since 2002

Batter vs Pitcher Matchup

Head-to-head comparison of any MLB batter and pitcher since 1950. Search players below and watch their matchup stats update...

Bryce Harper
Jake Irvin
AB6 HR0 OPS.889
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Ownage chart

Bryce Harper
    not enough matchup data to show
Jake Irvin
Note: given a league-wide OPS of ~.725, the closer the line gets to a player, the more ownage. Min of 5 PA in a season to qualify.

Matchup Ranks

  • SLG.333 .700
  • Hard Hit0% 30%
  • Quality AB56% 75%
  • SB Success0% 15%

Season stats

Harper vs Irvin: 2 Seasons
YrPAABH2B3BHRRBIBBSOBAOBPSLGOPS
20233110000101.0001.0001.0002.000
2024651000011.200.333.200.533
TOTALS962000021.333.556.333.889
Note: OPS color trend requires a min. of 5 PA in a season.

Predicted outcomes

Based on historical data and our prediction model, the probability of various outcomes for a random at-bat (hot streaks aside).

Gets on base (56% OBP)

1B: 22% 2B: 0% 3B: 0% HR: 0% BB: 22% HBP: 11%
1b 2b 3b hr bb hbp

Makes an out (45%)

  • Strikeout: 11%
  • Out (in play): 34%

Latest ABs

Harper vs Irvin: Last 25 ABs
Date Inn Score Count Result Details Hard hit?
8/19/23 - PHI @ WAS1 0-0(0 - 1)HBP-
8/19/23 - PHI @ WAS3 0-0(3 - 2)BB-
8/19/23 - PHI @ WAS6down 0-2(1 - 2)1Bground ball single to right
5/17/24 - WAS @ PHI1 0-0(0 - 0)Outpop fly to third
5/17/24 - WAS @ PHI3up 3-1(3 - 2)Outfly ball to center
5/17/24 - WAS @ PHI5up 4-2(3 - 2)SOstrike out-
4/6/24 - PHI @ WAS1 0-0(0 - 1)Outfly ball to deep center
4/6/24 - PHI @ WAS3up 1-0(3 - 0)IBB-
4/6/24 - PHI @ WAS6up 4-2(0 - 2)1Bfly ball single to shallow left

About Ownage charts

Want a quick look at the seasonal trends of a batter/pitcher matchup? Called Ownage Charts, they're a handy way to see which way the trend is headed. On each chart, the closer the OPS line gets to a player's name, the more ownage and bragging rights. For context, there's a horizontal line that denotes the league-wide OPS of about .725. A minimum of 5 plate appearances in a given season is required to qualify for the chart.

More about our philosophy

Baseball's an individual sport with team goals and nothing's a better example of that than an at-bat. A batter could miss a curve by 2 feet then crush a ball 400 feet the very next time up. Most baseball fans (minus degenerate gamblers) love that unpredictability. On the flip side, models can help predict what may happen and we've developed a variety of algorithms that can be applied to head-to-head matchups. Most rely on a fair amount of data but generally do well when there are at least 15 plate appearances.

Most of the tables above break down the actual head-to-head data in a way that's hopefully more digestable and actionable (i.e., helping you decide to sit or start a SP/batter). The "Predicted" table takes into account a whole bunch of data and tosses it into our at-bat predictive model: previous results, ballpark, weather and more. And, of course, the more historical data the tighter the accuracy. We have plans to release even more granular data, but for now, enjoy and let us know if you have any questions or suggestions.