Competitive Balance in Major League Baseball
Bibliographic record
Abstract
Back to the Future The more things change, the more they remain the same. In 1911 Major League Baseball (MLB) owners sold the motion picture rights to the World Series for $3,500. When the players demanded a cut of the proceeds, the owners canceled the deal instead. In 1994 the owners canceled the World Series rather than give in to the players' refusal to accept a salary cap. In 1888 and 1889 New York won back-to-back World Series trophies. In 1998 and 1999 New York won back-to-back World Series trophies. In 1879 the owners implemented a reserve clause, arguing that it was necessary to maintain competitive balance in the league. In 2000 the twenty-first century began with an owners' meeting at which the commissioner was directed to restore competitive balance to the sport. What sparked the owners' recent plea for competitive balance was the change in the economics of MLB that occurred in the 1990s. For some MLB teams the decade was marked by a growth in revenue sources resulting from new stadium construction or an explosion in the value of local media contracts. Since the revenues generated by these sources were not distributed evenly among the leagues' teams, the revenue gap increased markedly (see table 1). In 1990 the Yankees led all MLB teams with total revenues of $98 million, $64 million more than the Mariners who were at the bottom of the league in revenues. By 1999 the Braves led MLB with total revenues of $169.5 million, a staggering $121 million more than Montreal's league low. The growth in the revenue gap translated into a growth in the payroll gap, which increased from $15 to $70 million dollars over the decade. The most significant revenue growth came in the form of venue income (included in Other Revenues in table 1). Since 1989 eleven new stadiums have opened, and two other stadiums have received substantial face-lifts. These stadiums have luxury box suites, seat licenses, naming rights, signage, and other amenities that provide their teams with significant new revenue sources. Also, the new stadiums have facilitated an increase in ticket prices and served as an attraction in themselves, leading to significant increases in gate receipts for their tenants. Local television and radio income (Local Media Revenue, table 1) provided a secondary source of revenue growth. While the Yankees' record-setting cable contract grew only slightly over the decade, the average local media haul increased by nearly 50 percent. This is significant in light of the fact that the MLB low in local media revenue increased by barely $1 million over the decade. For some teams the increase in local media income more than doubled overnight and tripled over the decade. The disparity in revenues became the centerpiece of the economics of baseball in the 1990s. It is now used to sort teams into categories: or large market vs. small market. [1] The revenue gap is considered to be a major problem because of its perceived impact on the competitive balance among teams on the field. One theory is that when there are few barriers to player mobility high revenue teams buy all of the best talent. These teams win the most games, attract more fans, command higher local media fees, and extract ever better stadium lease agreements from their host cities. In contrast, low revenue teams can only afford to sign lower quality players and must rely on unproven talent developed in the Minor Leagues. These teams have losing seasons, do not make the playoffs, and have steadily lost attendance. They have little leverage with which to negotiate media deals or increase ticket revenues. As they lose money they have even less to spend on talent. With their hold on the best players, the hi gh revenue teams prevail on the field, winning more games, pennants, and championships. In time the competitive balance of the league will deteriorate as the high revenue teams dominate play. At least that's how it's presumed it will happen. …
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.004 | 0.001 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.025 | 0.002 |
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".