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Many professional sport organizations are currently in the process of finding or already using sports information systems (SIS) to integrate data from different information and measurement systems. The problem is that requirements are very heterogeneous. That is why no consistent definition of SIS and their categories exist, and it is often not clear which fields and functions SIS must cover. This work aims to provide a structured comparison of commercial SIS available on the market to provide an overview of the relevant features and characterize categories. Following PRISMA guidelines, a systematic search for relevant SIS providers was conducted. A catalog of 164 review items was created to define relevant features of SIS and to conduct semi-standardized interviews with product representatives. Overall 36 eligible SIS from 11 countries were identified and 21 of them were interviewed. The analysis of the interviews has shown that there are features that are present in all SIS, whereas others differ or are generally less represented. As a result, different SIS categories have been defined. The study suggests a more differentiated categorization of SIS is necessary and terms need to be defined more precisely. This review should be considered when companies designing SIS or sport organizations select SIS.
International Journal of Computer Science in Sport
Volume 20, Issue 1, 2021
Journal homepage:
DOI: 10.2478ijcss-2021-0001
Sports Information Systems: A systematic review
Thomas Blobel1, Martin Rumo2 & Martin Lames1
1Technical University of Munich, Germany, Department of Sport and Health Science, Chair
of Performance Analysis and Sports Informatics
2Swiss Federal Institute of Sport Magglingen, Switzerland
Many professional sport organizations are currently in the process of finding or
already using sports information systems (SIS) to integrate data from different
information and measurement systems. The problem is that requirements are very
heterogeneous. That is why no consistent definition of SIS and their categories
exist, and it is often not clear which fields and functions SIS must cover. This
work aims to provide a structured comparison of commercial SIS available on the
market to provide an overview of the relevant features and characterize
categories. Following PRISMA guidelines, a systematic search for relevant SIS
providers was conducted. A catalog of 164 review items was created to define
relevant features of SIS and to conduct semi-standardized interviews with product
representatives. Overall 36 eligible SIS from 11 countries were identified and 21
of them were interviewed. The analysis of the interviews has shown that there are
features that are present in all SIS, whereas others differ or are generally less
represented. As a result, different SIS categories have been defined. The study
suggests a more differentiated categorization of SIS is necessary and terms need
to be defined more precisely. This review should be considered when companies
designing SIS or sport organizations select SIS.
IJCSS – Volume 20/2021/Issue 1
In competitive sports, several specialized providers offer information systems (IS) dedicated to
handle data from different sources and make this data available to the different users in the
sport organization. Many clubs and associations are currently in the process of installing sports
information systems (SIS) in their organizations and are challenged to find an appropriate
solution for their requirements. Until now, no catalog of criteria approved by sports science
and/or sports informatics is available concerning general requirements of these systems.
Neither a systematic review of existing systems has been done. Therefore, the aim of this work
is to provide a structured comparison of the different commercial SIS on the market.
There is a variety of terms for sports information systems (SIS) and as well as high variability
in the scope of the available SIS-products. No binding definition exists of what exactly is
meant by SIS. For that reason, it is not clear which fields such SIS have to cover and which
features they must provide. Some of the SIS products offered were developed starting from a
specific application (e.g. medical data), which was then extended to other areas in the sport
organizations, or complex information systems from industry were applied to sports. As a
result, we find largely different products involving different software architectures. These
circumstances make it difficult to clearly compare these systems, to define their scope of
performance, and to classify them precisely. In practice, this also led to the frequent use of the
term athlete management systems (AMS) without a clear definition of the term and the features
or areas such a system has to cover. Due to the novelty and diversity of SIS, which have only
emerged in recent years, there is also no systematic overview of the various products, their foci
and features. Despite the diversity of SIS, first of all, a systematic review requires a conceptual
Sport science shows the need for sport organizations to merge information from different units
to provide specific information to individual users and developed the concept of “Sportart-
Informationssystem (Lames, 1997). In the context of this work, all organizations related to
sport are considered as sport organizations (e.g. sports clubs, sports associations and
federations, and sports institutes). The related problem of different units and data sources
involved in training systems (Schnabel, Harre, & Krug, 2014) was addressed by sports
informatics already years ago (Baca, 2006).
Due to the many different terms and different scopes of the systems (Table 1), a working
definition of SIS has to be defined, which mainly refers to information systems (Institute of
Electrical and Electronics Engineers (IEEE), 2017) and “Sportart-Informationssystem”
(Lames, 1997), and relates to the basic subjects of sports informatics (Baca, 2006):
Sports Information Systems (SIS) are information processing systems based on
Information Technology (IT) which, together with the associated sports-organizational
resources, serve to handle data from various sources in sport organizations within one
system and to make this information available user-specific and location-independent
via user interface (UI). SIS should cover all areas of sport organizations, focus sport-
specific processes, be scalable, and integrate methods of data science.
AIS/FIS and CIS are very similar and mainly differ in the structure of the sport organization.
Specialized information systems present data from different sources and generate information
with advanced analyses, typically highly specialized in a field of expertise. For example, a
training information system (TIS) can cover the planning and analysis of training sessions
and, for this purpose, contain a training exercise database and import and merge data from
tracking systems or other sensors.
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Table 1. Categories and short descriptions of information systems in sport.
Category Description
Sports Information Systems (SIS) The overarching term for all information systems
used in sport, to handle data of different sources an
generate information.
Association / Federation Information
Systems (AIS/FIS)
SIS with a high focus of merging data from
different decentralized locations and sources, for
one sport (e.g. national football federation) or for
different sports (e.g. Olympic sports federation).
Club Information Systems (CIS) SIS used in sport organizations that are mainly
located in one place in terms of facilities and staff
(e.g. clubs).
Specialized Information Systems: Specialized SIS to merge and present data from
different sources, but with high focus and expertise
on a specific field.
• Match Information Systems (MaIS) Specialized in different sources for match data.
