Published: June 25, 2021
Updated: August 14, 2026 at 07:35PM
Welcome
Welcome to my baseball season data analysis. This page offers interactive visualizations and detailed data tables that capture team and player performance throughout Major League Baseball (MLB) seasons. You can explore cumulative wins, run differentials, scoring trends, and advanced player statistics such as Wins Above Replacement, on-base plus slugging, and earned run average. The charts and tables highlight team momentum, offensive and defensive strengths, and individual contributions, providing a clear view of which teams and players are excelling over time.
All data are sourced from Baseball Reference and updated daily during the regular season, allowing you to track changes as the season unfolds. Whether you’re a fan, analyst, or fantasy baseball player, these visualizations offer an accessible, data-driven perspective on MLB performance. I hope you find these visualizations and data tables helpful in understanding the current MLB season. Thank you for visiting the page.
Executive Summary1
Recent performance data reveals a tight race at the top of the league, with the Milwaukee Brewers (75 wins), Tampa Bay Rays (74), Atlanta Braves (73), and Los Angeles Dodgers (73) separated by just two wins. Two patterns are particularly notable: the paradoxical profile of the Dodgers, whose elite record accompanies a negative median run differential, and the emergence of the NL Central, where the Brewers and Cubs are winning with distinct strategies of run prevention and offense, respectively.
The Los Angeles Dodgers present a fascinating case study in team performance, pairing a premier record (73-49) with atypical run-scoring metrics. Despite their high win percentage (59.8%), the team’s median run differential is -1, indicating that in a typical contest, they have been outscored. This contrasts sharply with other top teams like the Brewers, Rays, and Braves, all of whom have a median run differential of +1. The Dodgers’ data also show a relatively high standard deviation in runs allowed (3.63), which points to greater inconsistency in their run prevention efforts.
In the National League Central, the Milwaukee Brewers and Chicago Cubs are demonstrating divergent paths to elite status. The Brewers have amassed a league-leading 75 wins primarily through stout pitching and defense, holding opponents to a median of just three runs per game, tied for the lowest mark in baseball. In contrast, the Chicago Cubs (71-51) have built their success on a potent lineup with an exceptionally high ceiling, having scored 23 runs in a single game this season. This offensive strength is exemplified by Pete Crow-Armstrong, who leads all MLB position players with a 7.4 WAR.
Offensive consistency is a key separator for contending teams. The St. Louis Cardinals (61-60) and New York Yankees (68-53) show predictable outputs with low standard deviations in runs scored (2.61 and 3.04, respectively), though both have a -1 median run differential. Conversely, the Chicago White Sox exhibit high variability (3.77 SD in runs scored), leading to scoring outbursts like their 22-run game but also greater inconsistency.
On the pitching side, the data highlight how effective run prevention can keep a team competitive, even with a less formidable offense. The Seattle Mariners (57-65) serve as a prime example, allowing a median of only three runs per game with a league-best 2.72 standard deviation in runs allowed, a testament to their consistent pitching staff. This stability suggests their sub-.500 record is more attributable to an offense that scores a median of four runs. Conversely, the Athletics (47-74) continue to struggle on the mound, allowing a median of five runs with a league-high standard deviation of 4.35.
Finally, the data reveal thin margins for teams hovering around the .500 mark. Clubs like the Texas Rangers (60-62), for example, hold a positive median run differential of +1 but have little room for error. For such teams, consistent performance, particularly from their pitching staff, is critical for any postseason aspirations, as even minor regressions could significantly alter their trajectory.
Cumulative Wins
This figure presents cumulative wins by MLB team during the current season. Each panel corresponds to a single team, with the x-axis representing the progression of the season by date and the y-axis showing the total number of wins accumulated to date. This display helps illustrate how quickly teams have been winning games relative to one another and provides a clear view of momentum, slumps, or sustained success over time. Because the plot updates automatically as new data become available, it reflects each team’s current position in the season at the time of the most recent refresh.
