Baseball Season Tracking Analysis

September 16, 2026
Baseball Sports Data Visualization


Published: June 25, 2021
Updated: September 16, 2026 at 04:22PM



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

As the Major League Baseball season enters its final stretch, team performance data reveal distinct paths to success and clear separation in divisional races. The Milwaukee Brewers, Los Angeles Dodgers, and Tampa Bay Rays have established themselves as the league’s top teams, each with over 90 wins. Analysis of their run scoring and prevention offers insight into the different methods teams have employed to build their records. While some clubs exhibit a strong correlation between their win percentage and run differential, others present statistical anomalies. These patterns highlight the varied ways pitching, offense, and game management contribute to a team’s standing as the postseason approaches.

The most notable pattern is the comprehensive dominance of the Milwaukee Brewers, who lead MLB with 94 wins and a 62.25% win percentage. This success is built on a foundation of elite run prevention, as the data show their pitching and defense allow a median of just 3 runs per game, tied for the lowest in baseball. Their consistency is further evidenced by a low standard deviation of 3.04 in runs allowed, suggesting they rarely have poor pitching outings. This sustained performance has translated directly into scoreboard success, solidifying their position atop their division.

Delving deeper into Milwaukee’s performance, the team’s talent is unmistakable. The Brewers boast multiple players who rank among the league’s best in Wins Above Replacement (WAR), a metric estimating a player’s total contributions. Pitcher Jacob Misiorowski has accumulated a 6.0 WAR with an exceptional 0.812 WHIP (Walks and Hits per Inning Pitched). On the offensive side, infielder Brice Turang has posted a 6.8 WAR, one of the highest marks in MLB, underscoring the team’s strength in both run prevention and overall play.

A second compelling pattern emerges from the New York Yankees’ season, which presents a statistical divergence between their record and run differential. With 88 wins, the Yankees hold one of the best records in the American League, yet they possess a median run differential of -1. This profile is more commonly associated with teams near or below a .500 winning percentage. Such a discrepancy suggests the Yankees have excelled in low-margin contests, securing a substantial number of wins in games decided by a narrow score. This trend indicates a potential overperformance relative to their underlying run-scoring and prevention totals.

The Yankees’ ability to win close games may reflect the quality of their pitching staff. The team features Cam Schlittler, whose 7.0 WAR is the second-highest among all MLB pitchers, pointing to his substantial role in the team’s success. While their offense scores a median of 3 runs per game, lower than many elite counterparts, their pitching appears to keep them competitive in most contests.

In contrast to the Yankees, other top teams like the Los Angeles Dodgers (92 wins) and Tampa Bay Rays (91 wins) show a more traditional alignment of strong records and positive run differentials, with both clubs posting a median differential of +1. Meanwhile, the Philadelphia Phillies echo the Yankees’ pattern, having compiled 83 wins despite a -1 median run differential. The Phillies’ postseason push relies on key contributors like pitcher Jesús Luzardo, who holds a 6.4 WAR and ranks among the league leaders in innings pitched.



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.

Cumulative line graphs showing the number of wins over time for each Major League Baseball team during the current season. Each panel represents one team, with lines rising as teams win games. The graph provides a comparative view of how fast different teams have accumulated wins as of the latest update.

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.

Heatmap showing the current head-to-head win-loss records and differentials for each MLB team. The vertical axis lists each team and the horizontal axis lists their opponents. Each cell contains text indicating the team's record against that opponent, with the cell's background colored on a diverging scale—blue for a positive differential and red for a negative differential—illustrating the degree of head-to-head dominance.

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.

Scatterplots showing runs scored versus runs allowed for each Major League Baseball team in the current season. Each point represents a single game. Points above the dashed diagonal line indicate wins; points below indicate losses. Teams with more points above the line generally have stronger offensive and defensive performance. Each team is displayed in its own panel for comparison.

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.

Histograms showing the distribution of game-level run differentials for each Major League Baseball team in the current season. Bars to the right of zero represent wins, and those to the left represent losses. Bars are colored by game outcome. Teams with histograms skewed right tend to win by larger margins; teams with more bars near or below zero have narrower or less favorable results.

