PoloTrac: A Water Polo Tracking and Advanced Statistics

Application

Nathan Verlin

, Joey Gullikson

, John Mayberry

and Daniel Cliburn

Department of Computer Science, University of the Pacific, 3601 Pacific Ave., Stockton, California, U.S.A.

Department of Athletics, Water Polo, University of the Pacific, 3601 Pacific Ave., Stockton, California, U.S.A.

Department of Mathematics, University of the Pacific, 3601 Pacific Ave., Stockton, California, U.S.A.

Keywords: Water Polo, Tracking, Advanced Statistics, Mobile Application, Usability Testing.

Abstract: PoloTrac is an iOS mobile application designed to allow coaches, players, and spectators to record water polo

game events as they happen in real-time. PoloTrac contains features of a standard score-keeping application

(such as a functioning scoreboard, clock, and foul counter), however, PoloTrac also calculates and produces

post-game reports that provide advanced statistical output. This is accomplished by allowing the user to input

the location, type, tactic, and outcome of every shot attempted during a match. These reports are intended to

aid in determining player performance, team performance and the effectiveness of certain strategical methods

on scoring goals. While PoloTrac contains features recommended by top collegiate water polo coaches, these

features are designed to be accessible to users from all areas of water polo (from amateur to professional).

1 INTRODUCTION

Water polo is a competitive, aquatic sport that has

been played around the world for over a century.

Being the first team sport in the Olympic Games,

water polo has been a staple in high-level competitive

sports at the amateur, collegiate, and professional

levels (Escalante et al., 2011). The landscape of sports

statistics has changed considerably over the past

twenty years. Real-time sports performance analysis

is a crucial aspect of matches in major sports around

the world (Legg et al., 2012). Professional sports have

seen massive improvements in the way player

performance, individual play tactics, and overall

game strategies are evaluated. This progress known

as the “sabermetric revolution” has resulted in a

trickle-down effect into amateur leagues (Baumer and

Zimbalist, 2014). The progress of professional

organizations and the availability of coinciding

statistical software has led to an increase in the use of

advanced statistical tracking and analysis in many

sports at the amateur level as well. However, while

the physiological and biomechanical aspects of water

polo have been studied extensively, advanced

performance tracking and statistical analysis have

received less attention.

Many software programs available to collegiate

and amateur water polo teams produce only basic

player and team statistics. These statistics include

goals scored, shots attempted, steals, blocks, and

fouls along with the tracking of game events as they

occur. The limited progress and availability of new

statistics have created a need in the collegiate and

amateur water polo community for a system that is

able to record and provide advanced analytics based

on the latest statistical research and the

recommendations of top collegiate coaches.

PoloTrac is a mobile, iOS application designed to

allow coaches, players, and spectators to record play-

by-play water polo game events as they happen in the

pool. PoloTrac has the features that one might expect

from a score-keeping app such as a functioning

scoreboard and clock that can keep track of team fouls

and timeouts remaining. However, PoloTrac also

produces post-game reports that are designed to be

useful in determining player performance, team

performance and the effectiveness of certain tactics.

PoloTrac makes use of the touch interface of iOS

devices (iPhones and iPads) to allow users, with a

simple tap of the finger, to input specific locations in

the pool from which players shoot as well as locations

on the net at which they aim. Compiling and charting

this data may provide useful insights to water polo

players and coaches as to what positions and tactics

are producing success in competitions. By utilizing

the latest research and statistical models, PoloTrac is

Verlin, N., Gullikson, J., Mayberry, J. and Cliburn, D.

PoloTrac: A Water Polo Tracking and Advanced Statistics Application.

DOI: 10.5220/0008344601730180

In Proceedings of the 7th International Conference on Sport Sciences Research and Technology Support (icSPORTS 2019), pages 173-180

ISBN: 978-989-758-383-4

173

also the first application of its kind to bring advanced

data analytics to the average water polo player, coach,

and spectator.