Graph Prepared By: Isaac H. Michaels, DrPH
Data Source: www.baseball-reference.com
Head-to-Head Records
This figure presents a cross-tabulated heat map detailing the head-to-head performance of each MLB team during the current season. Each row corresponds to a specific team, while the columns represent their respective opponents. The intersecting cells contain text displaying the exact win-loss record for that specific matchup. Additionally, the background of each cell is colored according to the head-to-head differential using a diverging color scale, where positive values—indicating a favorable margin—and negative values—indicating an unfavorable margin—are visually distinguished. Teams whose rows feature a higher concentration of blues demonstrate broader dominance across the league. In contrast, rows saturated with reds highlight teams struggling against a variety of opponents. This visualization offers a comprehensive, at-a-glance snapshot of individual matchup advantages, intra-league parity, and overall team competitiveness to date.
Graph Prepared By: Isaac H. Michaels, DrPH
Data Source: www.baseball-reference.com
Runs Scored vs. Runs Allowed
This figure plots runs scored against runs allowed for each MLB team during the current season. Each panel corresponds to a single team, with individual points representing games. Points above the diagonal dashed line indicate games in which the team scored more runs than it allowed (wins), while points below the line indicate losses. Points are colored according to game outcome to distinguish between wins and losses. Teams with a larger number of points above the line tend to outscore their opponents more consistently, reflecting stronger overall performance. The figure provides a visual summary of each team’s run-scoring and defensive patterns across all games to date.
Graph Prepared By: Isaac H. Michaels, DrPH
Data Source: www.baseball-reference.com
Runs Differentials
Histograms
This figure shows histograms of game-level run differentials for each MLB team during the current season. Each bar represents the number of games with a given scoring margin, using a bin width of one run. Positive run differentials correspond to wins, while negative values correspond to losses. Bars are colored according to game outcome, distinguishing victories from defeats. Teams with histograms skewed to the right tend to win by larger margins or more frequently, indicating stronger overall performance. In contrast, teams with distributions centered near zero or skewed left tend to have closer or less favorable results. The figure offers a concise visual summary of how dominant — or narrowly competitive — each team’s games have been.
Graph Prepared By: Isaac H. Michaels, DrPH
Data Source: www.baseball-reference.com
Trends
This figure presents game-by-game run differentials for each MLB team over the course of the current season. Each vertical bar represents a single game, with its height indicating the margin of victory or defeat — positive values for wins and negative values for losses. Bars are colored green for wins and red for losses. The plot provides a visual timeline of team performance, revealing patterns such as winning or losing streaks, consistency in run margins, and periods of volatility. Teams with consistently tall positive bars tend to dominate opponents, whereas those with frequent negative bars or alternating patterns suggest closer or less predictable outcomes. Displaying these bars sequentially highlights the rhythm of each team’s season.
Graph Prepared By: Isaac H. Michaels, DrPH
Data Source: www.baseball-reference.com
Player Statistics
Batting
This table summarizes individual batting performance across Major League Baseball for all players with at least 25 at bats during the current season. It provides a comprehensive view of offensive production through both traditional and advanced metrics. Basic counting statistics such as games played (G), plate appearances (PA), hits (H), home runs (HR), and runs batted in (RBI) capture each player’s volume and contribution to team scoring. Rate-based measures—including batting average (BA), on-base percentage (OBP), slugging percentage (SLG), and on-base plus slugging (OPS)—reflect overall hitting efficiency and power.
Advanced indicators such as Wins Above Replacement (WAR), OPS+, and weighted on-base average (rOBA) contextualize performance relative to league and ballpark environments. Together, these metrics allow for comparisons across teams and player types, highlighting both consistent contributors and standout performers. The table serves as a detailed reference for evaluating individual offensive value throughout the season.
Note: Table displays rows only for players with at least 25 at bats.
Table Prepared By: Isaac H. Michaels, DrPH
Data Source: www.baseball-reference.com
*: Left-Handed Batter
#: Switch Hitter
G – Games Played
PA – Plate Appearances
AB – At Bats
R – Runs Scored/Allowed
H – Hits/Hits Allowed
2B – Doubles Hit/Allowed
3B – Triples Hit/Allowed
HR – Home Runs Hit/Allowed
RBI – Runs Batted In
SB – Stolen Bases
CS – Caught Stealing
BB – Bases on Balls/Walks
SO – Strikeouts
BA – Hits/At Bats
OBP – (H + BB + HBP)/(At Bats + BB + HBP + SF)
SLG – Total Bases/At Bats
OPS – On-Base + Slugging Percentages
OPS+ – OPS+ Adjusted to the player’s ballpark(s)
GIDP – Double Plays Grounded Into
IBB – Intentional Bases on Balls
Distributions and Leaders in Selected Statistics
Wins Above Replacement
This interactive plot shows the distribution of Wins Above Replacement (WAR) for Major League Baseball batters during the current season. Each horizontal box represents the spread of WAR values among players on a given team, with individual points marking each qualifying batter. Hovering over a point reveals the player’s name, team, and WAR value. The plot excludes players who have not reached the minimum number of at-bats required for inclusion, providing a clearer view of team-level performance among regular contributors.