• Medical Information Systems (MIS) Specialized in data of the medical department. The
system does not necessarily have to be sport-
specific, as the same requirements often exist in
other medical facilities.
• Load Information Systems (LIS) Specialized in data from different sources of load
assessment, mostly analyzed by the fitness coaches
or the medical department.
• Training Information Systems (TIS) These systems support the coaches in the planning,
implementation, and evaluation of training units.
• Scouting Information Systems (ScIS) These systems integrate large player databases
(player scouting) or match databases (match
scouting) and support the scouts in planning events,
centralizing reports and analyzing scouting data.
Athlete Management Systems (AMS) IT-based systems, primarily used to manage
individual athletes and groups, documenting and
storing related data of different fields, and control
objectives, with little focus on information
generation and distribution.
There is considerable overlap between SIS and AMS, the latter term being quite common in the
practical field. The Institute of Electrical and Electronics Engineers (IEEE) (2017) defines
management systems as a “set of interrelated or interacting elements to establish policy and
objectives and to achieve those objectives”. Referring to the notion that AMS could be defined
as IT-based systems, primarily used to manage individual athletes and groups, documenting
and storing related data of different fields, and control objectives, not covering the whole sport
organization and with little focus on information generation and distribution. For this paper,
SIS are considered as the overarching category, which includes various subcategories, and
AMS are one of these subcategories.
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In a recent paper, Blobel and Lames (2020) present a general concept of club information
systems (CIS) based on models of software engineering, training science, and business
intelligence (BI) from the perspective of an application in sports. It provides a CIS-architecture
and lists different features of CIS. This CIS-concept was supplemented and generalized to SIS.
The listed features of CIS provided a starting point for a criteria-based catalog with different
SIS items in different categories. This catalog then may serve as a template for a comparison of
the SIS products.
The general objective of this study is a structured and standardized analysis of the SIS products
available on the market. Additionally, it seeks for a basic understanding of SIS and determines
and defines relevant features for an SIS. The single products then are scrutinized with respect
to whether they dispose of these features. The results should provide valuable information to
SIS users or organizations in sports practice that intend to introduce an SIS.
The detailed objectives of this paper are as follows: Objective 1 is to give a systematic
overview of SIS products at the market and to provide general information about the products
(type, domain). Objective 2 is to list the detailed features of the SIS and to assess whether the
examined products dispose of them. Objective 3 is to characterize product categories of SIS
and the classification of the reviewed SIS.
Systematic Search Strategy
According to the PRISMA (preferred reporting items for systematic reviews and meta-
analysis) guidelines, a systematic search of relevant software providers was conducted (Moher,
Liberati, Tetzlaff, & Altman, 2009). PRISMA guidelines have already been used in the field of
sports, for example, in reviews on investigation trends and match analysis in football
(Sarmento et al., 2014; 2018).
Due to the unclear definitions and terms of SIS described above, complementary methods of
identifying relevant software products were chosen: the initial approach was identification
through personal contacts with experts in the field. Additionally, various lists on SIS were
included, which were found during the research (a market analysis of a company, a product
comparison of an SIS provider, and an AMS buyers guide (Glaeser, 2017), published in public
domain). Finally, a web search was performed. In contrast to literature reviews that rely on
literature databases like PubMed, IEEE Explore, or Science Citation Index, this is a product
review. As commercial products are offered presumably without exception on the internet on
product websites they may be found with major search engines. Therefore, the web search was
conducted on Google as the largest provider with the most comprehensive search index. The
web search via Google was done between 5th of May 2020 and 12th of May 2020 for relevant
results updated within the last 24 months, using the keyword combinations shown in Table 2.
Due to the large number of unspecific results, additional keywords were added as filter criteria.
As the number of hits per keyword combination showed high variability, below 100 hits, all
results were examined, and above 100 hits, only results classified as most relevant by Google,
were selected. This Google classification is based on an internal ranking system of Google
using different algorithms, which are applied to the search string entered (Google LLC, 2020).
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Table 2. Keyword combinations with additional terms to specify results at web search.
The inclusion criteria for the companies were: (1) providers of sport specific software
products; (2) commercially available products; (3) functionality for team/athlete management;
(4) at least two different areas in the club must be covered; (5) merging different data sources;
(6) language English or German.
Hits were excluded from this review if they (1) did not offer their own software, only used
software from another provider or offered consulting services; (2) were custom made
solutions; (3) applied unspecific software to sports data for a use case; (4) offered only
software for private use and hobby athletes; (5) covered only one field within a sports club.
First, uniform resource locator (URL), title, and short description of the suggested hits were
checked for exclusion criteria. Mismatches and duplicates were sorted out. Then, the website
of the remaining hits was visited to get more details about the company and its product. The
final hits were either existing software products that met the inclusion criteria, existing
software that was just developing an extension to meet these criteria, or software in
development that met these criteria with the first product version.
Development of the Review Item List
Due to the great differences between the SIS, their large scope, and the various features, it was
important to create a standardized basis for the review. The requirements of such SIS led to a
list of different required items for the review. This review item list allowed an independent and
equal analysis of the different SIS. To define the requirements for SIS, the CIS-concept of
Blobel and Lames (2020) was used as a starting point, where some system requirements are
already mentioned.
Keyword Combination Additional terms to include (+) or exclude (-) results
sports information systems /
information systems in sports
+software; -management
club information systems +software
‘athlete management systems’;;;;;
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Figure 1. Categories for items for comparison from the CIS concept of Blobel and Lames (2020).
Figure 1 shows the categories and sub-categories for the items of comparison and their origin
in the different components of the CIS concept in Blobel and Lames (2020). The category
“G. Company & Support” was added being obviously relevant for the purpose of this review.
For each category, respective sub-category, specific items of comparison were developed. The
item selection was mainly based on practical experiences with some SIS from a user
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Figure 2. List of 164 review items and the number of products with the respective item as count and color
Figure 2 shows the final item list. It contains 164 items that were checked for presence in each
product. To avoid a second large table, the frequencies of each item among the 21 examined
systems are given here numerically and color-coded as a leap ahead to the results section.
