A win probability chart shows how each team's likelihood of winning evolves over the course of a game. The line starts near 50% and fluctuates based on scoring events, ultimately reaching 100% or 0% at game end. The area above and below the 50% baseline is filled with team colors to convey momentum at a glance. This visualization is widely used across major sports for post-game analysis and live broadcasting.
#' anyplot.ai
#' line-win-probability: Win Probability Chart
#' Library: ggplot2 3.5.1 | R 4.4.1
#' Quality: 90/100 | Created: 2026-06-21
library(ggplot2)
library(scales)
library(ragg)
set.seed(42)
# Theme tokens
THEME <- Sys.getenv("ANYPLOT_THEME", "light")
PAGE_BG <- if (THEME == "light") "#FAF8F1" else "#1A1A17"
ELEVATED_BG <- if (THEME == "light") "#FFFDF6" else "#242420"
INK <- if (THEME == "light") "#1A1A17" else "#F0EFE8"
INK_SOFT <- if (THEME == "light") "#4A4A44" else "#B8B7B0"
INK_MUTED <- if (THEME == "light") "#6B6A63" else "#A8A79F"
# Imprint categorical palette — first series always #009E73
IMPRINT_PALETTE <- c(
"#009E73", # 1 — brand green (Hawks / home team winning zone)
"#C475FD", # 2
"#4467A3", # 3
"#BD8233", # 4
"#AE3030", # 5 — matte red (Wolves / away team winning zone)
"#2ABCCD", # 6
"#954477", # 7
"#99B314" # 8
)
HOME_COLOR <- IMPRINT_PALETTE[1] # #009E73: Hawks (home)
AWAY_COLOR <- IMPRINT_PALETTE[5] # #AE3030: Wolves (away) — semantic red for loss zone
# Win probability via spline control points encoding the game narrative:
# Hawks start slightly ahead, Wolves mount a 10-0 run in Q2 to take the lead,
# Hawks storm back in Q3, then seal it with back-to-back 3-pointers in Q4.
ctrl <- data.frame(
t = c(0, 5, 10, 15, 19, 22, 26, 30, 34, 38, 42, 45, 48),
p = c(0.50, 0.54, 0.58, 0.52, 0.36, 0.40, 0.52, 0.66, 0.60, 0.68, 0.61, 0.80, 0.87)
)
n <- 250
minute <- seq(0, 48, length.out = n)
wp_fn <- splinefun(ctrl$t, ctrl$p, method = "natural")
win_prob <- pmin(pmax(wp_fn(minute) + rnorm(n, 0, 0.012), 0.03), 0.97)
df <- data.frame(minute = minute, win_prob = win_prob)
# Key annotated events
event_times <- c(19, 29, 44)
events <- data.frame(
minute = event_times,
win_prob = approx(df$minute, df$win_prob, xout = event_times)$y,
label = c("Wolves 10-0 run", "Hawks 8-2 run\nto regain lead", "Back-to-back\n3-pointers"),
vjust_lbl = c(1.8, -0.5, -0.5)
)
# Quarter dividers
qt <- data.frame(minute = c(12, 24, 36), label = c("Q2", "Q3", "Q4"))
plot_title <- "line-win-probability · r · ggplot2 · anyplot.ai"
p <- ggplot(df, aes(x = minute, y = win_prob)) +
# Home winning zone: fill between 50% and line when Hawks are ahead
geom_ribbon(
aes(ymin = 0.5, ymax = pmax(win_prob, 0.5)),
fill = HOME_COLOR, alpha = 0.18
) +
# Away winning zone: fill between line and 50% when Wolves are ahead
geom_ribbon(
aes(ymin = pmin(win_prob, 0.5), ymax = 0.5),
fill = AWAY_COLOR, alpha = 0.18
) +
# Quarter dividers
geom_vline(
data = qt, aes(xintercept = minute),
color = INK_MUTED, linewidth = 0.35, linetype = "dotted"
) +
# 50% reference line
geom_hline(
yintercept = 0.5,
color = INK_SOFT, linewidth = 0.55, linetype = "dashed"
) +
# Win probability line
geom_line(color = HOME_COLOR, linewidth = 1.0) +
# Key event markers
geom_point(
data = events, aes(x = minute, y = win_prob),
shape = 21, size = 3.0,
fill = ELEVATED_BG, color = INK, stroke = 0.8
) +
# Key event labels
geom_text(
data = events,
aes(x = minute, y = win_prob, label = label, vjust = vjust_lbl),
color = INK_SOFT, size = 2.4, lineheight = 0.9
) +
# Quarter labels at top of panel
annotate(
"text",
x = c(0.4, qt$minute), y = 0.963,
label = c("Q1", qt$label),
color = INK_MUTED, size = 2.6, hjust = c(0, 0.5, 0.5, 0.5)
) +
# Zone labels
annotate("text", x = 1.5, y = 0.88,
label = "Hawks winning", color = HOME_COLOR,
size = 2.8, hjust = 0, fontface = "bold"
) +
annotate("text", x = 1.5, y = 0.12,
label = "Wolves winning", color = AWAY_COLOR,
size = 2.8, hjust = 0, fontface = "bold"
) +
# Final score
annotate("text", x = 47.2, y = 0.963,
label = "Final: Hawks 108 – Wolves 101",
color = INK_SOFT, size = 2.6, hjust = 1
) +
scale_y_continuous(
labels = scales::percent_format(accuracy = 1),
limits = c(0, 1),
breaks = c(0, 0.25, 0.5, 0.75, 1.0),
expand = c(0, 0)
) +
scale_x_continuous(
limits = c(0, 48),
breaks = c(0, 12, 24, 36, 48),
labels = c("0'", "12'", "24'", "36'", "48'"),
expand = c(0.005, 0)
) +
labs(
title = plot_title,
x = "Game Time (minutes)",
y = "Hawks Win Probability"
) +
theme_minimal(base_size = 8) +
theme(
plot.background = element_rect(fill = PAGE_BG, color = PAGE_BG),
panel.background = element_rect(fill = PAGE_BG, color = NA),
panel.grid.major.y = element_line(color = INK_MUTED, linewidth = 0.2),
panel.grid.major.x = element_blank(),
panel.grid.minor = element_blank(),
panel.border = element_blank(),
axis.line.x = element_line(color = INK_SOFT, linewidth = 0.4),
axis.line.y = element_line(color = INK_SOFT, linewidth = 0.4),
axis.title = element_text(color = INK, size = 10),
axis.text = element_text(color = INK_SOFT, size = 8),
plot.title = element_text(color = INK, size = 12, margin = margin(b = 10)),
plot.margin = margin(t = 16, r = 20, b = 12, l = 12)
)
ggsave(
filename = sprintf("plot-%s.png", THEME),
plot = p,
device = ragg::agg_png,
width = 8,
height = 4.5,
units = "in",
dpi = 400
)
Part of Win Probability Chart on anyplot.ai.