By displaying both central tendencies and outliers, the visualization highlights how WAR varies across teams—some showing tightly clustered distributions indicative of balanced rosters, while others have one or two high-impact players driving overall team value. These differences help illustrate where player contributions are concentrated and which teams benefit most from top-tier offensive performance.
Graph and Table Prepared By: Isaac H. Michaels, DrPH
Data Source: www.baseball-reference.com
This figure shows the distribution of Wins Above Replacement (WAR) among all qualified batters for the current season. Each bar represents the number of players within a given WAR range. The accompanying table lists the ten players with the highest WAR values, providing a reference for those whose overall contributions most exceed that of a replacement-level player. Together, the figure and table help illustrate the spread of player value across the league based on combined offensive, defensive, and baserunning performance.
| League-wide Leaders: Wins Above Replacement | |||
| 2026 Season Data as of August 14, 2026 at 07:36 PM |
|||
| Rank | Player | Team | WAR |
|---|---|---|---|
| 1 | Pete Crow-Armstrong* | CHC | 7.4 |
| 2 | Kevin McGonigle* | DET | 5.6 |
| 3 | Yordan Alvarez* | HOU | 5.5 |
| 4 | Brice Turang* | MIL | 5.3 |
| 5 | Otto Lopez | MIA | 5.3 |
| 6 | Bobby Witt Jr. | KCR | 5.3 |
| 7 | Ceddanne Rafaela | BOS | 5.2 |
| 8 | Wilyer Abreu* | BOS | 5.1 |
| 9 | Andy Pages | LAD | 4.9 |
| 10 | Junior Caminero | TBR | 4.8 |
| Table Prepared by: Isaac H. Michaels, DrPH Data Source: www.baseball-reference.com |
|||
| Note: Data exclude players with fewer than 25 at bats. | |||
Graph and Table Prepared By: Isaac H. Michaels, DrPH
Data Source: www.baseball-reference.com
On-Base Plus Slugging Percentage
This figure shows the distribution of On-Base Plus Slugging Percentage (OPS) across all qualified batters. Each bar represents the number of players whose OPS falls within a particular range. The accompanying table identifies the ten players with the highest OPS values, offering a snapshot of the league’s strongest overall offensive performers. Together, these outputs demonstrate how effectively players combine on-base ability and power hitting.
| League-wide Leaders: On-Base Plus Slugging Percentage | |||
| 2026 Season Data as of August 14, 2026 at 07:36 PM |
|||
| Rank | Player | Team | OPS |
|---|---|---|---|
| 1 | Eduardo Valencia | DET | 1.254 |
| 2 | Abimelec Ortiz* | WSN | 1.122 |
| 3 | Liam Hicks* | TBR | 1.091 |
| 4 | Yordan Alvarez* | HOU | 1.057 |
| 5 | Joshua Kuroda-Grauer | ATH | 1.019 |
| 6 | Bryan De La Cruz | PHI | 0.954 |
| 7 | Juan Soto* | NYM | 0.947 |
| 8 | Griffin Conine* | MIA | 0.944 |
| 9 | Shohei Ohtani* | LAD | 0.935 |
| 10 | James Wood* | WSN | 0.928 |
| 11 | Rafael Flores | PIT | 0.928 |
| Table Prepared by: Isaac H. Michaels, DrPH Data Source: www.baseball-reference.com |
|||
| Note: Data exclude players with fewer than 25 at bats. | |||
Graph and Table Prepared By: Isaac H. Michaels, DrPH
Data Source: www.baseball-reference.com
Runs Batted In
This figure shows the distribution of Runs Batted In (RBI) across all qualified batters. Each bar corresponds to the number of players whose RBI totals fall within a specified range. The accompanying table highlights the ten players with the highest RBI counts, illustrating the league’s top run producers. This output provides a league-wide view of offensive productivity in terms of driving in runs.