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 September 16, 2026 at 04:22 PM
Rank Player Team WAR
1 Pete Crow-Armstrong* CHC 9.2
2 Brice Turang* MIL 6.8
3 Kevin McGonigle* DET 6.7
4 Bobby Witt Jr. KCR 6.4
5 Yordan Alvarez* HOU 6.1
6 Wilyer Abreu* BOS 5.7
7 Otto Lopez MIA 5.6
8 Elly De La Cruz# CIN 5.6
9 Andy Pages LAD 5.5
10 Junior Caminero TBR 5.4
11 Ceddanne Rafaela BOS 5.4
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.

Histogram showing the distribution of On-Base Plus Slugging Percentage among all qualified batters. The x-axis represents OPS values, and the y-axis represents the number of players.

League-wide Leaders: On-Base Plus Slugging Percentage
2026 Season
Data as of September 16, 2026 at 04:22 PM
Rank Player Team OPS
1 Jahmai Jones BOS 1.193
2 Yordan Alvarez* HOU 1.024
3 Joshua Kuroda-Grauer ATH 1.019
4 Juan Brito# CIN 0.996
5 Brewer Hicklen ATL 0.989
6 Adael Amador# COL 0.969
7 Eduardo Valencia DET 0.946
8 Pete Crow-Armstrong* CHC 0.938
9 Lázaro Montes* SEA 0.930
10 Randal Grichuk CHW 0.929
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.

Histogram showing the distribution of Runs Batted In among all qualified batters. The x-axis represents RBI totals, and the y-axis represents the number of players.

League-wide Leaders: Runs Batted In
2026 Season
Data as of September 16, 2026 at 04:22 PM
Rank Player Team RBI
1 Alec Burleson* STL 111
2 Sal Stewart CIN 107
3 Pete Crow-Armstrong* CHC 102
4 Pete Alonso BAL 101
5 Jordan Walker STL 100
6 Yordan Alvarez* HOU 98
7 Rafael Devers* SFG 98
8 Junior Caminero TBR 96
9 CJ Abrams* WSN 96
10 Kyle Schwarber* PHI 95
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.

Histogram showing the distribution of Home Runs among all qualified batters. The x-axis represents Home Run totals, and the y-axis represents the number of players.

League-wide Leaders: Home Runs
2026 Season
Data as of September 16, 2026 at 04:22 PM
Rank Player Team HR
1 Kyle Schwarber* PHI 45
2 Pete Crow-Armstrong* CHC 42
3 Junior Caminero TBR 41
4 Matt Olson* ATL 39
5 Yordan Alvarez* HOU 39
6 Ben Rice* NYY 38
7 Hunter Goodman COL 38
8 Rafael Devers* SFG 37
9 Pete Alonso BAL 36
10 Kazuma Okamoto TOR 33
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.

Histogram showing the distribution of Stolen Bases among all qualified batters. The x-axis represents Stolen Base totals, and the y-axis represents the number of players.

League-wide Leaders: Stolen Bases
2026 Season
Data as of September 16, 2026 at 04:22 PM
Rank Player Team SB
1 Nasim Nuñez# WSN 46
2 Bobby Witt Jr. KCR 41
3 Chandler Simpson* TBR 41
4 Jazz Chisholm Jr.* NYY 40
5 Pete Crow-Armstrong* CHC 37
6 Fernando Tatis Jr. SDP 35
7 José Ramírez# CLE 33
8 José Caballero NYY 32
9 Otto Lopez MIA 30
10 Esteury Ruiz MIA 30
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.

Histogram showing the distribution of Bases on Balls among all qualified batters. The x-axis represents Walk totals, and the y-axis represents the number of players.

League-wide Leaders: Bases on Balls/Walks
2026 Season
Data as of September 16, 2026 at 04:22 PM
Rank Player Team BB
1 Yordan Alvarez* HOU 103
2 Bryce Harper* PHI 102
3 Taylor Ward 2TM 99
4 James Wood* WSN 98
5 Mike Trout LAA 96
6 Kyle Schwarber* PHI 93
7 Kevin McGonigle* DET 91
8 Miguel Vargas CHW 90
9 Geraldo Perdomo# ARI 88
10 Jake Bauers* MIL 88
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.

Histogram showing the distribution of Double Plays Grounded Into among all qualified batters. The x-axis represents GIDP totals, and the y-axis represents the number of players.

