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MLB Leaderboard

Saiem Gilani
@saiemgilani @saiemgilani

Source: vignettes/leaderboard-mlb.Rmd
leaderboard-mlb.Rmd
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Updated 2026-10-12: the final 2026 regular season; the postseason is under way.

This page is rebuilt every week with the site. It builds the division standings, charts run differential with logos and lists the league leaders with their headshots, for the latest MLB season with games: the season to date from opening day to the end of September, the final regular season after that. Data: the MLB Stats API through baseballr; no key needed.

Picking the season

The season runs inside one calendar year, but before opening day the Stats API standings for the new season come back empty, or with every team on zero games. The helper turns both into “not published” and the page steps back one season. Every Stats API call goes through live(): if the API does not answer, the page shows a note in place of each table and chart for that week instead of failing the site build. The Stats API’s season calendar (mlb_seasons()) says whether the regular season is still being played, so the status line can say what the numbers cover.

library(sdvplotR)
library(dplyr, warn.conflicts = FALSE)
library(ggplot2)
library(gt)

today <- Sys.Date()
current <- as.integer(format(today, "%Y")) # the season runs inside one calendar year

# A live API call, or NULL when the API does not answer: one bad week then shows
# a note in place of a table instead of failing the whole site build
live <- function(expr) tryCatch(expr, error = function(e) NULL)
unavailable <- function(what, ok) {
  if (ok) "" else sprintf("*%s were unavailable when this page was built on %s; they return next week.*", what, today)
}

# A season's standings from the MLB Stats API, or NULL before opening day: the
# API answers with no rows for a season it has no standings for, or with every
# team on zero games
standings_for <- function(season) {
  table <- live(baseballr::mlb_standings(season = season, league_id = "103,104"))
  if (NROW(table) == 0 || max(table$team_records_games_played) == 0) NULL else table
}

season <- current
raw_standings <- standings_for(season)
if (is.null(raw_standings)) {
  season <- current - 1
  raw_standings <- standings_for(season)
}
# last season always has standings, so none for either season means the API did not answer
available <- !is.null(raw_standings)
leaders_ok <- FALSE

# The Stats API's calendar for the current season: when its regular season and
# postseason end
calendar <- live(baseballr::mlb_seasons(sport_id = 1))
regular_end <- as.Date(as.character(calendar$regular_season_end_date[calendar$season_id == current]))
post_end <- as.Date(as.character(calendar$post_season_end_date[calendar$season_id == current]))
games_per_team <- if (available) round(median(raw_standings$team_records_games_played)) else NA
if (!available) {
  status <- "the MLB Stats API did not answer when this page was built, so this week's tables and chart are missing; they return next week."
  through <- ""
} else if (season < current) {
  status <- sprintf(
    "the offseason, so this is the final %d regular season; the %d season has no games yet.",
    season, current
  )
  through <- "final regular season"
} else if (length(regular_end) == 1 && today <= regular_end) {
  status <- sprintf("the %d season to date, about %d games per team.", season, games_per_team)
  through <- paste("through", games_per_team, "games")
} else if (length(post_end) == 1 && today <= post_end) {
  status <- sprintf("the final %d regular season; the postseason is under way.", season)
  through <- "final regular season"
} else {
  status <- sprintf("the offseason, so this is the final %d regular season.", season)
  through <- "final regular season"
}

The standings name each club by its nickname; mlb_teams() adds its abbreviation, full name and division, joined on the Stats API team id.

clubs <- live(baseballr::mlb_teams(season = season, sport_ids = 1))
available <- NROW(clubs) > 0 # mlb_teams(), like mlb_standings(), answers with no rows when the API is down
clubs <- select(clubs, team_id, abbreviation = team_abbreviation, team_name = team_full_name, division = division_name)
standings <- raw_standings |>
  transmute(
    team_id = team_records_team_id,
    rank = as.integer(team_records_division_rank),
    w = team_records_wins,
    l = team_records_losses,
    pct = as.numeric(team_records_winning_percentage),
    gb = team_records_division_games_back,
    rs = team_records_runs_scored,
    ra = team_records_runs_allowed,
    diff = team_records_run_differential,
    streak = team_records_streak_streak_code
  )
stopifnot(identical(class(standings$team_id), class(clubs$team_id)))
standings <- inner_join(standings, clubs, by = "team_id") |>
  arrange(division, rank)
nrow(standings)
#> [1] 30

