Methodology

Data Basis

The dataset aims to reconstruct the most complete Order of Battle (OOB) possible based on available information.

All identified units are displayed within the structure. Units for which detailed data exists can be expanded in the explorer, while those lacking vehicle-level information remain non-expandable. Units with no available data are explicitly marked as "No Data Available."

The objective is to present the OOB as comprehensively as possible, while maintaining the archive’s primary focus on vehicle-level composition rather than serving as a purely structural or administrative OOB reference.

The reconstruction process combines primary sources, standard organizational tables, and doctrinal interpretation. Whenever possible, original wartime reports are used as the foundational source for this archive.

From 1943 onwards, unit compositions are primarily derived from original German wartime documents such as Gliederungen, Lageberichte, Meldungen, and other strength and combat reports.

For earlier periods (1939–1942), where such detailed records are often unavailable, compositions are reconstructed using standard organizational tables (K.St.N.), total vehicle allocations from wartime reports, and delivery or production records for the relevant period.

Additionally, the archive provides contextual information about the theater of operations and front in which a unit was active at a given time. This is intended to offer operational context rather than a detailed account of military actions.

Representation Rules

The explorer displays the reconstructed unit structure in full, including units without available vehicle data.

Units with associated vehicle data can be expanded to reveal their internal composition, while those without such data remain non-expandable. Units for which no information is currently available are explicitly marked as "No Data Available."

Vehicle assignments are shown at the lowest level supported by the available sources, typically at company or platoon level, depending on data resolution.

K.St.N. references are displayed at company level. If a specific platoon operates under a distinct K.St.N., it is shown inline with the company reference.

Search bar will provide guidance if a given unit is Main, Independent or Organic. Unist Structure will show the full OOB of the Main Unit where the Organic Unit beloongs to. Same case will apply to Independent Units if in any given snapshot, they are assign to a Main Unit.

Reconstruction Principles

Standard organizational tables (K.St.N.) are used as the primary structural reference for unit construction. Vehicles are assigned at platoon level whenever possible, based on the level of detail provided by the sources. Distribution within subunits follows general German doctrinal principles, aiming to maintain balanced combat effectiveness.

K.St.N. references are displayed at company level. When a specific platoon operates under a distinct K.St.N., it is shown inline with the company reference. This reflects current system constraints, and future versions are expected to allow K.St.N. attribution at the appropriate hierarchical level.

For support elements, where sources often provide only aggregate quantities, equipment is distributed proportionally to ensure minimum functional capability across subunits.

Scope and Limitations

Panzergrenadier, Infantry, and Volksgrenadier units: infantry battalion composition is not yet fully modeled due to the complexity of vehicle types and distribution. In these cases, only support elements at battalion or company level are represented.

Panzer and Sturm units representation focuses on armored fighting vehicles as the primary combat elements; support components such as staff and supply elements are simplified or omitted.

Divisional headquarters are not represented in detail, as they function primarily as administrative structures rather than combat formations.

Closing Note

This archive represents a structured effort to bridge the gap between theoretical organization and documented operational reality.

As new material becomes available, both the dataset and its methodological framework will continue to evolve.