Wins Above Replacement

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Win a Replacement Above or Win a Top Substitute , commonly abbreviated as WAR or WARP , is a non-screen printing -standard baseball statistics developed to summarize "player's total contribution to his team". The player's WAR score is claimed as an additional number of wins his team has achieved over the expected number of team wins if the player is replaced with a replacement player: players who can be added to teams with minimal cost and effort.

Individual WAR values ​​are calculated from the number and success rate of field actions by players (in batting, baserunning, fielding, and pitching), with higher scores reflecting greater contributions to team success. The value of WAR also depends on what position the player is playing, with more values ​​will be weaker about a position like a catcher than a position with a strong blow like the first base. The high WAR value built by the player reflects a successful performance, large amount of play time, or both.

For example, Fangraphs assesses the regular 2014 season performance of Clayton Kershaw at 7.2 WAR, showing his team won about seven matches more than expected if the inning was paired by a substitute level player. Kershaw achieved this high WAR total by doing a lot of innings while maintaining a high strikeout rate and low home run and walk levels.

Video Wins Above Replacement

Overview

The basis for WARS values ​​is the estimated number of runs contributed by players through offensive actions such as batting and base running, and running is denied to opposition teams by players through defensive acts such as fielding and pitching. Statistics such as on-base weighted averages (WOBA), main zone ratings (UZR), running base (UBR), and independent defense pitching statistics (DIPS) measure the effectiveness of players in creating and storing tracks for their teams, on performances per -pel or per-inning. These statistics can be multiplied by the player's playing time to provide an approximate offensive and defensive amount that contributes to their team.

The additional division contributes to the team that generated an additional win, with 10 expected trajectories equal to about one win. Therefore, a value of 1.0 WAR for player signifies a contribution of about 10 times more than a substitute level player, over a period of time. The substitute level player is defined by Fangraph as a 17.5 contribution less than the average league performance player, over 600 appearance plates. Therefore, the WAR player has contributed about -7.5 runs relative to the average over the same number of plate appearances, 2.0 WAR players have contributed 2.5 runs, and 5.0 WAR players have contributed 32.5 walk.

For individual players, WAR scores can be calculated for a single season or season section, for multiple seasons, or across a player's career. Collective WAR values ​​for some players can also be estimated, for example to determine the contribution a team receives from an outfielder, pitcher relief, or from a specific position such as a catcher. It is also possible to extrapolate future WAR values ​​from previous player performance data.

Maps Wins Above Replacement

Calculation

There is no clearly defined formula for WAR. The sources that provide statistics calculate it differently. These include Baseball Prospectus, Baseball Reference, and Fangraphs. All of these sources publish the methods they use to calculate WAR, and all use similar, basic principles to do so. The version published by Baseball Prospectus is named WARP, which by Baseball Reference is named bWAR or rWAR ("r" derived from Rally or RallyMonkey, nickname for Sean Smith, which implements the statistics version of the site) and that for Fangraph it is named fWAR . Compared with rWAR, fWAR calculations emphasize peripheral statistics.

WAR values ​​are given the same scale for pitchers and batters; that is, pitchers and player positions will have roughly the same WAR if their contribution to their team is equal. However, the values ​​are calculated differently for the pitcher and player position: the player's position is evaluated using statistics for fielding and hitting, while pitchers are evaluated using statistics related to opponent's batter hits, runs, and strikeouts in the Fangraphs version and run allowed per 9 innings with team's defense adjustment for Baseball Reference version. Because independent WAR frameworks are calculated differently, they do not have the same scale and can not be used interchangeably in an analytical context.

Player position

Baseball Reference

Baseball Reference uses six components to calculate WAR for positioning players: The components are batting run, baserunning run, run added or lost due to grounding into double play in double play situations, running in the field, walking position setting, and level of walking alternatives (based on play time). The first five factors are compared to the average league, so the value 0 represents the average player.

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Istilah ${\ displaystyle P_ {runs} -A_ {runs}}  ÂÂ$ dapat dihitung dari lima faktor pertama, dan istilah lainnya dari faktor yang tersisa.