1. Division standings

Six tables in one, grouped by division. gt_sdv_logos() turns the Stats API abbreviations into logos (sdvplotR maps its AZ and CWS to ESPN’s ARI and CHW), and gt_color_pills() draws the run differential on a scale centred at zero.

reach <- max(abs(standings$diff))
standings |>
  mutate(logo = abbreviation) |>
  select(division, logo, team_name, w, l, pct, gb, rs, ra, diff, streak) |>
  gt(groupname_col = "division", id = "mlb-standings") |>
  tab_header(
    title = paste("MLB standings,", season),
    subtitle = paste("By division,", through)
  ) |>
  fmt_number(pct, decimals = 3) |>
  cols_label(
    logo = "", team_name = "Team", w = "W", l = "L", pct = "Pct", gb = "GB",
    rs = "RS", ra = "RA", diff = "Diff", streak = "Streak"
  ) |>
  tab_source_note("Data: MLB Stats API via baseballr | Viz: sdvplotR") |>
  gt_color_pills(
    diff,
    palette = c("#c84630", "#f7f7f7", "#2a7ab9"), domain = c(-reach, reach),
    digits = 0, pill_height = 22
  ) |>
  gt_sdv_logos(columns = logo, league = "mlb", height = 24) |>
  gt_theme_broadsheet()
MLB standings, 2026
By division, final regular season
Team W L Pct GB RS RA Diff Streak
American League Central
Cleveland Guardians Cleveland Guardians 85 77 0.525 - 678 667 11 L1
Chicago White Sox Chicago White Sox 84 78 0.519 1.0 776 720 56 W1
Minnesota Twins Minnesota Twins 77 85 0.475 8.0 739 797 -58 W1
Detroit Tigers Detroit Tigers 76 86 0.469 9.0 723 652 71 L1
Kansas City Royals Kansas City Royals 69 93 0.426 16.0 690 810 -120 W1
American League East
Tampa Bay Rays Tampa Bay Rays 98 64 0.605 - 736 650 86 L1
New York Yankees New York Yankees 93 68 0.578 4.5 739 601 138 W1
Boston Red Sox Boston Red Sox 87 75 0.537 11.0 689 611 78 L1
Baltimore Orioles Baltimore Orioles 79 82 0.491 18.5 718 739 -21 L1
Toronto Blue Jays Toronto Blue Jays 79 83 0.488 19.0 648 694 -46 W1
American League West
Houston Astros Houston Astros 81 81 0.500 - 734 766 -32 W2
Texas Rangers Texas Rangers 80 82 0.494 1.0 673 719 -46 L1
Seattle Mariners Seattle Mariners 76 86 0.469 5.0 664 722 -58 W2
Athletics Athletics 64 98 0.395 17.0 699 937 -238 L2
Los Angeles Angels Los Angeles Angels 62 100 0.383 19.0 655 752 -97 L2
National League Central
Milwaukee Brewers Milwaukee Brewers 103 59 0.636 - 832 618 214 W5
Chicago Cubs Chicago Cubs 89 73 0.549 14.0 850 703 147 W1
Pittsburgh Pirates Pittsburgh Pirates 82 80 0.506 21.0 767 739 28 W1
St. Louis Cardinals St. Louis Cardinals 77 85 0.475 26.0 720 749 -29 L4
Cincinnati Reds Cincinnati Reds 75 87 0.463 28.0 666 826 -160 L1
National League East
Atlanta Braves Atlanta Braves 94 68 0.580 - 742 626 116 L1
Philadelphia Phillies Philadelphia Phillies 88 74 0.543 6.0 713 698 15 W1
Miami Marlins Miami Marlins 80 82 0.494 14.0 715 712 3 W1
Washington Nationals Washington Nationals 77 85 0.475 17.0 821 815 6 W1
New York Mets New York Mets 74 88 0.457 20.0 699 731 -32 L1
National League West
Los Angeles Dodgers Los Angeles Dodgers 100 62 0.617 - 801 600 201 W3
San Diego Padres San Diego Padres 91 71 0.562 9.0 722 681 41 W2
Arizona Diamondbacks Arizona Diamondbacks 86 76 0.531 14.0 739 730 9 L2
San Francisco Giants San Francisco Giants 65 97 0.401 35.0 669 760 -91 L5
Colorado Rockies Colorado Rockies 58 104 0.358 42.0 752 944 -192 L1
Data: MLB Stats API via baseballr | Viz: sdvplotR

