalize FIP among pitchers with widely disparate HR/FB rates, there is another statistic that goes a step further in this regard.

What Is FIP-?

There is another relative to FIP that is intended to address the issue of comparing pitchers who pitch in ballparks that differ in their willingness to accommodate pitchers’ needs. FIP Minus, often known as FIP-, is a statistic that takes a pitcher’s FIP and compares it to the park characteristics of that pitcher’s home park, and then places it on a scale from 0 to 100, where 100 represents the average of the league. FIP-, in contrast to FIP and xFIP, is not displayed in a manner comparable to that of a conventional ERA.

However, one notable distinction is that the scales are oriented in the opposite direction.

To put it another way, if a pitcher had an ERA+ of 105 and a FIP- of 95, he would be 5 percent better than the rest of the league in each of those categories.

Using park factor, a Colorado Rockies pitcher would receive a positive adjustment to his or her earned run average if he or she pitched in a stadium that had a park factor of 118 (18 percent more offense than average) in 2019, whereas a San Francisco Giants pitcher would have their or her earned run average negatively adjusted if they pitched in a stadium that had a park factor of 90.

In this context, with 100 as the average, a FIP- of 90 or lower is considered excellent, while anything above 110 is considered poor.

How Reliable Is FIP?

Following this, the question arises as to how dependable FIP is in evaluating how successful, or rather, how effective a pitcher should be in assessing his or her effectiveness. The answer is that it is superior to merely looking at a pitcher’s earned run average on its own. FIP is an effective tool for identifying warning indications that a pitcher is either over- or underachieving over a shorter period of time, and it provides a more accurate estimate of their genuine capabilities. Having said that, the fact that FIP does not account for different types of pitchers is a flaw in the system that must be acknowledged.

Furthermore, certain players have the ability to “break” FIP, if you will.

Rivera pitched for 19 years, collecting up saves (including a career-high 652 in the process) with virtually one pitch: a lethal cutter.

Instead, he used that cutter to bore in on right-handed batters or to draw left-handed hitters away from him, resulting in poor contact.

The fact that strikeouts are preferred over weak contact has resulted in Rivera posting an ERA that was lower than his FIP in 14 of his 19 seasons, including five seasons in which his ERA was more than a run lower than his FIP in total.

However, he also had a 2.21 earned run average, which was better than his FIP by more than half a run.

However, for four consecutive seasons, he has ranked near the top of the league in terms of average speed.

(including three seasons beating it by at least half a run).

On the other side, there are players like John Burkett, a good pitcher with 166 career victories who retired in 2003 after a long and successful career.

His career FIP came in at a respectable 3.85, but his career ERA came in at 4.31, over half a run higher than his career FIP.

In reality, there is no simple reason, but the most easily available one is that the pitcher allowed a large number of hits to remain in the yard.

Though not without flaws, fan-created content (FIC) has made its way closer to the mainstream as more and more people recognize its value.

Who knows what will happen? Perhaps, in the future, the computation can be simplified to better catch pitchers like Kyle Hendricks and John Burkett who don’t exactly “fit” the formula, as has been the case in the past.

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