| League-wide Leaders: Runs Batted In | |||
| 2026 Season Data as of August 14, 2026 at 07:36 PM |
|||
| Rank | Player | Team | RBI |
|---|---|---|---|
| 1 | CJ Abrams* | WSN | 91 |
| 2 | Sal Stewart | CIN | 89 |
| 3 | Yordan Alvarez* | HOU | 87 |
| 4 | Alec Burleson* | STL | 84 |
| 5 | Jordan Walker | STL | 84 |
| 6 | Dillon Dingler | DET | 81 |
| 7 | Luis García Jr.* | 2TM | 78 |
| 8 | Junior Caminero | TBR | 77 |
| 9 | Pete Alonso | BAL | 77 |
| 10 | Brice Turang* | MIL | 76 |
| 11 | Andy Pages | LAD | 76 |
| 12 | Ben Rice* | NYY | 76 |
| 13 | Luis García Jr.* | WSN | 76 |
| Table Prepared by: Isaac H. Michaels, DrPH Data Source: www.baseball-reference.com |
|||
| Note: Data exclude players with fewer than 25 at bats. | |||
Graph and Table Prepared By: Isaac H. Michaels, DrPH
Data Source: www.baseball-reference.com
Home Runs
This figure presents the distribution of Home Run totals among all qualified batters. Each bar indicates the number of players whose Home Run counts fall within a given range. The accompanying table lists the ten players with the most Home Runs, highlighting leading power hitters. Together, the outputs display how frequently players hit for power across the league.
| League-wide Leaders: Home Runs | |||
| 2026 Season Data as of August 14, 2026 at 07:36 PM |
|||
| Rank | Player | Team | HR |
|---|---|---|---|
| 1 | Kyle Schwarber* | PHI | 37 |
| 2 | Yordan Alvarez* | HOU | 35 |
| 3 | Matt Olson* | ATL | 35 |
| 4 | Junior Caminero | TBR | 35 |
| 5 | Hunter Goodman | COL | 34 |
| 6 | Ben Rice* | NYY | 32 |
| 7 | James Wood* | WSN | 30 |
| 8 | CJ Abrams* | WSN | 29 |
| 9 | Pete Crow-Armstrong* | CHC | 27 |
| 10 | Shohei Ohtani* | LAD | 27 |
| Table Prepared by: Isaac H. Michaels, DrPH Data Source: www.baseball-reference.com |
|||
| Note: Data exclude players with fewer than 25 at bats. | |||
Graph and Table Prepared By: Isaac H. Michaels, DrPH
Data Source: www.baseball-reference.com
Stolen Bases
This figure shows the distribution of Stolen Bases across all qualified batters. Each bar represents the number of players with stolen base totals in a particular range. The accompanying table identifies the ten players with the most Stolen Bases, illustrating the league’s most aggressive or successful baserunners. These outputs together highlight differences in base-stealing frequency and effectiveness among players.
| League-wide Leaders: Stolen Bases | |||
| 2026 Season Data as of August 14, 2026 at 07:36 PM |
|||
| Rank | Player | Team | SB |
|---|---|---|---|
| 1 | Nasim Nuñez# | WSN | 40 |
| 2 | Chandler Simpson* | TBR | 33 |
| 3 | Bobby Witt Jr. | KCR | 32 |
| 4 | Jazz Chisholm Jr.* | NYY | 31 |
| 5 | Pete Crow-Armstrong* | CHC | 30 |
| 6 | José Ramírez# | CLE | 29 |
| 7 | José Caballero | NYY | 29 |
| 8 | Fernando Tatis Jr. | SDP | 28 |
| 9 | Esteury Ruiz | MIA | 28 |
| 10 | CJ Abrams* | WSN | 23 |
| 11 | Otto Lopez | MIA | 23 |
| 12 | Jackson Merrill* | SDP | 23 |
| 13 | Josh Naylor* | SEA | 23 |
| 14 | Bryson Stott* | PHI | 23 |
| Table Prepared by: Isaac H. Michaels, DrPH Data Source: www.baseball-reference.com |
|||
| Note: Data exclude players with fewer than 25 at bats. | |||
Graph and Table Prepared By: Isaac H. Michaels, DrPH
Data Source: www.baseball-reference.com
Bases on Balls/Walks
This figure displays the distribution of Bases on Balls (Walks) among all qualified batters. Each bar represents the number of players whose walk totals fall within a given range. The accompanying table lists the ten players with the highest walk counts, identifying those with the greatest plate discipline and strike zone awareness. These outputs together illustrate variation in on-base skill and patience at the plate across the league.
