The Effect of Gamification in Sport Applications

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The Effect of Gamification in Sport Applications
Áron Tóth
Department of Ergonomics and Psychology
Budapest University of Technology
and Economics
Budapest, Hungary
totharon@erg.bme.hu
Dr. Emma Lógó
Department of Ergonomics and Psychology
Budapest University of Technology
and Economics
Budapest, Hungary
emma@erg.bme.hu
Abstract—The effect of gamification in sport applications on
the people’s sporting habits and performance. Due to the counting
number of sensors built into everyday used devices, such as
smartphones and wearable technologies opened the possibility to
a broader user group to track and analyze their own performance
with sport tracking applications in a gamified system, to keep the
users motivated. The aim of the research to measure the effect of
the different game design elements, based on the responses of 21
statements. The results show that it is the least influencing factor
while choosing the application. On the other hand, progression
related game elements showed the most positive impact on the
workout regularity and intensity.
Keywords—gamification, sport application, effectiveness
I.
I
NTRODUCTION
Due to the rise of the infocommunication technologies, mobile
tools and sensors became strong part of the everyday life
(Clarke, 2017). The data gathered from these innovative sensors
are used in several areas and became accessible to the public as
well. CogInfoCom views any kind of hardware or software
component that collects and stores information and allows users
to interact with this information as an infocommunication
system (Baranyi & Csapó, 2012). Previous studies showed, that
such systems could be well adapted into the area of health and
sports. From the hardware perspective, based on doppler
measurements, the fitness activity can be recognized (Fu,
Florian, Arjan, & Vaithyalingam Gangatharan, 2018). From the
software perspective, changing the elderly people’s exercise
habits (Katajapuu et al., 2017), to create a system to store
electronic health records (HER) in the cloud (Adamko, Garai,
& Pentek, 2017), to encourage patients to report their medical
conditions (Toth & Tovolgyi, 2017) and even to help people
with non-standard cognitive characteristics (Izso, 2016).
In this article the sport tracking systems will be examined as
infocommunication system, focusing on smartphones and
accessories are a key subject for amateur and professional
athletes. Such devices are widely used during workouts
(Janssen, Scheerder, Thibaut, Brombacher, & Vos, 2017),
because various sensors are assembled into these devices (e.g.
GPS, gyroscope). Body area networks can encompass a large
variety of different kinds of interactions between the physical
sensors they use and the human biological and cognitive system
(Baranyi & Csapó, 2012). These sensors provide data to the
application used on the smartphone. These applications share
common elements, such as GPS tracking, community,
feedbacks and rewards.
This study aims to provide answer on the preferences of
consumers choice, how satisfied are they with those and the
impact of gamification on the athletes.
II. G
AMIFICATION
Fast-growing research area that uses User eXperience (UX)
design and evaluation methods to build interaction technology
that increases user motivation and engagement across areas of
health, business, and education with an increasing focus on
personalized experiences (Tondello & Nacke, 2018). Deterding
(2011) defined gamification as the use of game design elements
in non-game contexts. Gamification is different from games,
simulations and free play. The differences will be highlighted
based on the Caillois concept (2001). On the vertical axis play
(paida) means the free form of play, not necessary connected to
goals, and game (ludus) structured and rule based, goal
oriented. In this axis, gamification is closer to ludus, thus using
gamification always carries a goal. On the horizontal axes the
gamification does not mean a whole game, it only uses elements
from games that supports the purpose.
Figure 1 - Gamification between game and play, whole and parts
Reference: (Deterding et al., 2011)

The most basic game elements are points, badges and
leaderboards (PBL), that helps the users to track their progress,
compare themselves with others and collect achievement
symbols for excellence (Mekler, Brühlmann, Tuch, & Opwis,
2015).
Yu-Kai Chou’s Octalysis framework (Chou, 2015) is the most
accepted gamification tool to create a gamified environment or
analyze one. The game elements are grouped based on which of
the 8 Core Drives do they aim to motivate in the user.
Furthermore, the Core Drives are arranged in an order to
differentiate those game elements that effects the extrinsic
motivation and those which activates the intrinsic motivation.
In addition, the top part of the framework considered positive
motivations, while the bottom Core Drives are considered to be
more negative (Chou, 2015).