IJCSS – Volume 20/2021/Issue 1
Assessing SIS-items
In principle, the required information on the items of comparison could have been obtained by
a detailed study of the web pages of the provider. Some arguments speak against this method.
First, given the large number of 164 items, it is more than likely that some items are not
mentioned on the website although being present in the product. Second, as product
descriptions on the web site of the provider try to draw a positive image of the product, it is
necessary for a valid comparison to confirm the content expressed by an item. Finally,
denomination and meaning of the items on the web site and in our catalog may differ, so that a
common understanding is desirable. These reasons led to the conduction of semi-standardized
interviews with product representatives (Berekoven, Eckert, & Ellenrieder, 2009).
The low number of available products made it necessary to ensure a high response rate, which
is increased by personal contact. This also prevents companies' fears that the information might
be requested from competitors. The required information was collected according to the review
item list (Figure 2), which was transformed into a checklist for the interview questionnaire.
The interview procedure was semi-standardized and all interviews were conducted by the same
interviewer (TB). When appointments had been arranged, the general conditions were
explained. The interview was scheduled for one hour and was held in English or German, with
the help of video conferencing tools. Interviews were prepared by prior transfer of information
from the product website to the questionnaire. Each item of the checklist was gone through
linearly via screen sharing, and answered by using the options 1 = Yes, product disposes of
item; 2 = No, product does not dispose of item; and 0 = No Answer (NA). The answers were
entered directly into the checklist. In case of uncertainties, the interviewer re-phrased the
question, and the interviewed expert could explain the item further, which was taken note of. If
needed, the interviewer could explain the questions further or, in case of doubt, ask for details.
The product representative also had the opportunity to make additional comments (Meffert,
Burmann, Kirchgeorg, & Eisenbeiß, 2019).
After the interviews, the companies were given the opportunity for debriefing. The general
information and short description of the product, as well as the checklist reviewed by the
interviewer, were sent to the company representative for review, and a deadline for response
was defined. Any proposed changes were worked out with representatives of the company
until they were accepted. Only after this the product was marked completed. The results on
each product were entered in a spreadsheet and presented as tables and radar charts. Since the
products are very different, a comparison can only be made on the number of criteria a
particular product has.
Systematic search
The identification through personal contacts and suggestions led to 29 products. The third-
party lists delivered 27 products. Web search delivered a total of 139 results for the particular
term combinations with the additional keywords for the selected period. After a more extensive
analysis of the websites, this number decreased to 27 (Figure 3). After merging the results of
these three sources and eliminating duplicates, a total of 47 products was remaining.
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Figure 3. PRISMA flow chart of the different phases of the systematic review.
In a detailed analysis of each company website of the combined results, the inclusion and
exclusion criteria were applied to all products, reducing the number to 36 for interviews. The
reasons for the exclusions were: the same company distributed the software through two
channels with a different focus (n = 1); the website was offline (n = 1); product was only a
smartphone app for individual athletes (n = 2); product was offered by a consulting company
(n = 2); product was a use case of business software by using sports data (n = 4).
The companies were contacted through different channels, depending on availability. Existing
personal contacts were used to find an appropriate interview partner. Otherwise, the website
was searched for contact details and a mail to a specified contact person was sent. If this was
not possible, the contact form was used. The contact persons were approached in each case by
e-mail with a predefined and personalized text explaining the context of the survey, offering an
initial talk, and giving a deadline for response. If no answer came before the deadline, a second
mail was sent and another deadline set. The response rate was quite high (100 %) for personal
or direct contacts, but much lower for contacts through a web form (25 %). After a positive
answer, an appointment for an interview via video conference was scheduled. At the end of the
PRISMA process, 21 companies were interviewed and included in the review.
Overview of the different reviewed SIS provider and general information
Table 3 shows a list of all interviewed companies with general information and a short
description of product-specific characteristics. 18 companies operate worldwide, three are
restricted to regions (Europe/USA, Europe, or Germany). For companies with two locations,
only the main location was included. 16 companies stated that they supply all sports. Three
cover team sports, one individual sports, and one only football. The mean experience of the
companies in the field of SIS is 9.8 (± 5.5) years.
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Table 3. Overview of the reviewed SIS with additional information and short description.
Table 4 shows the 15 companies that were identified as eligible SIS but did not participate in
the review as they did not respond to the request (Figure 3). Since no information could be
requested directly, information available on the internet was used. Therefore, the categories
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supported countries and main sports were not included, as this information was incomplete on
the websites. The mean experience of the excluded companies in the field of SIS is 10.0 (± 6.4)
years. The founding date of the companies was mainly taken from the online database
Crunchbase (, accessed: 14th of November 2020).
Table 4. Overview of the excluded SIS with additional information and short description based on information
available on the internet.
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Figure 4. Number of all eligible SIS systems (n = 36) and the country of the product company.
A total of 36 products from ten different countries were identified as eligible SIS (Figure 4).
The majority (n = 19) came from Europe; the country with the most systems was the USA.
Results for SIS Items
The following section presents the detailed analysis of the interview items. The single data
points show the summarized answers of the interviewed experts for each item
(maximum = 21).
Figure 5. Number of SIS covering different fields within clubs.
Figure 5 provides an overview of the different fields/departments the SIS cover. Five fields
were included in all SIS in the review (team management; strength & conditioning;
performance analysis; data analysis; system administration). Only six SIS include the business
area (e.g. marketing, ticketing, or accounting). The coverage of the other areas is quite
different in the various systems. This is revealed by an item-based look on the particular fields.
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Figure 6. Detailed analysis of different fields within SIS.
