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Jeff Weaver: Career, Professional career & Amateur career
Jeffrey Charles Weaver (born August 22, 1976) is an American former right-handed Major League Baseball pitcher. During his career, he pitched for the Detroit Tigers, New York Yankees, Los Angeles Dodgers, Los Angeles Angels of Anaheim, St. Louis Cardinals, and Seattle Mariners. He is the older brother of fellow MLB pitcher Jered Weaver.
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Jeff Weaver topic overview
The analysis highlights Career, Professional career and Amateur career as prominent areas in the source structure around Jeff Weaver.
Related topics
64
Source areas
4
Connected nodes
68
Extracted relationships
52
Concept neighborhoods
32
Bridge connections
68
What this topic covers Research coverage
Source areas are shown by the number of related topics found in each part of the analysis. Use smaller areas too: they can reveal specialized angles and content gaps.
Professional career · 43 topics
Amateur career · 10 topics
Overview · 9 topics
Post-baseball career · 2 topics
Smaller areas are not necessarily less important. They contain fewer connections in this analysis and can be useful for finding specialized angles or coverage gaps.
Key facts & relationships
High-confidence facts extracted from structured source data. Use them as anchors for further research.
Earned run average
4.71
Strikeouts
1,214
Win–loss record
104–119
Explore all related topics Closing gaps
A structured outline of related entities, concepts and subtopics. Open any item to build a new map centered on it.
Browse the complete topic structure, not only the most central items. Less prominent entities and concepts can reveal missing angles, specialized context and useful research gaps. Each item opens a new analysis centered on that subject.
Deeper signals for content research, entity SEO and topical coverage. The plain-language headings explain what each technical view is useful for.
How Jeff Weaver connects Entity context
Entity context groups extracted connections by relationship type. Counts show recurrence in the analyzed source; the examples are research signals, not claims about importance.
The extracted context around Jeff Weaver shows recurring relationship patterns in the source. For example, Jeff Weaver → AAA Albuquerque Isotopes, After, Alan Benes, Andy, April, Arizona Diamondbacks, Dodgers, February, He, Isotopes, Jeff, Jered, Jered Weaver, Los Angeles Angels, Los Angeles Dodgers, Major League, May, On June, San Diego Padres, The Another extracted example is Jeff Weaver → Angels, Busch Stadium, Cardinals, Dodgers, He, Jeff, Jeff Weaver's, Jered, July, Louis Cardinals, On July, September, Sports Illustrated, St, Terry Evans, The, Weaver. Use these groups to spot repeated connection types before inspecting the individual relationships.
Jeff Weaver
Top relations
related to Return to the Dodgers· 23
Jeff Weaver → AAA Albuquerque Isotopes, After, Alan Benes, Andy, April, Arizona Diamondbacks, Dodgers, February, He, Isotopes, Jeff, Jered, Jered Weaver, Los Angeles Angels, Los Angeles Dodgers, Major League, May, On June, San Diego Padres, The
related to St. Louis Cardinals· 17
Jeff Weaver → Angels, Busch Stadium, Cardinals, Dodgers, He, Jeff, Jeff Weaver's, Jered, July, Louis Cardinals, On July, September, Sports Illustrated, St, Terry Evans, The, Weaver
Jeff Weaver relationships Subject–Predicate–Object triples
Relationships are represented as Subject → Predicate → Object triples. Confidence describes extraction strength, not the real-world importance of a relationship; lower-confidence rows may be contextual rather than explicit.
TTTA extracted 52 structured relationships around Jeff Weaver. Examples in this analysis include Jeff Weaver → Earned run average → 4.71 and Jeff Weaver → Strikeouts → 1,214. The table shows each extracted connection, where it came from and its confidence.
Subject
Predicate
Object
Confidence
Src
Jeff Weaver
Earned run average
4.71
1.00
infobox
Jeff Weaver
Strikeouts
1,214
1.00
infobox
Jeff Weaver
Win–loss record
104–119
1.00
infobox
Jeff Weaver
related to External links
Career
0.60
section
Jeff Weaver
related to External links
MLB
0.60
section
Jeff Weaver
related to External links
ESPN
0.60
section
Jeff Weaver
related to External links
Baseball Reference
0.60
section
Jeff Weaver
related to External links
Fangraphs
0.60
section
Jeff Weaver
related to External links
Minors
0.60
section
Jeff Weaver
related to External links
Retrosheet
0.60
section
Jeff Weaver
related to External links
Baseball AlmanacJeff Weaver
0.60
section
Jeff Weaver
related to External links
Baseball Almanac
0.60
section
No triples extracted yet.
Related concept clusters Concept neighborhoods
Concept neighborhoods group terms that sit near one another in the extracted graph. They are useful for discovering adjacent language and context, but proximity does not by itself imply a factual relationship.
The concept neighborhoods around Jeff Weaver bring nearby vocabulary together. In this analysis, examples include Jered, Series and First. Use the clusters to find adjacent concepts and terminology that may deserve separate research.
major league baseball
League
Major
Weaver
Baseball
Minor
First
Game
Series
Mariners
Pitcher
Detroit
Louis
new york yankees
New
York
Yankees
Anaheim
Detroit
St
Tigers
Angels
Angeles
Los
Career
Dodgers
los angeles dodgers
Los
Dodgers
Angels
Yankees
Anaheim
Detroit
New
St
Tigers
York
Mariners
Louis
los angeles angels of anaheim
Los
Detroit
New
St
Tigers
York
Dodgers
Anaheim
Angels
Yankees
Angeles
Career
st. louis cardinals
Louis
Mariners
Seattle
Tigers
York
Yankees
Win
Los
Dodgers
New
St
Series
college baseball
Major
League
Weaver
Mariners
Pitcher
Detroit
Louis
Seattle
Tigers
Career
Angeles
First
northwoods league
Major
Weaver
Minor
Baseball
Game
Series
Pitcher
Pitched
First
Season
Dodgers
Games
collegiate summer baseball
Major
League
Weaver
Mariners
Pitcher
Detroit
Louis
Seattle
Tigers
Career
Angeles
First
Connections between topic areas Semantic bridges
Semantic bridges connect parts of the graph that would otherwise be more separate. A bridge is a structural signal in this analysis, not a claim that the two topic areas are equivalent.
For Jeff Weaver, one of the stronger structural bridges in this analysis connects Jeff Weaver with Professional career. Bridges highlight paths between different parts of the map and can reveal research angles that are easy to miss in a flat list.
Number of nodes, edges, triples, density and central hubs. Use it to gauge the size and connectivity of the map.
Jeff Weaver
Nodes69
Edges68
Triples52
Avg. degree1.97
Density0.028986
Components1
Source & methodology
TTTA analyzes the structure around Jeff Weaver to surface related topics, entities, relationships, concept neighborhoods and bridge connections. Use the map to explore areas such as Career, Professional career & Amateur career, including less central topics that may reveal useful research gaps. Automatically extracted connections are research leads rather than rewritten encyclopedia content.