III. T
HEORETICAL BACKGROUND
Gamification elements in the sport applications are key features
to change user’s behavior (Ha, Kang, & Kim, 2017). Generally,
the applications are feedback and reward based (e.g. Strava,
Nike+ Run, Runkeeper, Endomondo). However, there are some
applications that has a bit different approach. Zombies Run
where the runner can see on the screen where the zombies are,
to know which direction to run, so the athlete won’t be catch by
the zombies. Another example, Spotify, the music streaming
application has a feature, that it choses music within a given
genre, that matches to the user’s running pace. Based on the
idea of music, the application Rock My Run provides selected
tracks to match with the heartrate and steps of the athlete.
Based on the Hook Model (Liu & Li, 2016), sport application
provides triggers, in the form of notifications in connection with
planned workout, someone gain upon the user or that a friend
just competed a workout, congratulate him/her. These are
present to make the user open the application and follow
through a certain action. The main goal for each application is
to make the user to track sport related activities and build
connections with other athletes.
During the sport activity instant feedback and progression
tracking are the most commonly used game elements. The
applications generally have a simplified user interface while the
athlete tracks the workout, to provide the user with the most
important data and trends (e.g. speed, distance, location). If the
user created a route to follow during the workout, progress bar
is shown. In Strava, there is an option to switch on the live
segment feature, which enables the athlete to see the stats just
as if all the other competitors were there. Almost like a video
game.
As it was sad earlier, the after-workout feedbacks and reward
mechanisms are the strongest in these applications. From
experience points, to Nike’s Fuel Score, to trophies and
different kind of measurements are in use to provide an accurate
feedback of the training. These elements help to understand and
highlight the key points of the workout, e.g. fastest lap, personal
record, longest workout. Also supports to show the user their
progression overtime.
Some applications reward users by giving badges if they
complete a challenge. Challenges can work as a trigger to the
users by adding a time limit and a goal to complete. Sometimes
these challenges relate to real world events, such as Tour the
France or Mt. Everest, e.g. climb the height of the Mt. Everest
with a bicycle or by running to collect the badge. These events
can provide a narrative to a workout, thus makes it more
interesting. The collected rewards, badges are generally shown
in trophy cases and displayed publicly.
To track progress there are training calendars used in all the
applications and the possibility to set a goal as well. Therefore,
the application always provides feedback on how much the
athlete completed of the goal and how much training needs to
be done.
To sum up, activity tracking systems are trying to gamify the
workout experiences, however, it is mainly datafication, where
the user can monitor activities (Loh, Sheng, & Ifenthaler, 2015).
However it is not all negative, because “Once we datafy things,
we can transform their purpose and turn the information into
new forms of value”(Kenneth, Cukier, & Mayer-schoenberger,
2013).
IV. T
HE RESEARCH
The aim of the research was to identify which game mechanics
in connection with app action are the ones, that trigger the user’s
reaction. The setup was the following: an online questionnaire
was shared on social media pages and groups to reach the target
audience.
The target audience was all the people who use their
smartphones to track their workout regularly. Based on age
restrictions, it was based on the applications regulations, thus
anyone could participate whom was over 13 years old. The next
criteria was to use a smartphone during a workout. Nor the type
of the phone, nor the type of the used sport application was
important. Apart from having previous experience with any
sport application, other regulation was not in use. This resulted,
that anyone whom used a sport application on their smartphone
to track their workout could be suitable to fill out the survey.
The target audience was reached by posting the questionnaire
in groups and pages that showed relevance. These were found
by searching for keywords that are connected to: sports, e.g.
running, biking, workout.
The questionnaire was built up from six parts; (I.) sport specific
questions, (II.) regularity of doing sports, (III.) overall workout
patterns, (IV.) applications used during workouts, (V.)
statements and lastly (VI.) demographic questions.
From the first section (I.) the aim was to see what kind of sport
they practice and if they are / were professional athlete. The
importance was to have the possibility to be able to separate the
professionals and the other participants. The professionals are
more experienced, and they tend to review and understand data
from their workout in more depth. During the analysis, this will
be examined from the results.
The second part (II.) measured the regularity of doing sports
based on three parameters. The (1) first one was the average
duration per exercise. The (2) second aspect was the average
number of workouts per week. The (3) third question aimed to
categorize the intensity of the activity. Based on these three
criteria, an overall score was calculated, between 0 and 126.