Figure 6 provides a more detailed view of the different fields of SIS. It is notable, that less
than half of the SIS allow changes in the data model (B4). Strength and conditioning (B.III),
training management (B.VII), sport science (B.VIII), and athlete (IX) seem to be standard
fields for SIS because they are provided at every reviewed product. Except for the training
drawing tool (B55) and special attributes (B68), the specific features within these fields are
balanced at a high appearance and have been named in at least 17 of the products.
The situation is different with video analysis (B.VI). Although 20 providers noted that they
covered this field, the distribution of the included features was different. Except for cloud
video storage (B45), all other features in this area were mentioned less than 14 times. The
opportunity to live tagging (B49) was mentioned least often (n = 7). Most SIS that cover the
medical field (n = 18) are balanced in terms of features and eight of the nine features are
presented in at least 15 products. In scouting (B.IV), the ticketing for scouts (B30) stands out,
which less than half of the products stated. For match and match preparation (B.V), eight of
nine features were named in at least 14 of the 16 products. Only the animation tool (B43) is
less represented.
IJCSS – Volume 20/2021/Issue 1
Figure 7. General of an SIS and general right governance for user.
Figure 8. Charts of different fields of SIS.
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As can be seen in Figure 7 at technology and licensing (C.I), all 21 companies offer their SIS
as a cloud-based (C1) solution and charge a license fee (C6). The other features here are quite
diverse. At software architecture (SWA) and adjustments (C.II), 20 of the products offer
modular (C10) architecture, and six provide an architecture in the form of a building kit
(C13). For detailed right governance (D), 15 of the products offer detailed right governance
(D1) and/or also 15 offer preset user profiles (D4).
Figure 8 shows for mobile access (E) that all of the systems provide ubiquitous access (E1)
and responsive design (E2). For user interface (F), all features are named by at least 16 of the
products. At support (G), six of the nine features (G6 – G11) are named by at least 16 products
or more. It was slightly different for the update policy (G12 – G14). For security (H), the
answers are highly balanced. Within the field of interfaces (I) QHDUO\ DOO SURGXFWV  
provide features to import and export data (I1 – I5). For data analytics and reporting, only the
features of integration of programming languages (J4) and implementation of analysis into the
UI (J7) were represented by less than 17 of the products. At reporting (J.II), all features were
named for at least 20 products.
Product Categories of SIS and Classification of the Reviewed Products
Figure 9. Taxonomy of sports information systems to show different categories, their relations and
Based on the definitions of Table 1, a model of the various systems and their relations to each
other has been developed (Figure 9). The overarching category is SIS, as defined in the
introduction. Within this SIS, there are two categories: AIS/FIS and CIS. There is a big overlap
between these two categories. Both categories cover all or at least most of the fields within a
sport organization and also have a strong focus on information generation and distribution. The
main difference is the structure of the location of the sport organization, i.e. centralized for CIS
and decentralized for AIS/FIS, which requires different system architectures. In the intersection
between these two categories, specialized information systems are placed that may have a
similar structure like systems on a higher level, but which are limited to a specific field of
expertise. For this reason, they can exist independently or act as a part of the higher-level
systems. AMS play a special role in this scheme because they could also contain specialized
information systems, but with a focus on management instead of information generation.
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The result of the classification of the reviewed products in product categories was as follows:
four products have been classified as AIS/FIS. CIS represented the largest group with nine
products. Three products have been classified as AMS. Within the category of specialized
information systems, there are two sub-categories: MaIS (n = 2) and TIS (n = 1). As none of the
reviewed products was a classic MIS or LIS, because in each case a system for player load
monitoring was included in the MIS, both system categories were combined in this review, and
two SIS fell into this combined category. No stand-alone ScIS participated in this study, instead
the scouting field was typically part of the higher system categories of AIS/FIS or CIS (n = 14).
Figure 10. Different strategies for SIS software architectures.
Two basic strategies can be distinguished in software architecture of SIS (Figure 10). On the
one hand, there is an all-in-one approach of a large software provider with many components
offered either as a whole or as different modules. Within this strategy, almost no suite can
cover all areas, and very often, additional third-party add-ons are required. In this case, one
selects the suite that best meets the requirements (= best-of-suite (BoS)). That strategy means
that the processes within the organization will be determined strongly by the process and
functions of the specific software architecture and must perhaps be adopted. The advantage is a
well synchronized all-in-one solution. The disadvantage is that probably not all areas are
covered and one cannot use the best individual systems on the market. With the best-of-breed
(BoB), on the other hand, specialized standard software components from different providers,
as well as custom software, are integrated. The organization selects the software for each area,
or even specific process, that best addresses their needs. This strategy focuses on internal
processes and searches for the best software solutions, but neglects cohesion between
departments, limiting overall perspective. That leads to fragmented and isolated data silos that
could be overcome and merged by a central platform that combines the data of the specific
software and provides it to all users. But therefore, another software platform is needed that
interfaces each single software solution used within the organization. The advantage is that the
platform can grow and systems can also be replaced. As a disadvantage, there could be
problems in the interaction of the systems (Light, Holland, & Wills, 2001). For the reviewed
SIS, a third approach is the most common. It can be described as a hybrid approach of BoS and
BoB. The SIS has basic integrated components as well as connections to other special software
serving just as platform. The number of integrated and externally connected components varies
considerably between the products examined.
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The aim of this paper was to systematically review available SIS on the market and to provide
an overview of the relevant features, based on the CIS-concept of Blobel and Lames (2020).
Systematic Search
Within this work, 36 products were identified as eligible SIS based on the PRISMA
Guidelines. Despite this systematic approach, it cannot be guaranteed that all systems on the
market were detected which raises the issue of representativity. The problem lies in the missing
binding standardized (= retrievable) product definitions but even more in the dynamics of the
market. New products continuously enter the market, existing products disappear, providers
are taken over by other companies with or without continuing to offer the product under the
same or a different name, or specialized systems become SIS by adding functionalities.
