  Prior studies on mobile app analysis often analyze apps across different
categories or focus on a small set of apps within a category. These studies
either provide general insights for an entire app store which consists of
millions of apps, or provide specific insights for a small set of apps.
However, a single app category can often contain tens of thousands to hundreds
of thousands of apps. For example, according to AppBrain, there are 46,625 apps
in the "Sports" category of Google Play apps. Analyzing such a targeted
category of apps can provide more specific insights than analyzing apps across
categories while still benefiting many app developers interested in the
category. This work aims to study a large number of apps from a single category
(i.e., the sports category). We performed an empirical study on over two
thousand sports apps in the Google Play Store. We study the characteristics of
these apps (e.g., their targeted sports types and main functionalities) through
manual analysis, the topics in the user review through topic modeling, as well
as the aspects that contribute to the negative opinions of users through
analysis of user ratings and sentiment. It is concluded that analyzing a
targeted category of apps (e.g., sports apps) can provide more specific
insights than analyzing apps across different categories while still being
relevant for a large number (e.g., tens of thousands) of apps. Besides, as a
rapid-growing and competitive market, sports apps provide rich opportunities
for future research, for example, to study the integration of data science or
machine learning techniques in software applications or to study the factors
that influence the competitiveness of the apps.