2. Run differential

Every club’s run differential as a bar in its primary color, best at the top, with its logo at the end of the bar.

if (available) {
  rd <- standings |>
    arrange(diff, desc(team_name)) |> # the name breaks a tie, so an unchanged week renders the same
    mutate(
      label = sprintf("%s (%+d)", team_name, diff),
      label = factor(label, levels = label),
      end = diff + sign(diff) * 0.06 * reach
    )

  ggplot(rd, aes(y = label)) +
    geom_col(aes(x = diff, fill = abbreviation), width = 0.72) +
    geom_vline(xintercept = 0, colour = "grey20", linewidth = 0.4) +
    geom_sdv_logos(aes(x = end, team = abbreviation), league = "mlb", height = 0.028) +
    scale_fill_sdv(league = "mlb", guide = "none") +
    scale_x_continuous(limits = c(-1.15, 1.15) * reach) +
    labs(
      title = paste("MLB run differential,", season, through),
      subtitle = "Runs scored minus runs allowed",
      x = "Run differential", y = NULL,
      caption = "Data: MLB Stats API via baseballr | Viz: sdvplotR"
    ) +
    theme_minimal(base_size = 12) +
    theme(
      plot.title = element_text(face = "bold"),
      panel.grid.major.y = element_blank(),
      panel.grid.minor = element_blank()
    )
} else {
  # the Stats API did not answer: a stand-in keeps this figure, which the gallery shows
  ggplot() +
    annotate("text", x = 0, y = 0, size = 5, label = paste0(
      "MLB standings were unavailable when this page was built on ", today, ".\nThey return next week."
    )) +
    theme_void()
}

Horizontal bar chart of every MLB club's run differential, best at the top, each bar in the club's primary color with its logo at the end of the bar.

3. League leaders with headshots

The Stats API’s leaderboards, one category at a time (mlb_stats_leaders(); the rate stats list qualified players only). Its player ids are MLBAM ids, which gt_sdv_headshots(id_system = "league") turns into MLB’s own headshots. Ties share a rank, so a category can show more than three players.

categories <- tibble::tribble(
  ~category, ~stat, ~group, ~digits,
  "Home runs", "homeRuns", "hitting", 0,
  "Batting average", "battingAverage", "hitting", 3,
  "OPS", "onBasePlusSlugging", "hitting", 3,
  "Stolen bases", "stolenBases", "hitting", 0,
  "ERA", "earnedRunAverage", "pitching", 2,
  "Strikeouts", "strikeouts", "pitching", 0
)
top3 <- function(i) {
  x <- live(baseballr::mlb_stats_leaders(
    leader_categories = categories$stat[i], season = season, sport_id = 1,
    leader_game_types = "R", limit = 3
  ))
  if (NROW(x) == 0) {
    return(NULL) # the API did not answer for this category
  }
  x |>
    filter(stat_group == categories$group[i], rank <= 3) |>
    transmute(
      category = categories$category[i], rank, person_id, player = person_full_name, team_id,
      value = formatC(as.numeric(value), format = "f", digits = categories$digits[i])
    )
}
leaders <- bind_rows(lapply(seq_len(nrow(categories)), top3))
leaders_ok <- nrow(leaders) > 0
if (leaders_ok) {
  leaders <- leaders |>
    left_join(select(clubs, team_id, abbreviation), by = "team_id") |>
    mutate(
      value = sub("^0\\.", ".", value), # .312, not 0.312, as baseball writes it
      headshot = person_id
    )
}
head(leaders)
#> # A tibble: 6 × 8
#>   category         rank person_id player     team_id value abbreviation headshot
#>   <chr>           <int>     <int> <chr>        <int> <chr> <chr>           <int>
#> 1 Home runs           1    691718 Pete Crow…     112 45    CHC            691718
#> 2 Home runs           1    656941 Kyle Schw…     143 45    PHI            656941
#> 3 Home runs           3    624413 Pete Alon…     110 43    BAL            624413
#> 4 Batting average     1    670541 Yordan Al…     117 .316  HOU            670541
#> 5 Batting average     2    672515 Gabriel M…     109 .311  AZ             672515
#> 6 Batting average     3    650333 Luis Arra…     143 .310  PHI            650333
leaders |>
  select(category, rank, headshot, player, abbreviation, value) |>
  gt(groupname_col = "category", id = "mlb-leaders") |>
  tab_header(
    title = paste("MLB leaders,", season),
    subtitle = paste0("Top three, ", through)
  ) |>
  cols_label(rank = "", headshot = "", player = "Player", abbreviation = "", value = "") |>
  cols_align("right", value) |>
  tab_source_note("Data: MLB Stats API via baseballr | Viz: sdvplotR") |>
  gt_sdv_headshots(columns = headshot, league = "mlb", id_system = "league", height = 36) |>
  gt_sdv_logos(columns = abbreviation, league = "mlb", height = 22) |>
  gt_theme_savant()
MLB leaders, 2026
Top three, final regular season
Player
Home runs
1 Player 691718 headshot Pete Crow-Armstrong Chicago Cubs 45
1 Player 656941 headshot Kyle Schwarber Philadelphia Phillies 45
3 Player 624413 headshot Pete Alonso Baltimore Orioles 43
Batting average
1 Player 670541 headshot Yordan Alvarez Houston Astros .316
2 Player 672515 headshot Gabriel Moreno Arizona Diamondbacks .311
3 Player 650333 headshot Luis Arraez Philadelphia Phillies .310
OPS
1 Player 670541 headshot Yordan Alvarez Houston Astros 1.033
2 Player 691718 headshot Pete Crow-Armstrong Chicago Cubs .942
3 Player 575929 headshot Willson Contreras Boston Red Sox .902
Stolen bases
1 Player 683083 headshot Nasim Nuñez Washington Nationals 49
2 Player 802415 headshot Chandler Simpson Tampa Bay Rays 46
3 Player 677951 headshot Bobby Witt Jr. Kansas City Royals 45
ERA
1 Player 694819 headshot Jacob Misiorowski Milwaukee Brewers 1.80
2 Player 693645 headshot Cam Schlittler New York Yankees 1.95
3 Player 519242 headshot Chris Sale Atlanta Braves 2.16
Strikeouts
1 Player 694819 headshot Jacob Misiorowski Milwaukee Brewers 252
2 Player 668909 headshot Gavin Williams Cleveland Guardians 248
3 Player 656302 headshot Dylan Cease Toronto Blue Jays 239
3 Player 693645 headshot Cam Schlittler New York Yankees 239
Data: MLB Stats API via baseballr | Viz: sdvplotR