The decision to do an interview-based instead of a web-based review has reduced the number
of SIS products included in this review to only 21 of the 36 detected products. This is
regrettable, but in this case quantity was sacrificed to completeness and validity. As website
entries are meant for advertising the product, information on specific items may be biased.
Also, it would have remained unclear whether an item is not detected because it is not part of
the product or just not listed. Moreover, items could be described in a way making it difficult
to attribute unambiguously a certain category and thus make sure comparability between
products. For these reasons, interviews with product representatives were conducted accepting
a reduced number of reviewed products.
Overview of Different Reviewed SIS Products and General Information
The objects of this review are quite diverse, as it included established SIS as well as start-ups,
complete solutions, and special solutions. The major objective was not to conduct a detailed
qualitative comparison per item, but to give an overview on the SIS market and the prevalence
of a list of potentially relevant features based on a catalog of criteria. For this purpose, it was
sufficient to cover a large number of existing systems and to take a detailed view only on
presence and absence of the respective fields at each SIS.
An examination of the countries of origin shows that all products included here come from
Western countries (Figure 4). One reason for this is the limitation to English and German. It
may be assumed that countries, such as China or Russia, with their highly structured sports
programs, also have systems to manage athletes and their data. Moreover, it is also possible
that national and customized solutions have been developed for own purposes but are not
available on the open market. The comparatively high number of systems from Germany is
most likely a result of the search strategy relying besides a web search also on personal
contacts of the authors. Nevertheless, 36 systems from 11 different countries in a
comparatively small market document a high degree of diversity and shows that this topic is of
relevance in many countries, both justifying a systematic review.
Detailed Fields and Features of the Reviewed SIS
The following section focuses on selected SIS items, discussing them in detail, and explaining
their general impact and their importance for sport organizations.
When looking at the different fields at sport organizations, it is obvious that certain standard
fields are part of all or most of the SIS. It is notable that the business area (A14) is covered by
very few SIS (Figure 5). This shows that SIS were primarily designed for the sports area at the
clubs. One reason may be the strong separation between sports and business within most sport
organizations, even though there is a strong overlap here as well. For example, an official
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diagnosis of an injury is important for the public relations department or a player's playing
time affects the bonuses that are defined in his contract and are therefore relevant for
accounting and controlling. Thus, many reasons speak in favor of integrating a business
Less than half of the SIS allow the manipulation of the data model (B4). Especially for data
analysis, this could be important, because a predefined data model often does not provide the
necessary data structure for specific analyzes, making it impossible or complicated
workarounds are necessary. The medical field (B.II) as a standard in sport organizations is not
covered by all of the systems. On the one hand, this may have to do with the special
characteristics of this area or, on the other hand, with the fact that special legal requirements
and certificates are necessary in some cases. The features at scouting (B.VI) are covered quite
similar. Only the ticketing for scouts (B30) is an outlier, but as part of the planning and
organization of many scouts at different events and locations, this is a very important
requirement in sports practice. For league data (B31 & B40), there is an overlap to match
preparation (B.V), because both fields use match data, but in a different way. Well-structured
and effective access to these data for both areas can create synergies and thus enhance the
added value of such SIS. The structure of video analysis (B.VI) is very diverse at the reviewed
SIS products. The reason could be the complexity of these tools. There are specialized software
products, and it is difficult to reproduce the full functionality, which some SIS providers have
learned the hard way. Here, we find BoS and BoB (Figure 10) solutions as well. While the
former may have the advantage of being an all in one solution, the latter offers greater
independence by replacing or adding video analysis tools. For storage, various SIS offer video
cloud storage (B45) for media files, others integrate external cloud storage optimized for video
files into their SIS or linking streaming platforms. Practice shows that live tagging (B49) is a
priority demand of coaches, especially in the youth sector, to set their pre-defined tags directly
during the match. If there is no separate video analyst this can be helpful to reduce the work for
post-processing. Surprisingly, not all SIS include the management of training exercises (B51 –
B53). A closer look shows that these features are not included in the actual system but could be
integrated by a third-party tool. One positive finding is that sports science (B.VIII) aspects are
strongly represented in the reviewed products. This creates a sport-specific focus, to become
more than just a general information system. Accessing the whole database (B58) is an
important feature of it to develop analyses in other data analysis tools, especially if they are
more advanced and not included in the SIS standard analysis.
All systems offer cloud services (C1), and only a few still offer desktop (C2) solutions, mostly
for special applications like video analysis to have better performance. The possibility of
hosting the SIS on club servers (C3) is still important for some sport organizations, as they do
not trust cloud solutions. However, these concerns are now disappearing more and more. Most
SIS support common browsers (C5) and therefore have no limitation on the operating system
(C4). The difference between C4 and C5 is explained by the fact that one SIS only supports
one operating system for its desktop application for video analysis. Because cloud services
generate regular costs for running and maintenance server and update the software, SIS
providers follow modern standards of regular license fees (C6). Most SIS providers have
recognized the need for scalability due to different initial situations and sporting developments
and offer different modules (C10). Software architecture (SWA) is usually fixed. Open
architecture could pose a threat to the stability of the system, and sport organizations typically
do not have the capabilities to develop their own software to be integrated.
IJCSS – Volume 20/2021/Issue 1
Not all SIS offer detailed right governance (D1), but instead only preset user profiles (D4).
Sport organizations are structured very differently in terms of size, departments, and
responsibilities. Inflexible user profiles can, therefore, become a challenge in terms of access
For mobile access (E), the SIS are very similar. Only mobile web pages (E3) do not seem to be
so common (n = 13). This technology is maybe not very popular, or companies prefer to invest
the resources in developing and maintaining mobile apps (E4) to provide more regulated
applications. Mobile web pages could be an interesting opportunity, to provide more flexible,
device independent and easier to maintain solutions for mobile access. Especially in the
diverse and fast changing environment of sport organizations. However, this must be decided
depending on the specific requirements.
A user-specific presentation (F4 – F6) of content seems to be important for user interfaces (F).
