If you’ve ever wondered why Monkeystats doesn’t emphasize stats like RBI, OPS, or Runs Created, the short answer is: those stats can be misleading, especially outside of Major League Baseball.
What Is BaseRuns?
BaseRuns (BsR) is a run estimator originally developed by David Smyth and later refined and popularized by sabermetric analysts like Tom Tango.
Instead of crediting runs after the fact (like RBI), BaseRuns models the run-scoring process itself. It asks:
Given how often an offense gets on base, advances runners, and makes outs, how many runs should it produce?
This approach turns out to be remarkably accurate. Among major run estimators, BaseRuns is widely regarded as one of the best at matching real-world scoring, including in environments that don’t look like MLB.
Why Context Matters (and Why BaseRuns Handles It Better)
Many “standard” stats quietly assume a fairly normal professional baseball environment. But recreational baseball and softball often aren’t normal:
- Some leagues average 3–4 runs per game
- Others average 15–20+ runs per game
- Fielding quality varies a lot
- Pitching depth varies even more
In a low-scoring game, a home run is extremely valuable. In a high-scoring game, simply reaching base can be just as valuable, because big innings are built on traffic. BaseRuns adapts to these realities naturally.
If every batter hit a home run, each would be worth exactly one run.
If every batter walked, each walk would also be worth one run.
That sounds obvious, but many stats fail this logic test. BaseRuns doesn’t.
Why Not OPS?
OPS is convenient because it’s simple: it adds On-Base Percentage (OBP) and Slugging Percentage (SLG).
The problem is that OPS isn’t a true run model. It:
- can double-count certain contributions,
- doesn’t reflect how innings actually unfold, and
- becomes less reliable as scoring environments drift away from “normal MLB.”
OPS is fine as a quick shorthand. It’s just not the stat I want driving the “who helped us score runs” question, especially for rec leagues.
Why Not Runs Created?
Runs Created was a major step forward historically, and it’s still interesting. But one classic issue shows up when you apply it to individual players: it can treat a player’s own on-base events and power events as if they “interact with themselves,” which can inflate values for certain stat lines.
In plain English: it can start behaving as though a single player is hitting in every lineup spot, which isn’t how baseball works.
BaseRuns avoids this pitfall by modeling the run-scoring process in a way that plays more nicely with real-world lineup context and a wide range of scoring levels.
Why BaseRuns Ignores RBI and Runs Scored
RBI and runs scored are resultant stats, not component stats. They depend heavily on:
- lineup position,
- teammates getting on base ahead of you,
- teammates driving you in behind you, and
- the random sequencing of events.
Two identical hits can produce wildly different RBI totals depending on whether the bases happened to be empty or loaded. BaseRuns focuses on what the hitter actually controls: getting on base, advancing runners, and, most importantly, avoiding outs.
What BaseRuns Does Not Measure (Yet)
BaseRuns is intentionally context-neutral. A hit in the first inning and a hit in the last inning are treated the same. A bases-empty double and a bases-loaded double are valued based on the underlying event, not the moment’s drama.
That’s not because “clutch” doesn’t exist, it’s because measuring it properly requires play-by-play data, including:
- inning and score,
- base/out state,
- leverage,
- and the sequence of events.
Stats like Win Probability Added (WPA) are great for that kind of analysis, but they require details Monkeystats does not yet track. (Live scoring and play-by-play are on the long-term roadmap.)
The Bottom Line
Monkeystats uses BaseRuns because it:
- models how runs are actually scored,
- holds up in any scoring environment,
- avoids misleading assumptions,
- scales from youth leagues to adult rec leagues,
- and focuses on what players truly control.
It’s not the flashiest stat. But for this app, where leagues vary wildly and the goal is clarity and fairness, it’s the most honest one.
Further Reading
- BaseRuns overview (Wikipedia): https://en.wikipedia.org/wiki/Base_runs
- Runs Created overview (Wikipedia): https://en.wikipedia.org/wiki/Runs_created
- Win Probability Added (Baseball-Reference): https://www.baseball-reference.com/about/wpa.shtml
- BaseRuns discussion article (FanGraphs / The Hardball Times network): https://tht.fangraphs.com/base-runs-and-carl-hubbell/