| League-wide Leaders: Bases on Balls/Walks | |||
| 2026 Season Data as of August 14, 2026 at 07:36 PM |
|||
| Rank | Player | Team | BB |
|---|---|---|---|
| 1 | James Wood* | WSN | 90 |
| 2 | Taylor Ward | 2TM | 87 |
| 3 | Taylor Ward | BAL | 87 |
| 4 | Bryce Harper* | PHI | 85 |
| 5 | Yordan Alvarez* | HOU | 84 |
| 6 | Mike Trout | LAA | 82 |
| 7 | Kyle Schwarber* | PHI | 79 |
| 8 | Nick Kurtz* | ATH | 79 |
| 9 | Kevin McGonigle* | DET | 75 |
| 10 | Bryan Reynolds# | PIT | 74 |
| Table Prepared by: Isaac H. Michaels, DrPH Data Source: www.baseball-reference.com |
|||
| Note: Data exclude players with fewer than 25 at bats. | |||
Graph and Table Prepared By: Isaac H. Michaels, DrPH
Data Source: www.baseball-reference.com
Double Plays Grounded Into
This figure shows the distribution of Double Plays Grounded Into among all qualified batters. Each bar represents the number of players whose GIDP totals fall within a specific range. The accompanying table lists the ten players who have grounded into the most double plays, providing insight into tendencies related to contact type and situational hitting. These outputs together help illustrate how frequently players contribute to defensive double plays when batting with runners on base.
| League-wide Leaders: Double Plays Grounded Into | |||
| 2026 Season Data as of August 14, 2026 at 07:36 PM |
|||
| Rank | Player | Team | GIDP |
|---|---|---|---|
| 1 | Junior Caminero | TBR | 22 |
| 2 | Freddie Freeman* | LAD | 18 |
| 3 | Iván Herrera | STL | 17 |
| 4 | Vladimir Guerrero Jr. | TOR | 16 |
| 5 | Josh Naylor* | SEA | 16 |
| 6 | Alec Bohm | PHI | 16 |
| 7 | Salvador Perez | KCR | 16 |
| 8 | Bo Bichette | NYM | 15 |
| 9 | Bryce Harper* | PHI | 15 |
| 10 | Jose Altuve | HOU | 15 |
| 11 | Francisco Alvarez | NYM | 15 |
| 12 | Tyler Freeman | COL | 15 |
| Table Prepared by: Isaac H. Michaels, DrPH Data Source: www.baseball-reference.com |
|||
| Note: Data exclude players with fewer than 25 at bats. | |||
Graph and Table Prepared By: Isaac H. Michaels, DrPH
Data Source: www.baseball-reference.com
Pitching
This table presents pitching performance across Major League Baseball for all pitchers who have appeared in at least 10 games during the current season. It includes both traditional and advanced measures of pitching effectiveness and workload. Core statistics such as wins (W), losses (L), earned run average (ERA), games started (GS), and innings pitched (IP) summarize each pitcher’s role and overall contribution. Additional categories—such as complete games (CG), shutouts (SHO), and saves (SV)—highlight specific game outcomes and pitching durability.
Rate-based indicators including WHIP (walks plus hits per inning pitched), strikeouts per nine innings (SO9), and walks per nine innings (BB9) quantify efficiency and control, while advanced metrics such as Wins Above Replacement (WAR), ERA+, and fielding independent pitching (FIP) adjust for ballpark and defensive effects. Together, these data provide a nuanced view of pitcher performance, distinguishing consistent starters, high-leverage relievers, and emerging contributors across teams and leagues.
Note: Table displays rows only for players that played in at least 10 games.