But if it becomes more specific, there are differences between the SIS that have to be
In principle, all typical support (G) services are offered for the selection and implementation of
SIS. The update policy is slightly different and must then be checked more closely when
selecting the SIS.
All SIS provide general security (H) standards. Only GDPR (H3), as a European regulation,
was not covered by two non-European providers.
Since SIS should help to centralize different data sources, the products in general offer
corresponding interfaces (I) for importing and exporting data. Because these questions have
not been further specified, problems may occur with unusual formats and interfaces and must
be checked before. In the case of common source systems, auto feeds (I6) and partnerships
(I7) can be relevant to simplify data import. Especially for unusual source systems, a general
API (I8) of the SIS could be useful to import the data.
At first glance, the area of data analytics and reporting (J) seems to be well covered. It appears
that the topic of machine learning (J2) is also relevant here, but the results do not provide any
insights on how it is implemented in each case. It is important to make the results of the data
analyses directly accessible to the users in the organization to increase the acceptance and use
of these methods. But not all SIS allow the integration of the analyses into the user interface
(J7) or integrate programming languages (J4) in the architecture of the SIS. This means that
access to the analyses and the workflow for the analyses differ enormously between different
SIS. It can range from direct integration of the developed analyses in the SIS user interface to
intricate access via external tools and extensive import and export processes. One consequence
of this may even be that analyses demanded by staff cannot be realized at all. However, this
does not hold in general but requires a qualitative inspection of the specific SIS with precise
use cases.
Product Categories
The categorization (Table 1 and Figure 9) was made only for the 21 reviewed SIS since there
was not enough information available for all eligible SIS to also classify and include them.
However, it also illustrates the diversity of the SIS, which requires a more detailed
classification, even if it is difficult to make a strict distinction between the different categories.
This often depends on the areas covered in sport organizations and the focus of the particular
SIS. In general, each system requires athlete management and the integration of different data
sources. For this reason and referring to the results of the classification it appears, that very
few systems can be classified as real AMS. The majority are information systems with different
IJCSS – Volume 20/2021/Issue 1
foci. Nevertheless, for a better understanding, it is important to define different categories and
to assign the systems according to their characteristics and scope.
The classification of the SIS cannot be strictly separated into BoS, BoB, or hybrid system
architecture (Figure 10). In sports, there are too many different fields and source systems for
one provider to cover all of them. Therefore, it is rather a wide range of different hybrid
models, which tended either more strongly to BoS or BoB. Each SIS must offer interfaces to
different source systems, sometimes even to other SIS. However, such a classification is
important for the strategy of the software providers, but also for the selection of SIS at the
Limitations of this work
In some cases, there are quite large time differences between the different interviews, as the
identification of the product and the execution of the interview lasted long. Therefore, and due
to the dynamics of the SIS market, this study can only provide a snapshot. However, this is
only partially relevant for this study, since the main objective is to provide a general overview
of existing SIS and the representation of the different features from a CIS concept. It would be
worthwhile to build up and continuously update an SIS product database.
Although the questionnaire already contained 164 items, the results were too general in several
fields. For some questions, not only further details but also the specification of the features
would have been of interest. The interview was consciously kept at this level, as each interview
already lasted about one hour, and a more detailed interview would have considerably reduced
the participation of the companies. Besides, more detailed questions in the individual fields
would probably have required several experts from the company. This study intended to
provide a more general overview, but one the entire range of SIS. More detailed follow-up
studies of individual fields of such SIS can then be based on this.
The categories were developed based on SIS definitions. The term athlete management
systems (AMS), which is commonly used in practice, was restricted. This can lead to
controversies, as definitions in other studies on this topic may be different. SIS and its
subcategories in the context of this study are IT-based systems, and therefore a corresponding
definition from the field of information technology has been used. The standards of IEEE
(Institute of Electrical and Electronics Engineers), IEC (International Electrotechnical
Commission), and ISO (International Organization for Standardization), which can be
regarded as valid and widely used, were chosen for this work.
As this study shows, the term AMS applies to only a few available systems or may be
misleading, as it does not include the essential component of information generation. It is
therefore recommended to refer to the systems in general as SIS or then more specifically as
AIS/FIS or CIS. The study entails conclusions for at least three different areas addressed below.
Conclusions for Sports Informatics
A large number of different IT systems in sport, with different data and informatics methods,
requires an interdisciplinary approach, which sports informatics should address as a linking
discipline. Sports informatics disposes of the necessary interdisciplinary knowledge from
computer science, sports science, and sports practice that is required for the development and
implementation of such SIS (Perl, 2003).
IJCSS – Volume 20/2021/Issue 1
Sports informatics must demonstrate more strongly that it has the necessary domain know-how
that is relevant for the development of such SIS. To this end, sports informatics should be more
aware of its potential as an applied science in order to combine specific theoretical knowledge
of the disciplines involved and transfer it into SIS development and sports practice. In practice,
theoretical models from the field of sports science should guide the design of SIS.
Conclusions for SIS Companies
The review provides a market overview for SIS companies to position their product. For
example, missing features can be identified to adapt their product and close gaps to other
providers. On the other hand, it can also be used to cover a niche if necessary, if the company
is not big enough to develop a complete CIS/FIS/AIS.
Central findings from the review and the CIS concept of Blobel and Lames (2020) can also be
used to adapt the respective product. For example, the modularity, integrated analyses, user-
specific content, and usability of the systems are very relevant.
The review also shows that the providers offer opportunities for using the SIS from a sports
science perspective. This indicates that sports science is primarily seen from the user
perspective of SIS, which requires access to such systems but has less influence on the basic
architecture. Therefore, it is recommended to include domain know-how from sports science in
the development of such SIS. Especially the integration of sports informatics is suggested,
which can build an interdisciplinary bridge between SIS providers, sport practice and sport
Conclusions for Sport Organizations
This study provides a product overview to sport organizations and also lists the various
features they should consider for a precise product selection. Besides, this work can be used to
carry out the requirements analysis of the sport organization in advance. This must be done
independently of the possible products and requires the determination and documentation of
the internal source systems, data structures, processes, stakeholders, and fields of application
of such SIS. It is important to be able to map essential internal processes in SIS. For example,
major problems could arise if the software architecture of the SIS is not suitable. Furthermore,
the analysis of short, medium, and long-term goals is necessary to select a product that not
only fits the current needs but also future demands.
