Geology’s Grip on Baseball: Investigating the Sedimentology, Mineralogy, and Physical Properties of Baseball Rubbing Mud
Bibliographic record
Abstract
Major League Baseball (MLB) prepares a minimum of 156 baseballs for each game by rubbing them with mud, sourced from the same company since the 1950’s (Baseball Rubbing Mud, n.d.). This mud is intended to add grip and color to the baseball in a way that ensures competitive consistency across the league. Despite its long-standing use, the geologic characteristics of this mud and its precise effects on the baseball are still poorly understood. In this study, we analyze the mineralogy and physical properties of the baseball rubbing mud in the context of its depositional environment in a tributary of the Delaware River near Philadelphia. Samples of game-used and new baseballs were analyzed with Scanning Electron Microscopy (SEM), along with SEM analysis of the un-applied mud. These data were supplemented with X-Ray Diffraction (XRD), Particle Size Distribution (PSD), and Rock-Eval of the mud itself. Results show that the mud is composed primarily of non-swelling clays (Kaolinite, Chlorite, and Illite/Mica) and quartz, with minor amounts of other components. SEM images show that the clays primarily accumulate in the pores, adding the desired color to the baseball, while the coarser quartz grains serve as a scouring material, inducing scratches, micro-cracks, patches of erosion, and occasional flaking of the leather. This provides minor grip enhancement to the ball without significantly altering ball aerodynamics. The lack of swelling clays also prevent overly slippery or inconsistent grip in the presence of moisture. While muds could be sourced from different locations, changing the location of mud collection would result in variations in composition, grain size, and color that could alter the grip and color uniformity in ways that could provide competitive inconsistencies.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".