Batting berjalan tergantung pada Runed Above Average (wRAA) berbobot, tertimbang untuk pelanggaran liga, dan dihitung dari wobA.

${\ displaystyle wRAA = {\ tfrac {wOBA-.320} {1,25}} * (AB BB HBP SF SH)}  ÂÂ$

dimana

${\ displaystyle wOBA = {(\ alpha _ {1} * uBB \ alpha _ {2} * HBP \ alpha_ {3} * 1B \ alpha _ {4} * 2B \ alpha_ {5} * 3B \ alpha_ {6} * HR \ alpha_ {7} * SB- \ alpha_ {8} * CS) \ over (AB BB-IBB HBP SF)}}  ÂÂ$

Here, "AB" is the number of bats, "BB" is the base number of the ball ("uBB" is the unintentional basis on the ball and "IBB" is the intentional basis on the ball), HBP how many times beaten by the pitch, "SF "number of sacrifices hits," 1B "number of single hits," 2B "double amount," 3B "three times the amount," HR "home run number," SB " "the number caught on stealing. ${\ displaystyle \ alpha _ {1}}$ for ${\ displaystyle \ alpha_ {8}}$ represents the weighting coefficient. Baseball Reference removes batting pitcher results from its data, calculates the linear weight and WOBA coefficients for each league, then measures the value for each league and season.

Position adjustment is a value that depends on the player's position: 10.0 for catcher, -10 for first baseman, 3.0 for second baseman, 2.0 for third baseman, 7.5 for shortstop, -7.5 for left fielder, 2.5 for center fielder, -7, 5 for the right fielder, and -15.0 for the designated hammer. These values ​​are set with the assumption of 1,350 rounds played (150 games out of 9 innings). The player's position adjustment is the sum of position adjustments for each position played by players adjusted for the number of games played by players in that position, normalized to 1,350 innings.

Fangraphs

The Fangraph formula for positioning players involves offense, defense, and running bases. This is measured using a weighted average Runed On Top, Ultimate zone rating (UZR), and Ultimate base running (UBR), respectively. These values ​​are adjusted using park factors, and position adjustments are applied, resulting in a "added value above the player's average". For this added value scale to reflect the player's value compared to the substitute level player, which assumed 20 runs below the average per 600 appearance plate. The four values ​​are measured in the path.

${\ displaystyle fWAR = wRAA UZR Position {\ tfrac {20} {600}} * PA}$

Position adjustment is a value that depends on the player's position: 12.5 for catcher, -12.5 for first baseman, 2.5 for second or third baseman, 7.5 for shortstop, -7.5 for left fielder, 2.5 for a fielder center, -7.5 for right winger, and -17.5 for designated hitters. These values ​​are scaled by the number of games played by players in each position.

Pitcher

Baseball Reference

Baseball reference uses two components to calculate WAR for pitcher: Runs Allowed (both received and unaccepted) and Pitched Innings.

Fangraphs

Rather than focus on the actual walk allowed, Fangraphs uses FIP as their main component to calculate WARs as they feel more accurate.

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Analysis

In 2009, Dave Cameron stated that the FWAR did "an impressive job of projecting victory and loss". He found that the team's projected records based on the fWAR and the team's actual records had a strong correlation (correlation coefficient of 0.83), and that each team was in two standard deviations (= 6.4 wins).

In 2012, Glenn DuPaul conducted a cumulative rWAR regression analysis of five randomly selected teams per season (from 1996 to 2011) against the total wins the teams won for the season. He found that both are highly correlated, with a correlation coefficient of 0.91, and that 83% of the variance in victory is described by fWAR (R ² = 0.83). Standard deviation is 2.91 victory. The regression equation is:

${\ displaystyle Wins = 52.7 0.97 * fWAR}$

yang dekat dengan persamaan yang diharapkan:

${\ displaystyle Wins = 52 fWAR}  ÂÂ$

where a replacement-level team is expected to have a 0.320 percentage win, or 52 wins in the 162 season.