League-wide Leaders: Double Plays Grounded Into
2026 Season
Data as of September 16, 2026 at 04:22 PM
Rank Player Team GIDP
1 Junior Caminero TBR 25
2 Freddie Freeman* LAD 20
3 Salvador Perez KCR 20
4 Alex Bregman CHC 19
5 Manny Machado SDP 19
6 Alec Bohm PHI 19
7 Vladimir Guerrero Jr. TOR 19
8 Iván Herrera STL 18
9 Bryce Harper* PHI 18
10 Josh Bell# MIN 18
11 Jose Altuve HOU 18
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 September 16, 2026 at 04:22 PM
Rank Player Team WAR
1 Cristopher Sánchez* PHI 7.5
2 Cam Schlittler NYY 7.0
3 Jesús Luzardo* PHI 6.4
4 Dylan Cease TOR 6.1
5 Jacob Misiorowski MIL 6.0
6 Yoshinobu Yamamoto LAD 5.8
7 Parker Messick* CLE 5.7
8 Chris Sale* ATL 5.4
9 Eduardo Rodríguez* ARI 5.1
10 Chase Burns CIN 4.9
11 Zack Wheeler PHI 4.9
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.

Histogram showing the distribution of Earned Run Average among qualified pitchers. The x-axis represents ERA values, and the y-axis represents the number of pitchers.

League-wide Leaders: Earned Run Average
2026 Season
Data as of September 16, 2026 at 04:22 PM
Rank Player Team ERA
1 Justin Martínez ARI 0.00
2 Hagen Smith* CHW 0.41
3 Matt Brash SEA 0.54
4 Robert Suarez ATL 0.56
5 Paul Sewald TOR 0.82
6 Josh Hader* HOU 0.85
7 Dennis Santana ARI 0.90
8 Mason Miller SDP 1.12
9 Alimber Santa HOU 1.17
10 Aaron Civale CHC 1.19
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


(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.

Histogram showing the distribution of WHIP among qualified pitchers. The x-axis represents WHIP values, and the y-axis represents the number of pitchers.

League-wide Leaders: Walks Plus Hits per Innings Pitched
2026 Season
Data as of September 16, 2026 at 04:22 PM
Rank Player Team WHIP
1 Josh Hader* HOU 0.661
2 Tyler Wells TBR 0.722
3 Paul Sewald TOR 0.727
4 Brandyn Garcia* ARI 0.755
5 Logan Henderson MIL 0.781
6 Daniel Duarte NYM 0.809
7 Cam Booser* TBR 0.811
8 Jacob Misiorowski MIL 0.812
9 Jacob Latz* TEX 0.817
10 Luke Weaver NYM 0.818
11 Hagen Smith* CHW 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.

Histogram showing the distribution of Strikeouts-to-Walks Ratio among qualified pitchers. The x-axis represents SO/BB values, and the y-axis represents the number of pitchers.

League-wide Leaders: Strike Outs to Walks Ratio
2026 Season
Data as of September 16, 2026 at 04:22 PM
Rank Player Team SO/BB
1 Bryse Wilson MIL 22.00
2 Blake Weiman* LAA 12.00
3 A.J. Minter* NYM 10.00
4 Bryse Wilson 3TM 10.00
5 Connor Thomas* KCR 9.00
6 Jhoan Duran PHI 8.33
7 Will Dion* CLE 8.33
8 Tarik Skubal* DET 8.29
9 Garrett Whitlock BOS 8.29
10 Tarik Skubal* 2TM 6.92
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.

Histogram showing the distribution of Innings Pitched among qualified pitchers. The x-axis represents innings totals, and the y-axis represents the number of pitchers.

League-wide Leaders: Innings Pitched
2026 Season
Data as of September 16, 2026 at 04:22 PM
Rank Player Team IP
1 Sandy Alcantara MIA 205.0
2 Cristopher Sánchez* PHI 193.2
3 Michael Wacha KCR 188.2
4 Cam Schlittler NYY 184.2
5 Yoshinobu Yamamoto LAD 179.0
6 Jesús Luzardo* PHI 178.2
7 Eduardo Rodríguez* ARI 178.1
8 Logan Gilbert SEA 178.0
9 Tanner Bibee CLE 177.1
10 Michael King SDP 175.0
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


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.

Histogram showing the distribution of Games Pitched among qualified pitchers. The x-axis represents the number of games pitched, and the y-axis represents the number of pitchers.