2 RELATED WORKS

There is a growing body of literature describing the

use of computing and advanced algorithms to analyze

data related to athletics and sports competitions

(Wang and Hsieh, 2016; Gruic and Gruic, 2018;

Beernaerts et al., 2018). Our application, PoloTrac, is

a mobile application that allows users to record and

analyze data from water polo matches using advanced

data analytics techniques. In section 2.1 we present

several uses of mobile applications in sports. In

section 2.2 we discuss recent advancements in the

collection and analysis of water polo statistics.

2.1 Mobile Applications in Sports

The use of mobile applications to record statistics and

to deliver content related to athletic events is

becoming increasingly common (Ault et al., 2008;

Savva et al., 2015; Berentowicz et al., 2017). Suomela

and Soinio (2005) were among the first to discuss the

use of smart phones to keep the score and time of

outdoor sporting competitions. Specifically, they

describe a novel system, StatKeeper, used in the 2004

World Ultimate Frisbee Championship. Like

PoloTrac, StatKeeper was designed to be simple and

user-friendly. Since it had to be usable by untrained

volunteers on a regular basis, the application had to

have a clear and intuitive flow of events to maximize

scorekeeping efficiency.

Park et al., (2014) propose an integrated

management system designed as a mobile application

to monitor participation in various sports activities.

The system was developed as a mobile application

and aims to systematically manage user activity level.

Similar to PoloTrac, this application uses two main

user interfaces, one for the tracking and logging of

data and the other for the presentation of statistics and

charts designed to provide the user with useful

information.

Can and Donmez (2015) describe an Android

application designed to utilize sensors that measure

GPS location, speed, and acceleration. These

measurements are tracked by the application and are

presented to users before, during, and after cardio

exercise sessions. The main user interface of the

application relies on a GPS enabled map that presents

the user’s location along with activity statistics. The

statistics are interactive and users are able to explore

data in a variety of fashions.

Hlupic et al., (2015) discuss a system to record

and process actions that occur at handball

competitions and provide statistical analysis during

and after each match. Like PoloTrac, this system can

provide coaches with data about player and team

efficiency during competitions. A mobile application

was developed to allow users to record player actions

(such as a shot to the goal) as a handball match

progresses. A separate web application is used to

generate reports.

2.2 Water Polo Statistics

Enomoto et al. (2003) were among the first to report

findings from an analysis of water polo statistics that

sought to identify characteristics of high performing

teams. Their findings suggest that, among other

things, highly ranked teams take more shots and make

fewer offensive mistakes than lower ranked teams.

Other authors followed with similar discriminatory

analyses of water polo contests based on common

box-score statistics (Argudo et al., 2009; Lupo et al.,

2010, 2011; Escalante et al., 2011, 2013).

More relevant to this paper is the work of Harris

and Graham (n.d.) who examined factors that affect

individual shot probabilities. This work explored the

“hot hand” effect, suggesting that as a player makes

more shots, the odds of a goal increase. This paper

also found several significant elements in predicting

the success of a shot, such as if the shot was a penalty

shot, where the shot was taken, and the sequence of

passes leading up to the shot. The shot-based

approach described by Harris and Graham is a

simplified approach of the shot-tracking methods

employed by PoloTrac.

Also paramount to the development of PoloTrac

is the work of Graham and Mayberry (2014) who

present a notational analysis of offensive tactics

commonly employed in elite men’s water polo

competitions. Following earlier analyses of

basketball game data (eg. Kubatko et al., 2007), this

work took a possession-based approach to studying

water polo and introduced the idea of measuring

tactical efficiency as the expected proportion of

tactical uses which lead to a goal being scored. This

work also provided a list of tactical definitions and

additional performance metrics adapted for use by

PoloTrac. Graham and Mayberry (2016) additionally

applied a possession-based approach to address the

question of referee bias in water polo. The authors

used a logistic model to predict foul calling

probabilities based on various game-state statistics.

icSPORTS 2019 - 7th International Conference on Sport Sciences Research and Technology Support

174

PoloTrac utilizes a similar logistic-based approach to

estimate shot probabilities based on shot location,

shot type, shooter hand, and defender position.