Table Prepared By: Isaac H. Michaels, DrPH
Data Source: www.baseball-reference.com
•: Left-Handed Pitcher
W – Wins
L – Losses
W-L% – Win-Loss Percentage
ERA – 9 * ER / IP
G – Games Played or Pitched
GS – Games Started
GF – Games Finished
CG – Complete Game
SHO – Shutouts
SV – Saves
IP – Innings Pitched
H – Hits/Hits Allowed
R – Runs Scored/Allowed
ER – Earned Runs Allowed
HR – Home Runs Hit/Allowed
BB – Bases on Balls/Walks
IBB – Intentional Bases on Balls
SO – Strikeouts
HBP – Times Hit by a Pitch
BK – Balks
WP – Wild Pitches
BF – Batters Faced
ERA+ – ERA+ Adjusted to the player’s ballpark(s)
WHIP – (BB + H)/IP
H9 – 9 x H / IP
HR9 – 9 x HR / IP
BB9 – 9 x BB / IP
SO9 – 9 x SO / IP
SO/W – SO/W or SO/BB
Distributions and Leaders in Selected Statistics
Wins Above Replacement
This interactive visualization displays the distribution of Wins Above Replacement (WAR) for Major League Baseball pitchers during the current season. Each horizontal boxplot represents the spread of WAR values among pitchers on a given team, while individual points correspond to qualifying players who have appeared in the minimum number of games required for inclusion. Hovering over a point reveals the pitcher’s name, team, and WAR value.
The plot allows comparisons of pitching depth and performance across teams. Teams with higher median WAR values or a few standout outliers may rely heavily on elite pitching contributions, whereas more evenly distributed clusters suggest balanced rotations or bullpens. By examining the variation in WAR among teams, the figure highlights both dominant aces and the broader distribution of value among supporting pitchers.
Graph Prepared By: Isaac H. Michaels, DrPH
Data Source: www.baseball-reference.com
This figure displays the distribution of Wins Above Replacement (WAR) among all qualified pitchers for the current season. Each bar represents the number of pitchers whose WAR values fall within a particular range. The accompanying table lists the ten pitchers with the highest WAR, identifying those whose overall contributions most exceed those of replacement-level players. Together, these outputs provide a structural overview of how pitcher value is distributed across the league.
| League-wide Leaders: Wins Above Replacement | |||
| 2026 Season Data as of August 14, 2026 at 07:36 PM |
|||
| Rank | Player | Team | WAR |
|---|---|---|---|
| 1 | Cristopher Sánchez* | PHI | 6.6 |
| 2 | Cam Schlittler | NYY | 4.9 |
| 3 | Jacob Misiorowski | MIL | 4.8 |
| 4 | Dylan Cease | TOR | 4.8 |
| 5 | Parker Messick* | CLE | 4.5 |
| 6 | Jesús Luzardo* | PHI | 4.4 |
| 7 | Zack Wheeler | PHI | 4.4 |
| 8 | Eduardo Rodríguez* | ARI | 4.3 |
| 9 | Chase Burns | CIN | 4.3 |
| 10 | Sean Burke | CHW | 4.0 |
| Table Prepared by: Isaac H. Michaels, DrPH Data Source: www.baseball-reference.com |
|||
| Note: Data exclude pitchers with fewer than 10 game appearances. | |||
Graph and Table Prepared By: Isaac H. Michaels, DrPH
Data Source: www.baseball-reference.com
Earned Run Average
This figure illustrates the distribution of Earned Run Average (ERA) among all qualified pitchers. Each bar represents the number of pitchers whose ERA falls within a given range. The accompanying table lists the ten pitchers with the lowest ERA, highlighting those who have allowed the fewest earned runs per nine innings pitched. Together, these outputs show how pitching effectiveness is distributed across the league in terms of run prevention.
| League-wide Leaders: Earned Run Average | |||
| 2026 Season Data as of August 14, 2026 at 07:36 PM |
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| Rank | Player | Team | ERA |
|---|---|---|---|
| 1 | Matt Brash | SEA | 0.54 |
| 2 | Robert Suarez | ATL | 0.56 |
| 3 | Mason Miller | SDP | 0.88 |
| 4 | Josh Hader* | HOU | 0.96 |
| 5 | Daniel Duarte | NYM | 1.04 |
| 6 | Alimber Santa | HOU | 1.17 |
| 7 | Louis Varland | TOR | 1.30 |
| 8 | Troy Melton | DET | 1.46 |
| 9 | Tommy Nance | MIN | 1.46 |
| 10 | Brent Headrick* | NYY | 1.47 |
| Table Prepared by: Isaac H. Michaels, DrPH Data Source: www.baseball-reference.com |
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| Note: Data exclude pitchers with fewer than 10 game appearances. | |||
Graph and Table Prepared By: Isaac H. Michaels, DrPH
Data Source: www.baseball-reference.com
(Walks + Hits) per Innings Pitched
This figure shows the distribution of (Walks + Hits) per Innings Pitched (WHIP) among all qualified pitchers. Each bar represents the number of pitchers whose WHIP falls within a certain range. The accompanying table identifies the ten pitchers with the lowest WHIP, reflecting the most efficient at limiting baserunners. Together, these outputs demonstrate variation in pitcher control and contact management across the league.
