Marcus Stroman was among the top free agent pitchers this offseason, so when the Chicago Cubs signed him, it was natural to wonder how he’d do in notoriously breezy Wrigley Field. But history was of no help: Despite 173 starts in a career that began eight years ago, Stroman has never pitched there.
While analytics can’t yet project how Stroman will perform in the varying winds of the Friendly Confines, innovative work by a baseball statistics site using detailed weather data may be an important step toward that goal.
Wrigley Field is the only big league stadium I haven’t pitched at in my career. Crazy. Can’t wait to call it home! @Cubs— Marcus Stroman (@STR0) December 1, 2021
The baseball statistics website FanGraphs now displays data on individual players in varying atmospheric conditions: temperature, barometric pressure, elevation, air density and, of course, wind speed and direction. The data, collected by OpenWeather, goes back to the 2010 season.
These breakdowns, known as “splits,” most likely won’t have managers filling out the lineup card with an eye on the weather vane — but to FanGraphs’s creator and owner, that’s not the point.
“It’s one extra piece of the puzzle for analyzing what players are doing,” said David Appelman, an Arlington, Va., resident.
The study of weather’s effects upon baseball is no academic exercise. Real-life wins and losses are at stake. For example, in a season’s early weeks, fans and front offices shouldn’t overreact to a lethargic offense, because it’s long been known the cool of spring favors pitching and batters warm up as the summer does.
Also consider that a breeze of just 10 mph can substantially change a flyball’s path — making a difference of 35 feet, according to Alan Nathan, a University of Illinois professor who studies the effects of physics on baseball. In baseball terms, FanGraphs said a player’s slugging percentage, a measure of a hitter’s batting productivity, varies by 35 points (or the difference between 0.773 and 0.738, for example) depending on whether an airborne ball is aided by a tail wind or deterred by a head wind.
Now take into mind that Stroman, playing last season for the New York Mets, faced the most batters in the MLB when the wind was blowing out at 10 mph or greater.
“We just put this data out there, thinking, ‘This is stuff people might be interested in, so let’s see what they do with it,’ ” Appelman said. “There had been weather research, but there wasn’t an easy place to go and query baseball data based on weather.”
So what does Appelman expect to emerge from this? “I generally think with weather data, a lot of what people suspect is true will turn out to be true. There may be some surprising findings, but much of it seems to intuitively make sense.”
Appelman anticipates these splits will draw at least one specific audience: players of daily fantasy sports (DFS). In DFS, as the name suggests, athletes are selected every day, so it makes sense to compare a ballplayer’s past performance against the weather forecast for his game.
“There are a number of people in the DFS space who take weather data very seriously,” Appelman said. “It’s either baked into daily projections, or a lot of it people are doing on their own.”
While FanGraphs’ weather splits are a notable milestone, they, too, are something of a blunt instrument considering the limitations of collecting data. Nathan, the University of Illinois professor, noted that while wind plays a huge role in the game, it’s one of the hardest factors for which to account. Measuring velocity and direction at a single point is easy — but throughout an entire ballpark?
“We live in a three-dimensional world: X, Y and Z,” Nathan said. “In a stadium, you look at the flags mounted in various places, and the wind is different in different locations at the same time.”
And that brings it back to Stroman. Nobody knows how he’ll be affected by Wrigley’s winds until the Cubs open the season with a home series against the Milwaukee Brewers.
Still, FanGraphs can answer: Last year, how did Stroman perform when the wind was blowing out? Not too great.
With the caveats of a small sample size and how yesterday’s results guarantee nothing about tomorrow, the stats say he got roughed up: His earned run average (ERA) was 4.30 amid the unfavorable winds while that number for the whole season was 3.02.
But a closer look at the data tells a more complicated story. His poor ERA when winds were blowing out had more to do with batters hitting the balls into gaps. Despite facing 103 batters in winds that could send a deep flyout over the fence, how many homers did he give up?