3 POLOTRAC OVERVIEW

The idea behind PoloTrac was to use the extended

tablet model of the Apple iPad to create a touch screen

interface that allows for rapid input and recording of

plays in real time as they take place during a water

polo match. The application can then generate

statistics and charts as well as export spreadsheet

enabled reports to leverage the model of tactical

efficiency described by Mayberry and Graham

(2014). PoloTrac is designed to be a standalone

application capable of tracking events during a water

polo match. While other score-keeping applications

also attempt to simplify the recording of in-game

events, PoloTrac uses an intuitive and sequence-

based event flow that allows for the recording and

advanced analysis of various tactics, outcomes, and

locations within the pool.

Figure 1: The Main Menu of PoloTrac.

3.1 Main Menu

The PoloTrac main menu has three core functions

(New Game, Load Game, and Advanced Statistics)

accompanied by three subfunctions (Whiteboard,

Notebook, and Video Library) as seen in Figure 1.

The core functions serve as a method for opening new

games, loading previous games, and viewing and

exporting outputs based on the events recorded during

games. The subfunctions are independent coaching

tools that have been recommended to increase the

usefulness of PoloTrac in a game or practice setting.

These features are separate from the tracking and

analysis that represent the core functionality of

PoloTrac and serve as simple tools for completing

actions such as drawing up plays to instruct player

positioning, saving notes about specific players and

strategies, and uploading video to be organized and

viewed for instruction or strategical scouting.

3.1.1 Team Management

In order to track players and their corresponding

statistics appropriately, values for name and cap

number must be attached and saved. PoloTrac

accomplishes this through a feature called team

building. Team building allows for the creation,

editing, and saving of teams made up of unique,

individual players. These teams are saved within the

application, therefore, once a user inputs the players

and numbers of a specific team this information

persists in the application until manually deleted. In

the New Game creation screen, users have the option

to select two teams from their current list of saved

teams or to create a new team. This functionality was

designed specifically with water polo leagues in mind

as teams who are in the same league frequently play

one another more than once.

Teams also serve as an attribute to a specific

player. This allows for the sorting of players by teams

which is particularly useful in many use cases

involving statistical output. For example, a coach may

want to see a compilation of a specific team’s

statistics. They may also want to see what players

have the highest statistics from a specific team for

scouting and preparation purposes. Or they may want

to see which players have recorded the best statistics

overall to provide some insight as to which team’s

players are producing the best statistics. From a

coaching perspective, this information is critical in

creating a competitive advantage through scouting.

Therefore, PoloTrac’s ability to input, store and track

players from different teams is one of the critical

underlying features of the application from a

coaching and evaluation perspective.

3.2 Secondary Functions

In addition to its primary features, PoloTrac includes

three secondary functions designed specifically with

the coach and spectator in mind. These features

include a virtual whiteboard in which coaches can

draw plays and strategies and erase them with the tap

of a button, a notebook designed to keep typed notes,

and a video library designed for the user to upload and

organize videos.

PoloTrac: A Water Polo Tracking and Advanced Statistics Application

175

3.2.1 Whiteboard

The whiteboard feature was designed and

implemented as a way to “draw up” specific plays,

tactics, and positioning over the image of a pool (see

Figure 2). This gives both the players and coaches a

better perspective of certain locations in the pool

relative to the goal. Traditionally, coaches use dry

erase boards to communicate this information. By

using a tablet interface such as the iPad with

programmable software, functionality can be

implemented that extends far beyond the reach of a

traditional dry erase board.

Figure 2: Example of a play drawn on the virtual

whiteboard.

Users are able to draw on the whiteboard in a

variety of colors, place markers for both offenders

and defenders, and erase the entire board at the press

of a button. While these features are relatively simple,

in the context of a game the ability to accurately draw

and erase legible diagrams over the course of a thirty-

second to one-minute timeout is critical. A match

outcome could be determined by the ability or

inability of a coach to effectively communicate with

players to execute an important play or possession.

3.2.2 Notebook and Video Library

The early stages of PoloTrac’s development included

observations of the coaching process during water

polo games. Through attending matches and viewing

past televised matches, it was observed that coaches

frequently jot down notes containing information to

refer back to during timeouts and at the conclusion of

games. Due to the rapid pace of play in water polo,

these game-time notes were often on various pieces

of scratch paper and written in formats that were

illegible. Therefore, the need to have a section

dedicated to simple notes arose. PoloTrac’s Notebook

feature is designed to provide a centralized location

for notes. Notes can be attached to specific teams for

organizational purposes. For example, a coach might

collect notes on his team in order to recall key points

of improvement during practice and training sessions,

while also collecting notes on opposing teams based

on the style and tactics of their play. This allows for a

much clearer and organized method of note taking

that can be stored and referenced when needed.