In the third sector (III.) the question was about to gather data on
which sport on what regularity does the participant does. It was
essential information to know, to have the possibility of
connecting the rest of the data with each sport.
Furthermore, the next block (IV.) contained 12 questions on the
applications that are used during a workout and the reason
behind choice of those ones. It is important to understand why
the user chose that certain application among the several other
ones. Here the list of applications was gathered based on the top
downloaded numbers in the Apple Store and the Google Play
Store. Also, there was an option to add the name of the
application that they use, however it was missing from the list.
Moreover, in this part the overall usefulness, the overall
satisfaction and their level of recommendation was asked. This
set of questions purpose was to show an overall evaluation of
the applications listed in the research.
The next part (V.) was aimed to measure the characteristics of
the gamification elements in the sport applications. This was
carried out with 21 statements in connection of different
scenarios in the sport tracking systems. The respondent had to
evaluate the statement on a four level Likert-scale, from
strongly disagree to the strongly agree. The novelty of the
research that the statements were assembled based on the
Octalysis framework (Chou, 2015). The 21 scenarios contained
game elements from all the 8 Core Drives. Thus, the different
scenarios that a user generally meets in sport tracking
applications, can be connected to concrete game elements and
grouped based on the Core Drives of the Octalysis.
The last part (VI.) consisted of demographic questions, age,
highest degree of school has completed.
V. T
HE RESULTS
The results are based on 306 responses average age of 29
(standard deviation: 10,55, median: 25, range: 43). The data
shows, the cycling, running and fitness were the sports that
were the most actively done. Biking was the highest among
everyday usage, running and fitness was 1
st
and 2
nd
among the
number of people done it several times a week. This means that
people use their bikes daily, thus not only for clearly
recreational and sport related, but as for commuting.
Figure 2 - Regularities in sports
From the list of sport application available, based on the three
factors introduced in section IV. (usefulness, impression,
recommendation), the highest received score was for Polar,
Garmin, Strava.
Both Polar and Garmin sell professional sports related products,
e.g. watches, thus their programs are the highest rated, might be
because their interest to provide the best tool. The relation
between professionals and non-professionals were around 50%
(Average Dev.: 8%) for all the applications, only exception was
showed at the results of the Garmin users, where around 24%
was professional user. This might be because of the thought
that, if someone, who is not a professional athlete uses
professional tools, they might do better.
Another possible tool to compare the different sport tracking
systems is the Net Promoter Score (NPS). NPS is derived from
a single question that may be included as part of a larger
customer survey. The single question asks the customer to use
a scale of 0 to 10 to rate their willingness and intention to
Figure 3 - Questionnaire responses on applications and NPS
recommend the company to another person. Ratings of 9 and 10
are used to characterize so-called ‘promoters,’ ratings of 0
through 6 characterize ‘detractors,’ and ratings of 7 and 8
characterize ‘passives.’(Jeske, Callanan, & Guo, 2011). The
NPS score varies between -100 and 100. The top 3 scores are in
alignment with the other two factors measured. The reasons
behind the bigger differences between the results of Google
Fitness, Apple Health Kit and Samsung Health could be
because these applications are pre-installed on the devices. To
understand the NPS more research need to be done.
In the 4
th
section of the questions aimed to understand the
importance of each feature for the choice. Based on the results
the most important ones were the free features, The visual and
detail of the workout summary and The stability of the
application. Interestingly, when the question was about the
rewards after each workout, seemed the least important in the
choice. However, the user only meets with the gamified
elements, after the first use of the sport tracking system.
Another result that requires attention is the 10
th
place, the
question about the impact of the friends using the application.
73 76 69 51 62 25 60 35 23 28 7
0
1
2
3
4
5
6
7
8
9
10
Usefullness [average] Impression [average]
0
100
200
300
Number of responses
Daily Multiple time s per week
Once per week Once per month
Occasionally Never

If a friend uses a certain app, that would not make be an
important feature for the athlete to take into consideration.
Table 1- The ranking of the features influencing the users
1=most influential, 10=least influential
More influence Less influence
1 Free features Information during
workout 7
2 visual and detail of the
workout summary Compatibility 8
3 Stability of the
application User Interface – Design 9
4 Ease of use Friend’s use the app 10
5 Accuracy Educational features 11
6 Customization Workout Rewards 12
In the next paragraphs the results from the sport tracking
systems Octalysis focused analysis and the statements will be
introduced.
