Can We Measure the Pressure an Offense Puts on a Defense?
Is there a way to define and measure the pressure that hitters and baserunners can put on an opposing defense?
Power remains the clearest path to scoring runs in Major League Baseball. A home run removes the defense from the play entirely.
In addition, walks create baserunners without requiring a ball to find grass. Strikeouts end plate appearances without giving the defense an opportunity to make a mistake. There is a reason the three true outcomes explain so much of modern offense.
There is also a reason players and fans from previous generations occasionally watch the modern game and wonder why a player doesn’t steal a base, take the extra 90 feet or do anything to make the defense complete a play.
These complaints are not always delivered with much statistical support. “Manufacturing runs” can become a catch-all endorsement of bunts, hit-and-runs and any other tactic that reminds someone of baseball in 1987.
But buried somewhere beneath the nostalgia is a reasonable question. Does forcing the defense to execute carry measurable offensive value?
Once the ball enters play or a runner reaches base, the defense still has work to do. Fielders must convert uncertain chances into outs. Pitchers must control the running game. Outfielders must make accurate throws, cutoff men must complete relays and defenders must apply tags.
Quantifying pressure is an attempt to measure at least part of the value the small-ball delegation has been yelling about.
Defining Pressure
“Pressure” is a word often associated with fast, aggressive or contact-oriented teams. Those descriptions are intuitive, but they are too broad to measure.
Simply counting stolen bases rewards teams that create more opportunities. Counting every ball in play treats a routine popup the same way as a difficult groundball in the hole. Counting successful advances ignores the attempts a team declined and the outs it made.
A useful framework would have to separate how often an offense creates pressure opportunities, how aggressively it acts when those opportunities appear and how much value those decisions produce. Those concepts are related, but they are not interchangeable.
A team can create significant pressure without running unusually often. It can be aggressive but inefficient. It can also run selectively and still produce substantial value. This metric was designed to consider those distinctions.
Creating Pressure
The first component of my pressure framework measures how often an offense creates situations in which the defense must respond. That begins with reaching first base (“first base creation”). A plate appearance that ends with a runner at first introduces stolen base opportunities, first-to-third decisions and the possibility of advancement on subsequent contact.
The framework also isolates balls in play with an estimated out probability between 20% and 80%. These are the plays in the uncertain middle: difficult enough that an out is not guaranteed, but manageable enough that the defense is expected to have a legitimate chance to record the out.
My objective is to measure how often the offense forces the defense to complete a non-guaranteed play, and this avoids treating contact as inherently valuable. A routine fly ball does not create meaningful pressure simply because a defender catches it. A ball that requires range, a clean exchange or an accurate throw does.
Measuring Aggression Relative to Opportunity
Once runners reach base, the pressure framework considers aggression. That means it tracks stolen base attempts, first-to-third advances, runners scoring from second and several types of tag-up decisions.
However, raw totals are not enough. A team that attempts 100 steals in 200 opportunities is behaving differently from one that attempts 100 in 400. The same applies to every advancement category. Aggression, therefore, has to be measured relative to the opportunities that a team creates.
The value of those decisions also has to be compared with the alternative of the runner holding at his base. A successful advance is not automatically a good decision, just as an unsuccessful one is not necessarily reckless.
The relevant question is whether the expected benefit of taking the next base justified the risk of making an out. This distinction separates productive pressure from activity for its own sake.
What the Metric Measures — and What It Does Not
My pressure framework measures (1) how often an offense creates defensive responsibilities with uncertain outcomes and (2) how effectively it pursues additional bases.
It is not a hustle score. It is not a direct measure of speed. It does not quantify psychological pressure, and it does not assume aggressive baseball is automatically better baseball. It is also not an alternative to overall offensive metrics such as wRC+, OPS or runs per plate appearance.
Most importantly, it should not be used to make the argument that singles, stolen bases and extra-base advances can replace home runs. The generation that wants to make that case does not receive complete vindication here.
Pressure is a complementary offensive dimension. It is not superior to the three true outcomes. It describes what a team does after those outcomes can no longer explain a play.
Does the Pressure Framework Add Meaningful Information?
To test this question, I built a team-level model using home run rate, walk and hit-by-pitch rate, and strikeout rate as the inputs.
From 2021 through 2025, that TTO model explained 68.2% of the variation in team runs per plate appearance. That is a strong baseline. Power, plate discipline and strikeout avoidance account for most of the basic structure of offense.
Adding pressure creation and context-adjusted aggression increased adjusted R² from 68.2% to 74.6%.
That 6.4-percentage-point improvement represents roughly a 20% reduction in the variation the original model left unexplained.
Aggression also maintained a positive independent relationship with run production after controlling for home runs, walks and hit-by-pitches, strikeouts, and first base creation. Its standardized coefficient was positive and statistically significant at β = 0.169 with a p-value below .001.
This means the metric is not simply identifying good offenses and assigning them another favorable label. It is capturing information that the foundational offensive variables did not fully explain.
That relationship should still be interpreted directionally rather than causally. In other words, these findings do not prove that every team would score more by instructing its runners to become more aggressive. The specific players in question, the game state and the opportunity quality still determine whether an attempt is worthwhile.
Still, what my findings do show is that pressure represents a real and measurable part of run creation.
Complaints about modern offenses never “forcing the issue” are not entirely without merit. They just needed an opportunity-adjusted framework and a few thousand lines of data to support their point.
More Than One Way to Create Pressure
Pressure is valuable. The next question to answer is where that value comes from.
The Los Angeles Dodgers produced the most gross pressure runs in the five-year sample I tested, despite carrying an essentially league-average aggression profile.
That result captures why pressure cannot be reduced to stolen bases or a simple mandate to run more often. The Dodgers created so many offensive opportunities that even conventional decisions generated significant cumulative value.
Other teams followed a very different path. For instance, Tampa Bay, Cleveland, Kansas City and Milwaukee repeatedly attempted more advances than expected. Some teams paired that aggression with strong execution. Others accepted lower efficiency in exchange for greater volume.
Those differences raise the more interesting baseball questions.
Is aggressive always better? Is a team’s “pressure identity” driven more by the organization itself or by the players on its roster? Can teams without elite power use these skills to narrow a slugging disadvantage?
Those are questions I will explore in Part 2.
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