Untuk menguji FWAR sebagai alat prediktif, DuPaul melakukan regresi antara pemain kumulatif tim WAR dari tahun sebelumnya dengan kemenangan yang diraih tim untuk tahun itu. Persamaan regresi yang dihasilkan adalah:

${\ displaystyle Wins = 63,83 0,68 * fWAR}  ÂÂ$

which has a statistically significant correlation of 0.59, which means that 35% of the variance in team victory can be accounted for by the cumulative fWAR of its players from the previous season.

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Use

WAR is not recognized as an official stat by Major League Baseball or by the Sports Bureau of Elias.

ESPN publishes the Baseball Reference of WAR version on the statistics page for player and pitcher positions.

Bill James states that there is a bias that benefits players from previous eras because there is a greater difference in skill levels at the time, so "best players are farther than average than now". That is, in modern baseball, it is more difficult for a player to surpass his peers than in the 1800s and the dead ball and the live-ball era of the 1900s.

Towards the end of the Major League Baseball season of 2012 and thereafter, there is much debate about which players should win the Major Baseball Most Most Valuable Player Award for the American League. The two candidates considered by most authors are Miguel Cabrera, who won the Triple Crown, and Mike Trout, a rookie who led Major League Baseball at WAR. The debate focuses on the use of traditional baseball statistics, such as RBI and home runs, and sabermetric statistics such as WAR.

Cabrera leads the American League in average batting, home runs, and RBI, but Trout is regarded as a more complete player by some. Relative to the average player, Cabrera contributed an extra 53.1 through batting, but -8.2 through defense and -2.9 through baserunning, while Trout contributed 50.1 batting runs, 13.0 defensive runs, and 12.0 baserunning runs. Cabrera, the only one of two players whose teams enter the postseason, will win an award in a landslide, with 22 of the first 28 voices of the American Baseball Writers Association. He and Trout post the same season in 2013; Cabrera again won the MVP. Dave Cameron disagrees, in the article fangraphs.com:

Over the past two years, we've seen the best two seasons in baseball history, and they are basically unknown to the organization assigned to record history. We have been fortunate enough to see Mickey Mantle in his time in modern times, and instead of celebrating it, we have spent Novembers explaining why his team-mate's inferiority should make him not win an individual award.

Some sabermetricians "have distanced themselves from the importance of a single-season WAR value" because some defensive metrics incorporated into WAR calculations have significant variability. For example, during the 2012 season, Toronto Blue Jays employs an infield shift against some left-handed batters, such as David Ortiz or Carlos PeÃÆ'Â ± a, in which Britten Lawrie's third baseman will be assigned to the shallow right field. This results in a very high Defensive Runs Saved (DRS) for Lawrie, and hence a high RWAR, which uses DRS as a component. Ben Jedlovec, an analyst for DRS Baseball Info Solutions creator, said Lawrie "made dramas in places where very few third basemen made the drama" due to "a very optimum position by Blue Jays". Other fielding metrics, Ultimate zone ranks (UZR), use DRS data but do not include runs saved as a result of shifting.

Jay Jaffe, a writer for Baseball Prospectus and a member of the American Baseball Writers Association, adapted the WAR for statistics he developed in 2004 called "Jaffe Wins Above Replacement Score," or JAWS. The average metric of a WAR career player with its seven-year peak (not necessarily a year in a row). The latter number is then used to measure the feasibility of the player being inducted into the Baseball Hall of Fame by comparing it to the average JAWS of Hall of Fame players in that position. Baseball's explanation of JAWS says, "The stated purpose is to raise the Hall of Fame standard, or at least to defend them rather than erode them, by recognizing players who are at least as good as the Hall of Fame in that position, using means through which longevity is not one the only determinant of eligibility. "

For example, on August 5, 2013, the third baseman AdriÃÆ'¡n BeltrÃÆ' Â © has accumulated 68.8 War, and 44.9 WAR of the best seven-season combinations. Averaged together, these figures give BeltrÃÆ'Â © a JAWS of 56.8, which ranks slightly higher than the average JAVS 55.0 for the 13th thirteenth basement currently in the Hall of Fame. With the size of JAWS, BeltrÃÆ'Â © is a decent candidate for the Hall of Fame.

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See also

• Value over substitute - another metric to measure player contributions

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Note

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References

Source of the article : Wikipedia