The overall results indicate that among the game elements
tested in the study, instant feedback, progress bars, earned lunch
and appointment dynamics has effect on the participants.
Instant feedback in sports is one of the most basic game
element, that are used, since during the workout information is
provided about the current state and after finishing the workout
to show the captured data. Progress bars are beneficial mostly
during the workouts, when in the progress is displayed
(duration and distance) visually. Thus, the athlete receives
information on, how much effort is needed to finish the
workout. Earned lunch means, that the user knows the
straightforward actions by which the player can obtain a
reward. A good example would be to complete a challenge,
where the user needs to reach a given meter of elevation (e.g.:
the height of Mt. Everest) or to complete a distance. Game
element appointment dynamics utilize a reoccurring schedule
where users have to take the Desired Action (in this case a
workout) to effectively reach the Win-State (e.g. a race, new
record). This game element was the most positively stated in
the study.
Figure 4 - Sport systems game elements and participants responses
On the other side, the least typical statements follow. The social
elements are considered as one of the key features of the sport
applications. However, the results from the study shows that
game elements in relation to the Social Influence and
Relatedness (Core Drive 5) are the least motivating mechanics.
This result is in parallel of the answers for the preferences to
choose a sport tracking application (See Table 1).
From the results, it can be seen, that users are using the
application mostly to monitor their workouts to complete the
weekly planned routine (Statement: “I like to see that I
completed all the workouts I have planned”), or to see
progression, (Statement: “I am only satisfied with a workout, if
I broke any of my personal records”) received also high points.
Moreover, to see the completion of the weekly workout plan is
also a statement that the majority agrees with. This shows, that
the sport application users are mainly focusing on the data
analysis and to track their progression.
The comparison was done based on the responses to the
statements and the game elements implemented in the sport
tracking systems with the Octalysis framework (See Figure 4).
The sport systems (orange in Figure 4) shows the overall scores
of each Core Drives based on the game elements implemented.
The further from the center, the more game element is used in
connection of that Core Drive.
On the other hand, the responses (marked blue in Figure 4) are
displayed contrary. The marks closer to the center are the ones
that has stronger effect on the athletes.
In this way, the impact of the Core Drives and the game
elements can be compared. This figure shows that the game
elements effects does not fulfill the effect on the athletes.
VI. C
ONLCUSIONS
Gamification is an interdisciplinary area, that is between HCI,
game studies (Xu, 2012), that makes it difficult to analyze the
user’s behavior from all the aspects. During the use of a sport
application several properties influence the athlete’s attitude.
The results of the research shows, the choice of the sport
tracking application is based on objective values, rather
subjective ones. The users are looking for a stable and easy to
use application that provides useful free features. Also, the
reward mechanism at this point are not taken into consideration.
This shows that gamification is not implemented, as an extrinsic
motivation to make people to download the application. In
contrast, it is used to help athletes to from a habit and make the
progression easily understandable.
The net promoter score can add a broad information about the
user’s perception of the application’s usefulness. However, to
understand more about the reason why the users gave certain
NPS, another more detailed questionnaire or a focus group
could be done. This the user’s preferences on why one
application received a higher score than the other could be
determined.
The findings of the study show, that the game elements applied
in sport tracking systems are focusing on datafication. The
Core Drive 1:
Epic Meaning &
Calling
Core Drive 3:
Empowerment
of Creativity
Core Drive 5:
Social Influence
& Relatedness
Core Drive 7:
Unpredictability
& Curiosity
Core Drive 8:
Loss &
Avoidance
Core Drive 6:
Scarcity &
Impatience
Core Drive 4:
Ownership &
Possession
Core Drive 2:
Development &
Accomplishment
Sport system analysis Responses

athletes are motivated by mainly extrinsic rewards, badges,
leaderboards and intensity scores.
This type of reward mechanism combination boosts motivation
during the discovery and onboarding phases, however, lacks the
game design elements to keep the user in the sport tracking
application on the long run. On the athletes, whom has a strong
intrinsic motivation to progress in a sport, the previously
mentioned reward system has a low impact, thus for them these
game elements are negligible. Thus, the analyzed sport
applications lack the possibility to motivate the user on the long
term.
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