The selection of a suitable SIS is only one step and requires the integration of the SIS into the
internal processes and the adaptation of these processes. Clear communication within the sport
organization is important, which explain the investment and commits to the use of the system.
It also requires the employment of a qualified staff, who is acknowledged by the other
departments, is given sufficient time resources and a clear mandate to implement the SIS in the
sport organization as a continuous task in collaboration with all users. These fundamental steps
are necessary not only to buy suitable and powerful SIS but also to fully exploit its potential for
advancing the entire organization.
IJCSS – Volume 20/2021/Issue 1
Baca, A. (2006). Computer science in sport: An overview of history, present fields and future
applications (Part I). International Journal of Computer Science in Sport, 5, 25–35.
Berekoven, L., Eckert, W., & Ellenrieder, P. (2009). 0DUNWIRUVFKXQJࣟ PHWKRGLsche
and practical application] (12th ed.). Wiesbaden: Gabler.
Blobel, T., & Lames, M. (2020). A Concept for Club Information Systems (CIS) - An
Example for Applied Sports Informatics. International Journal of Computer Science
in Sport, 19(1), 102–122.
Glaeser, C. (2017). A Buyer’s Guide for Athlete Management System Software. Retrieved
May 28, 2020, from
Google LLC. (2020). Google Search - Discover How Google Search Works. Retrieved July
27, 2020, from
Institute of Electrical and Electronics Engineers (IEEE). (2017). ISO/IEC/IEEE International
Standard - Systems and software engineering - Vocabulary [PDF file].
Lames, M. (1997). Unterstützung von Training und Wettkampf [Support of Training and
Competition]. In J. Perl, M. Lames, & W.-D. Miethling (Eds.), ,QIRUPDWLNLP 6SRUW
Ein HanGEXFK>&RPSXWHUVFLHQFHLQVSRUWV$KDQGERRN@ (pp. 170–187). Schorndorf:
Light, B., Holland, C. P., & Wills, K. (2001). ERP and best of breed: a comparative analysis.
Business Process Management Journal, 7(3), 216–224.
Meffert, H., Burmann, C., Kirchgeorg, M., & Eisenbeiß, M. (2019). 0DUNHWLQJࣟ*UXQGODJHQ
instruments, practical examples] (13th ed.). Wiesbaden: Springer Gabler.
Moher, D., Liberati, A., Tetzlaff, J., & Altman, D. G. (2009). Preferred reporting items for
systematic reviews and meta-analyses: The PRISMA statement. BMJ (Online),
339(7716), 332–336.
Perl, J. (2003). Sportinformatik [Sports Informatics]. In H. Haag & B. Strauß (Eds.), TW4.5
Theoriefelder der Sportwissenschaft [Theoretical Fields of Sports Science] (2nd ed.,
pp. 77–95). Schorndorf: Hofmann.
Sarmento, H., Clemente, F. M., Araújo, D., Davids, K., McRobert, A., & Figueiredo, A.
(2018). What Performance Analysts Need to Know About Research Trends in
Association Football (2012–2016): A Systematic Review. Sports Medicine, 48(4),
Sarmento, H., Marcelino, R., Anguera, M. T., CampaniÇo, J., Matos, N., & LeitÃo, J. C.
(2014). Match analysis in football: a systematic review. Journal of Sports Sciences,
32(20), 1831–1843.
Schnabel, G., Harre, H.-D., & Krug, J. (2014). TW2 Trainingslehre - 7UDLQLQJVZLVVHQVFKDIW
Leistung - Training - Wettkampf [Training theory - WUDLQLQJ VFLHQFH performance -
training - competition] (3rd ed.; J. Krug, Ed.). Aachen: Meyer & Meyer Sport.
With the evaluation of the software industry, a huge number of software applications are designing, developing, and uploading to multiple online repositories. To find out the same type of category and resource utilization of applications, researchers must adopt manual working. To reduce their efforts, a solution has been proposed that works in two phases. In first phase, a semantic analysis-based keywords and variables identification process has been proposed. Based on the semantics, designed a dataset having two classes: one represents application type and the other corresponds to application keywords. Afterward, in second phase, input preprocessed dataset to manifold machine learning techniques (Decision Table, Random Forest, OneR, Randomizable Filtered Classifier, Logistic model tree) and compute their performance based on TP Rate, FP Rate, Precision, Recall, F1-Score, MCC, ROC Area, PRC Area, and Accuracy (%). For evaluation purposes, I have used an R language library called latent semantic analysis for creating semantics, and the Weka tool is used for measuring the performance of algorithms. Results show that the random forest depicts the highest accuracy which is 99.3% due to its parametric function evaluation and less misclassification error.
Full-text available
In professional sports clubs, the growing number of individual IT-systems increases the need for central information systems. Various solutions from different suppliers lead to a fragmented situation in sports. Therefore, a standardized and independent general concept for a club information systems (CIS) is necessary. Due to the different areas involved, an interdisciplinary approach is required, which can be provided by sports informatics. The purpose of this paper is the development of a general and sports informatics driven concept for a CIS, using methods and models of existing areas, especially business intelligence (BI). Software engineering provides general methods and models. Business intelligence addresses similar problems in industry. Therefore, existing best practice models are examined and adapted for sport. From sports science, especially training systems and information systems in sports are considered. Practical relevance is illustrated by an example of Liverpool FC. Based on these areas, the requirements for a CIS are derived, and an architectural concept with its different components is designed and explained. To better understand the practical challenges, a participatory observation was conducted during years of working in sports clubs. This paper provides a new sports informatics approach to the general design and architecture of a CIS using best practice models from BI. It illustrates the complexity of this interdisciplinary topic and the relevance of a sports informatics approach. This paper is meant as a conceptional starting point and shows the need for further work in this field.