A similar ideology lies behind the video library.

Often times during water polo tournaments, multiple

matches will take place in one day giving coaches and

players the ability to watch their upcoming

competition before playing them. In order to better

understand and outline what an opponent's strengths

and weaknesses are, video of previous matches is

studied. The video library in PoloTrac serves as a

centralized location for images and videos of

matches, plays, or practices. Similar to the notebook,

videos can be linked with specific teams for

organizational purposes. A personal collection of

videos and tactics can be accumulated over time and

used as a coaching tool to demonstrate strategies to

increase the competence of one’s own team while

studying the tactics of a competitor.

Figure 3: PoloTrac’s primary tracking screen. The

draggable ball user interface is also depicted in the center

of the screen.

3.3 Primary Tracking Screen

The primary tracking screen (shown in Figure 3) is

the key component of PoloTrac. This screen is

designed for entering and recording inputs of various

aspects of water polo matches. The primary tracking

screen has two main purposes. The first is to keep

score for the game as a traditional scoreboard would.

This includes information that is common in sports

competitions, but also critical to the success of the

icSPORTS 2019 - 7th International Conference on Sport Sciences Research and Technology Support

176

application’s tracking and analysis features. The

second purpose is to provide an intuitive and fast-

paced system to track shot information during a

match and record it accurately. This is accomplished

by leveraging the landscape orientation of the iPad in

order to create a “two-thumbed” interface that can be

used in a similar manner as a game-pad controller.

Figure 4: The shot chart displayed in the center of the screen

used to track the location of an attempted shot.

3.3.1 Scoreboard and Clock

The scoreboard and clock features seen at the bottom

of Figures 3 and 4 serve as the basic information

display that mirrors the standard water polo

scoreboard. This includes data such as home and

away score, the current quarter of play, the current

time remaining in that quarter, the total exclusions for

each team and the total number of timeouts remaining

for each team. The score itself is dynamic and will

update if a shot with the outcome of “goal” is tracked

for a certain player. The team in which that player is

on is awarded a point and their score is automatically

incremented. The clock feature is controlled by the

start and stop buttons directly next to the scoreboard.

The clock appears green when it is running and red

when it is stopped. This feature is designed to

highlight the clock in the user’s mind to ensure it is

not running when it should be stopped or stopped

when it should be running. The clock, quarter, and

timeout values can all be manually configured in the

case of a discrepancy between the match and what is

reflected on the PoloTrac scoreboard. In some

scenarios, it is not uncommon to see the clock be reset

to a certain value by the officials of the game in order

to ensure accuracy and fairness. Since the clock plays

a role in the recording and tracking of shots and shot

data, its accuracy is of utmost importance.

3.3.2 Draggable Ball and Player Location

PoloTrac utilizes a unique user interface to keep track

of shooting locations in the pool. The touch and pan

gesture-recognizing capabilities of the iPad allows for

the user to “tap” or “drag” the water polo ball to the

approximate place in the pool from where the player

attempted the shot (as shown in the middle of Figure

3). The pool image embedded as the background on

the PoloTrac screen (shown as the background image

of Figures 1 to 4) has squares that represent 2 meters

by 2 meters. While these squares may not be on every

pool the user encounters, knowing their length will

aid the user in approximating the player’s location in

the pool at the time of a shot. Based on this action,

coordinates are created and attached to the specific

shot and later used for building charts that can show

the location of a player or team’s shot attempts.

3.3.3 Shot Chart

In addition to tracking shot locations in the pool,

PoloTrac also captures the location on the goal in

which the ball was shot. Figure 4 shows the goal

image that the user is shown before the shot is

submitted. This image, like the main pool, contains a

water polo ball icon that can be tapped or dragged to

the location in the goal at which the player shot. The

coordinates of this approximate location are saved

along with the details of the shot and used for

statistical analysis and outputs.