4. Interactive version

The 30 clubs from the standings in one reactable: click a column header to sort the league by it (run differential, runs scored, streak), or search for a club or a division. reactable_sdv_logos() draws the logos, and reactable_sdv_team_color_bar() fills each club’s wins cell in its color, to the length of its win total.

league_table <- standings |>
  arrange(desc(pct), team_name) |>
  transmute(logo = abbreviation, team_name, division, w, l, pct, rs, ra, diff, streak)

reactable::reactable(
  league_table,
  searchable = TRUE, highlight = TRUE, compact = TRUE, defaultPageSize = 15,
  columns = list(
    logo = reactable::colDef(name = "", cell = reactable_sdv_logos("mlb", height = 24), html = TRUE, width = 46),
    team_name = reactable::colDef(name = "Team", minWidth = 150),
    division = reactable::colDef(name = "Division", minWidth = 120),
    w = reactable::colDef(name = "W", style = reactable_sdv_team_color_bar(league_table, "logo", "mlb")),
    l = reactable::colDef(name = "L"),
    pct = reactable::colDef(name = "Pct", format = reactable::colFormat(digits = 3)),
    rs = reactable::colDef(name = "RS"),
    ra = reactable::colDef(name = "RA"),
    diff = reactable::colDef(name = "Diff"),
    streak = reactable::colDef(name = "Streak", sortable = FALSE)
  )
)

More recipes like this one, in plotly, ggiraph, leaflet and reactable, are in Interactive charts.

  • MLB walks through baseballr and sdvplotR more broadly.
  • NHL builds the same three views for hockey.
  • Social graphics, automated posts leaderboards like these on a schedule.

Our Authors

Citation

To cite the sdvplotR R package in publications, use:

BibTeX Citation

@misc{gilani_carl_lee_kay_weatherman_sdvplotR,
  author = {Gilani, Saiem and Carl, Sebastian and Lee, Jared and Kay, Camden and Weatherman, Andrew},
  title = {sdvplotR: The SportsDataverse's R Package for Multi-League Sports Plotting.},
  url = {https://sdvplotR.sportsdataverse.org},
  year = {2026}
}