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Marc Esserman: Career, Professional career & Scholastic career

Marc Esserman (born July 28, 1983) is an American chess player who currently holds the FIDE title of International Master (IM).

Language: English [EN]
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Marc Esserman topic overview

The analysis highlights Career, Professional career and Scholastic career as prominent areas in the source structure around Marc Esserman.

Related topics
40
Source areas
5
Connected nodes
45
Extracted relationships
5
Related term clusters
15
Bridge connections
45

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 · 23 topics
Scholastic career · 9 topics
Overview · 3 topics
Teaching and writing · 3 topics
Other interests · 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.

Born
(1983-07-28) July 28, 1983 (age 43) Miami, Florida
Country
United States
FIDE rating
2438 (August 2026)
Peak rating
2474 (April 2016)
Title
International Master (2009)

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Marc Esserman

Explore all related topics Closing gaps

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.

Overview

Scholastic career

Professional career

Teaching and writing

Other interests

For the semantics nerds

You can skip this section if you’re here for content ideas and keyword inspiration.

Advanced semantic analysis

How Marc Esserman connects Entity context

The extracted context around Marc Esserman shows recurring relationship patterns in the source. For example, Marc Esserman → (1983-07-28) July 28, 1983 (age 43) Miami, Florida Another extracted example is Marc Esserman → United States. Use these groups to spot repeated connection types before inspecting the individual relationships.

Marc Esserman

Top relations

Born · 1
Marc Esserman → (1983-07-28) July 28, 1983 (age 43) Miami, Florida
Country · 1
Marc Esserman → United States
FIDE rating · 1
Marc Esserman → 2438 (August 2026)
Peak rating · 1
Marc Esserman → 2474 (April 2016)
Title · 1
Marc Esserman → International Master (2009)

Important terminology

Use these terms to understand the vocabulary surrounding the topic, not as a checklist for keyword stuffing.

Important terminology

esserman chess games open marc fide defeated 2011 morra im 2009 2016 international 1st world champion 2010 game tournament gambit

Marc Esserman relationships Subject–Predicate–Object triples

TTTA extracted 5 structured relationships around Marc Esserman. Examples in this analysis include Marc Esserman → Born → (1983-07-28) July 28, 1983 (age 43) Miami, Florida and Marc Esserman → Country → United States. The table shows each extracted connection, where it came from and its confidence.

SubjectPredicateObjectConfidenceSrc
Marc EssermanBorn(1983-07-28) July 28, 1983 (age 43) Miami, Florida1.00infobox
Marc EssermanCountryUnited States1.00infobox
Marc EssermanFIDE rating2438 (August 2026)1.00infobox
Marc EssermanPeak rating2474 (April 2016)1.00infobox
Marc EssermanTitleInternational Master (2009)1.00infobox

Related concept clusters Related term clusters

The concept neighborhoods around Marc Esserman bring nearby vocabulary together. In this analysis, examples include Fide, Master and Title. Use the clusters to find adjacent concepts and terminology that may deserve separate research.

  • Marc Esserman
    • Fide
    • Master
    • Title
    • International
    • Player
    • Games
    • Marc
    • Chess
    • 1st
    • August
    • Gambit
    • Game
  • marc esserman
    • Fide
    • Master
    • Title
    • International
    • Player
    • Games
    • Marc
    • Chess
    • 1st
    • August
    • Gambit
    • Game
  • chess
    • Marc
    • Games
    • Esserman
    • August
    • Club
    • Fide
    • Harvard
    • States
    • United
    • Master
    • Title
    • Boston
  • boylston chess club
    • Marc
    • Games
    • Esserman
    • August
    • Boston
    • Club
    • Esserman's
    • Fide
    • Four
    • Harvard
    • League
    • March
  • united states chess league
    • States
    • United
    • League
    • Marc
    • Born
    • Master
    • Title
    • Games
    • Esserman
    • August
    • Boston
    • Chess
  • internet chess club
    • Marc
    • Games
    • Esserman
    • August
    • Boston
    • Club
    • Esserman's
    • Fide
    • Four
    • Harvard
    • League
    • March
  • chess life
    • Marc
    • Games
    • Esserman
    • August
    • Club
    • Fide
    • Harvard
    • States
    • United
    • Master
    • Title
    • Boston
  • international master
    • Title
    • Master
    • Marc
    • August
    • Player
    • States
    • United
    • Later
    • Champion
    • Gambit
    • Im
    • World

Connections between topic areas Semantic bridges

For Marc Esserman, one of the stronger structural bridges in this analysis connects Marc Esserman 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.

Min side: 3
Marc Esserman — Professional career · splits 22 ⟂ 24
Marc Esserman — Scholastic career · splits 36 ⟂ 10
Marc Esserman — Overview · splits 42 ⟂ 4
Marc Esserman — Teaching and writing · splits 42 ⟂ 4
Marc Esserman — Other interests · splits 43 ⟂ 3

Map overview Semantic statistics

Marc Esserman

Nodes46
Edges45
Triples5
Avg. degree1.96
Density0.043478
Components1

Source & methodology

TTTA analyzes the structure around Marc Esserman to surface related topics, entities, relationships, concept neighborhoods and bridge connections. Use the map to explore areas such as Career, Professional career & Scholastic career, including less central topics that may reveal useful research gaps. Automatically extracted connections are research leads rather than rewritten encyclopedia content.

Source: Wikipedia — Marc Esserman · EN edition · Analysis: TopicsToTalkAbout

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