| League-wide Leaders: Walks Plus Hits per Innings Pitched | |||
| 2026 Season Data as of August 14, 2026 at 07:36 PM |
|||
| Rank | Player | Team | WHIP |
|---|---|---|---|
| 1 | Josh Hader* | HOU | 0.714 |
| 2 | Jacob Misiorowski | MIL | 0.737 |
| 3 | Dylan Lee* | ATL | 0.741 |
| 4 | Jacob Latz* | TEX | 0.741 |
| 5 | Daniel Duarte | NYM | 0.750 |
| 6 | Brock Stewart | LAD | 0.750 |
| 7 | Tyler Ferguson | CHC | 0.766 |
| 8 | Cam Booser* | TBR | 0.769 |
| 9 | Brandyn Garcia* | ARI | 0.794 |
| 10 | Kevin Kelly | TBR | 0.818 |
| 11 | Luke Weaver | NYM | 0.818 |
| Table Prepared by: Isaac H. Michaels, DrPH Data Source: www.baseball-reference.com |
|||
| Note: Data exclude pitchers with fewer than 10 game appearances. | |||
Graph and Table Prepared By: Isaac H. Michaels, DrPH
Data Source: www.baseball-reference.com
Strike Outs to Walks Ratio
This figure presents the distribution of Strikeouts-to-Walks Ratio (SO/BB) among all qualified pitchers. Each bar corresponds to the number of pitchers whose SO/BB ratio falls within a given range. The accompanying table lists the ten pitchers with the highest ratios, indicating the best combination of strikeout ability and control. Together, these outputs illustrate the range of pitching command and dominance across the league.
| League-wide Leaders: Strike Outs to Walks Ratio | |||
| 2026 Season Data as of August 14, 2026 at 07:36 PM |
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| Rank | Player | Team | SO/BB |
|---|---|---|---|
| 1 | A.J. Minter* | NYM | 10.00 |
| 2 | Bryse Wilson | 3TM | 10.00 |
| 3 | Tyler Ferguson | 2TM | 10.00 |
| 4 | Tyler Ferguson | CHC | 9.50 |
| 5 | Jhoan Duran | PHI | 8.43 |
| 6 | Will Dion* | CLE | 8.33 |
| 7 | Tarik Skubal* | DET | 8.29 |
| 8 | A.J. Minter* | 2TM | 8.00 |
| 9 | Tarik Skubal* | 2TM | 7.11 |
| 10 | Garrett Whitlock | BOS | 7.00 |
| Table Prepared by: Isaac H. Michaels, DrPH Data Source: www.baseball-reference.com |
|||
| Note: Data exclude pitchers with fewer than 10 game appearances. | |||
Graph and Table Prepared By: Isaac H. Michaels, DrPH
Data Source: www.baseball-reference.com
Innings Pitched
This figure shows the distribution of Innings Pitched among all qualified pitchers. Each bar represents the number of pitchers who have thrown within a specific range of innings. The accompanying table highlights the ten pitchers with the highest innings totals, reflecting those most relied upon for workload and durability. Together, these outputs illustrate the distribution of pitching volume across the league.