Full-text available
Systematic reviews should build on a protocol that describes the rationale, hypothesis, and planned methods of the review; few reviews report whether a protocol exists. Detailed, well-described protocols can facilitate the understanding and appraisal of the review methods, as well as the detection of modifications to methods and selective reporting in completed reviews. We describe the development of a reporting guideline, the Preferred Reporting Items for Systematic reviews and Meta-Analyses for Protocols 2015 (PRISMA-P 2015). PRISMA-P consists of a 17-item checklist intended to facilitate the preparation and reporting of a robust protocol for the systematic review. Funders and those commissioning reviews might consider mandating the use of the checklist to facilitate the submission of relevant protocol information in funding applications. Similarly, peer reviewers and editors can use the guidance to gauge the completeness and transparency of a systematic review protocol submitted for publication in a journal or other medium.
Full-text available
Abstract The main focus of this paper was to review the available literature on match analysis in adult male football. The most common research topics were identified, their methodologies described and the evolutionary tendencies of this research area systematised. A systematic review of Institute for Scientific Information (ISI) Web of Knowledge database was performed according to PRISMA (Preferred Reporting Items for Systematic reviews and Meta-analyses) guidelines. The following keywords were used: football and soccer, each one associated with the terms: match analysis, performance analysis, notational analysis, game analysis, tactical analysis and patterns of play. Of 2732 studies initially identified, only 53 were fully reviewed, and their outcome measures abstracted and analysed. Studies that fit all inclusion criteria were organised according to their research design as descriptive, comparative or predictive. Results showed that 10 studies focused predominantly on a description of technical, tactical and physical performance variables. From all comparative studies, the dependent variables more frequently used were "playing position" and "competitive level". Even though the literature stresses the importance of developing predictive models of sports performance, only few studies (n = 8) have focused on modelling football performance. Situational variables like game location, quality of opposing teams, match status and match half have been progressively included as object of research, since they seem to work as effective covariables of football performance. Taking into account the limitations of the reviewed studies, future research should provide comprehensive operational definitions for the studied variables, use standardised categories and description of activities and participants, and consider integrating the situational and interactional contexts into the analysis of football performance.
Full-text available
Enterprise resource planning (ERP) software is the dominant strategic platform for supporting enterprise-wide business processes. However, it has been criticised for being inflexible and not meeting specific organisation and industry requirements. An alternative, best of breed (BoB), integrates components of standard package and/or custom software. The objective is to develop enterprise systems that are more closely aligned with the business processes of an organisation. A case study of a BoB implementation facilitates a comparative analysis of the issues associated with this strategy and the single vendor ERP alternative. The paper illustrates the differences in complexity of implementation, levels of functionality, business process alignment potential and associated maintenance.
Dieses bewährte Standardwerk liefert Studierenden im Bachelor- und Masterprogramm sowie Praktikern umfassende Grundlagen des Marketingmanagements und widmet sich eingehend allen neuen Entwicklungen der marktorientierten Unternehmensführung. In der 13. Auflage wurden alle Kapitel überarbeitet. Insbesondere wurden neue Entwicklungen im digitalen Marketing umfassend berücksichtigt. Die Autoren zeigen u.a. die Auswirkungen der Digitalisierung auf die Customer Journey und erläutern neue Methoden der digitalen Informationsgewinnung (Big Data). Der Marketing-Mix wurde um Abschnitte zur Preisgestaltung im Internet, zur Multichannel-Distribution und zur digitalen Kommunikation ergänzt, während die Themenfelder Customer-Relationship-Management (CRM), Beschwerde- und Key Account-Management sowie Corporate Social Responsibility (CSR) erstmals Einzug in den Lehrbuchklassiker erhalten. Mit diesem umfassenden Blick auf das Marketing wird die neue Auflage ihrem Ruf als "Bibel des Marketings" (w & v - werben und verkaufen) weiterhin gerecht. Der Inhalt • Konzeptionelle Grundlagen des Marketing • Käuferverhaltens- und Marketingforschung • Marketingziele • Marketingstrategien • Marketing-Mix • Marketingorganisation und -implementierung • Marketingcontrolling Prof. Dr. Dr. h.c. mult. Heribert Meffert ist Professor der Betriebswirtschaftslehre, insbesondere Marketing, und emeritierter Direktor des Instituts für Marketing am Marketing Center Münster (MCM) der Westfälischen Wilhelms-Universität Münster. Prof. Dr. Christoph Burmann ist Inhaber des Lehrstuhls für innovatives Markenmanagement (LiM) an der Exzellenz-Universität Bremen. Prof. Dr. Manfred Kirchgeorg ist Inhaber des SVI-Stiftungslehrstuhls für Marketing, insbesondere E-Commerce und Crossmediales Management, an der HHL Leipzig Graduate School of Management. Prof. Dr. Maik Eisenbeiß ist Inhaber des Lehrstuhls für ABWL, insbesondere Marketing, an der Exzellenz-Universität Bremen.
Computer science in sport: An overview of history, present fields and future applications (Part I)
  • A Baca
Baca, A. (2006). Computer science in sport: An overview of history, present fields and future applications (Part I). International Journal of Computer Science in Sport, 5, 25-35.
Google Search - Discover How Google Search Works
  • Llc Google
Unterstützung von Training und Wettkampf [Support of Training and Competition
  • M Lames
Lames, M. (1997). Unterstützung von Training und Wettkampf [Support of Training and Competition].
A Buyer’s Guide for Athlete Management System Software
  • C Glaeser
Glaeser, C. (2017). A Buyer's Guide for Athlete Management System Software. Retrieved May 28, 2020, from