League-wide Leaders: Games Pitched
2026 Season
Data as of September 16, 2026 at 04:22 PM
Rank Player Team G
1 Mason Fluharty* TOR 78
2 Brent Headrick* NYY 76
3 Braydon Fisher TOR 73
4 Brock Burke* CIN 73
5 Rico Garcia BAL 72
6 Aaron Ashby* MIL 71
7 Adrián Morejón* SDP 71
8 Tyler Rogers TOR 70
9 Hogan Harris* ATH 70
10 Kevin Ginkel ARI 69
11 Eduard Bazardo SEA 69
12 Brennan Bernardino* COL 69
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


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.

Histogram showing the distribution of Times Hit by Pitch among qualified pitchers. The x-axis represents the number of hit batters, and the y-axis represents the number of pitchers.

League-wide Leaders: Times Hit by Pitch
2026 Season
Data as of September 16, 2026 at 04:22 PM
Rank Player Team HBP
1 Anthony Kay* CHW 24
2 Cade Cavalli WSN 16
3 Nolan McLean NYM 15
4 Spencer Arrighetti 2TM 15
5 Framber Valdez* DET 14
6 Chris Sale* ATL 14
7 Sean Manaea* NYM 14
8 Spencer Arrighetti HOU 14
9 Nick Lodolo* CIN 14
10 Brady Singer CIN 13
11 Kai-Wei Teng HOU 13
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.

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


G – Games Played or Pitched
GS – Games Started
CG – Complete Game
Inn – Innings Played in Field
Ch – Defensive Chances = Putouts + Assists + Errors
PO – Putouts
A – Assists
E – Errors Committed
DP – Double Plays Turned
Fld% – Fielding Percentage = (Putouts + Assists) / (Putouts + Assists + Errors)


Distributions and Leaders in Selected Statistics


Innings Played in Field

This figure shows the distribution of Innings Played in the field among all qualified players. Each bar represents the number of players who have logged a given range of defensive innings, regardless of position. The accompanying table lists the ten players with the highest totals, representing those who have accumulated the most time on the field over the course of the season. Together, these outputs illustrate the overall distribution of defensive playing time and workload across the league.

Histogram showing the distribution of Innings Played in the field among qualified players. The x-axis represents innings totals, and the y-axis represents the number of players.

League-wide Leaders: Innings Played in Field
2026 Season
Data as of September 16, 2026 at 04:22 PM
Rank Player Team Inn
1 Matt Olson ATL 1342.0
2 Michael Busch CHC 1312.0
3 Ozzie Albies ATL 1310.0
4 Austin Riley ATL 1309.0
5 Cole Young SEA 1308.1
6 Junior Caminero TBR 1307.2
7 Pete Crow-Armstrong CHC 1289.0
8 Nico Hoerner CHC 1288.0
9 Jackson Merrill SDP 1284.1
10 Geraldo Perdomo ARI 1284.0
Table Prepared by: Isaac H. Michaels, DrPH
Data Source: www.baseball-reference.com
Note: Data exclude players with fewer than 10 game appearances.

Graph and Table Prepared By: Isaac H. Michaels, DrPH
Data Source: www.baseball-reference.com


Double Plays Turned

This figure displays the distribution of Double Plays Turned among all qualified fielders. Each bar represents the number of players who have participated in a specific range of double plays. The accompanying table identifies the ten players most frequently involved in turning double plays, typically including middle infielders and corner infielders. Together, these outputs illustrate how defensive double-play involvement is distributed among players and positions across the league.

Histogram showing the distribution of Double Plays Turned among qualified fielders. The x-axis represents double play totals, and the y-axis represents the number of players.

League-wide Leaders: Double Plays Turned
2026 Season
Data as of September 16, 2026 at 04:22 PM
Rank Player Team DP
1 Alec Burleson STL 123
2 Matt Olson ATL 119
3 Spencer Torkelson DET 107
4 Michael Busch CHC 106
5 Christian Walker HOU 99
6 Josh Naylor SEA 98
7 TJ Rumfield COL 93
8 Masyn Winn STL 89
9 Geraldo Perdomo ARI 88
10 Brice Turang MIL 87
11 Pete Alonso BAL 87
Table Prepared by: Isaac H. Michaels, DrPH
Data Source: www.baseball-reference.com
Note: Data exclude players with fewer than 10 game appearances.

Graph and Table Prepared By: Isaac H. Michaels, DrPH
Data Source: www.baseball-reference.com




  1. This executive summary was generated by an AI summarizer agent and reviewed by an editor agent. I review any summaries flagged for revision.↩︎

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