| League-wide Leaders: Innings Pitched | |||
| 2026 Season Data as of August 14, 2026 at 07:36 PM |
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| Rank | Player | Team | IP |
|---|---|---|---|
| 1 | Sandy Alcantara | MIA | 163.2 |
| 2 | Cristopher Sánchez* | PHI | 155.2 |
| 3 | Michael Wacha | KCR | 150.2 |
| 4 | Cam Schlittler | NYY | 146.2 |
| 5 | Logan Gilbert | SEA | 145.1 |
| 6 | Gavin Williams | CLE | 144.2 |
| 7 | Tanner Bibee | CLE | 144.1 |
| 8 | Jesús Luzardo* | PHI | 143.2 |
| 9 | Eduardo Rodríguez* | ARI | 143.1 |
| 10 | Parker Messick* | CLE | 142.1 |
| Table Prepared by: Isaac H. Michaels, DrPH Data Source: www.baseball-reference.com |
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| Note: Data exclude pitchers with fewer than 10 game appearances. | |||
Graph and Table Prepared By: Isaac H. Michaels, DrPH
Data Source: www.baseball-reference.com
Games Pitched
This figure displays the distribution of Games Pitched among all qualified pitchers. Each bar represents the number of pitchers who have appeared in a certain range of games. The accompanying table identifies the ten pitchers with the most appearances, often reflecting bullpen specialists or high-usage relievers. Together, these outputs illustrate variation in how frequently pitchers take the mound throughout the season.
| League-wide Leaders: Games Pitched | |||
| 2026 Season Data as of August 14, 2026 at 07:36 PM |
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| Rank | Player | Team | G |
|---|---|---|---|
| 1 | Mason Fluharty* | TOR | 63 |
| 2 | Brent Headrick* | NYY | 62 |
| 3 | Brock Burke* | CIN | 61 |
| 4 | Steven Okert* | HOU | 59 |
| 5 | Braydon Fisher | TOR | 58 |
| 6 | Dylan Lee* | ATL | 57 |
| 7 | Tyler Rogers | TOR | 57 |
| 8 | Eduard Bazardo | SEA | 57 |
| 9 | Fernando Cruz | NYY | 57 |
| 10 | Brennan Bernardino* | COL | 57 |
| Table Prepared by: Isaac H. Michaels, DrPH Data Source: www.baseball-reference.com |
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| Note: Data exclude pitchers with fewer than 10 game appearances. | |||
Graph and Table Prepared By: Isaac H. Michaels, DrPH
Data Source: www.baseball-reference.com
Times Hit by Pitch
This figure presents the distribution of Times Hit by Pitch among all qualified pitchers, reflecting how often each has struck opposing batters with a pitch. Each bar represents the number of pitchers with hit-by-pitch totals within a specific range. The accompanying table lists the ten pitchers with the highest HBP counts, indicating those whose pitching style, control, or aggressiveness results in more hit batters. These outputs together illustrate league-wide variation in hit-by-pitch frequency.
| League-wide Leaders: Times Hit by Pitch | |||
| 2026 Season Data as of August 14, 2026 at 07:36 PM |
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| Rank | Player | Team | HBP |
|---|---|---|---|
| 1 | Anthony Kay* | CHW | 21 |
| 2 | Spencer Arrighetti | HOU | 14 |
| 3 | Nolan McLean | NYM | 13 |
| 4 | Framber Valdez* | DET | 13 |
| 5 | Cade Cavalli | WSN | 12 |
| 6 | Sean Manaea* | NYM | 12 |
| 7 | Trevor McDonald | SFG | 12 |
| 8 | Kai-Wei Teng | HOU | 11 |
| 9 | Chris Sale* | ATL | 10 |
| 10 | Yohan Ramírez | PIT | 10 |
| 11 | Nick Lodolo* | CIN | 10 |
| 12 | Riley O'Brien | STL | 10 |
| Table Prepared by: Isaac H. Michaels, DrPH Data Source: www.baseball-reference.com |
|||
| Note: Data exclude pitchers with fewer than 10 game appearances. | |||
Graph and Table Prepared By: Isaac H. Michaels, DrPH
Data Source: www.baseball-reference.com
Fielding
This table presents fielding statistics for Major League Baseball players who have appeared in at least 10 games during the current season. The data summarize individual defensive performance across positions and teams, emphasizing both opportunity and execution in the field. Traditional indicators such as games played (G), innings in the field (Inn), putouts (PO), assists (A), and errors (E) describe the frequency and outcomes of defensive chances (Ch). Fielding percentage (Fld%) offers a basic efficiency measure, while double plays (DP) illustrate situational impact.
More advanced measures—including total runs above average (Rtot), defensive runs saved (Rdrs), and range factors (RF/9 and RF/G)—capture defensive range, positioning, and overall run prevention value. Comparative metrics such as league-average range factors (lgRF9 and lgRFG) provide contextual benchmarks for evaluating fielding performance relative to peers. Together, these data give a comprehensive view of how fielders contribute to team defense, from routine plays to high-impact run-saving efforts.