3.3.4 Shot Tracking Flow

Water polo is a fast-paced game and one offensive

possession could contain multiple shot attempts. In

order to provide the most accurate results possible,

PoloTrac’s user interface is designed in a sequence-

specific order that allows for the user to input details

and location of a shot in a timely manner. The actions

of selecting events in sequence are carried out on the

two sides of the screen. The right side of the screen is

intended to be selected with the user’s right thumb

and indicates the content to appear on the left side of

the screen that is selectable by the user’s left thumb.

When users select the Player button on the

primary screen (shown in the upper right of Figures 3

and 4) the left side of the screen displays the list of

players on the current team so that users can quickly

select the player that took the shot (depicted on the

left side of Figures 3 and 4). Users can then indicate

the shot type and tactic that the player used to attack

the goal using the appropriate buttons on the right of

the screen, which generates a list of corresponding

options on the left side of the screen. Similarly, the

PoloTrac: A Water Polo Tracking and Advanced Statistics Application

177

Outcome button presents a table of outcomes (such as

“goal” and “miss”) that are possible throughout the

course of a game. Lastly, the “Chart” button should

be selected and the user can indicate the location of

the successful or unsuccessful shot (shown in the

center of Figure 4). Once all shot details are entered,

users record the shot using the Submit button (shown

in the bottom right of Figures 3 and 4) and the

outcome is used to update the scoreboard and

statistics automatically. For example if a player from

the home team scores a goal, the home score will

automatically increment by one.

3.4 Advanced Outputs

An advanced statistics screen was designed to provide

useful feedback to coaches and players through

statistics and charts. Users are able to organize these

statistics and charts by both individual, team, and

game. For example, users could see a shot chart for a

specific player from today’s game or they could see a

chart for all of that player’s games. The output of the

entire team can be viewed as well. This allows

coaches and players to easily access statistics for both

informational and instructional purposes. The

advanced output screen may also be used as a

scouting tool. By looking through previous matches

of an opponent and their players, trends in the shot

diagram could indicate specific strategies used by a

team thus giving the user a competitive advantage.

3.4.1 Basic Statistics

Like other water polo scorekeeping programs,

PoloTrac allows users to track statistics for each

player such as shots attempted, goals scored, assists,

total points, exclusions, and steals (as shown in

Figure 5). PoloTrac also provides these statistics for

both teams and players over the course of an

individual game or an entire season. This information

is accessible through the advanced statistics menu

option and allows users to filter through the data by

specifying a team, player, and game on the left side

of the screen.

3.4.2 Shot Diagram and Tactical Efficiency

In addition to the basic statistics presented by

PoloTrac, users are also able to view the locations in

the pool from which players and teams are taking

shots. As can be seen in the upper right of Figure 5,

the application displays an image of a pool with color

coded icons corresponding to the coordinates of each

recorded shot. Made shots appear with a green hue

and missed shots appear with a red hue. This view can

allow coaches to identify trends in shot locations

based on their own expertise to provide feedback to

their players. Each shot displayed in the chart is

selectable, meaning that it can be “tapped” to see

more information. This information contains all of the

recorded and calculated details of the shot following

the tactical definitions of Graham and Mayberry

(2014).

Figure 5: The Advanced Statistics screen.

PoloTrac calculates a predicted goal probability

for each shot (displayed as “Tactical Efficiency” and

shown under “Individual Shot Statistics” in Figure 5).

This value is obtained from a logistic model that uses

shot location, shot type, hand, defender position, and

offensive tactic as predictors and the binary variable

goal or no goal as the response. To obtain

coefficients, the model uses a sample of 5177 shots

from 86 collegiate water polo games during the 2016-

2018 seasons. The model was trained on a randomly

selected subsample of shots using a 60-40 split and

the remaining 40% of shots were used as a testing set

for model validation. The model achieved 70%

prediction accuracy on the testing set.

Incorporation of predicted goal probabilities

allows users to quantify the quality of their shot

selections, a feature that sets PoloTrac apart from

other scorekeeping applications. Players and coaches

can use this information both during games and in

post-game evaluation to identify weaknesses and

areas for improvement. For example, by looking at a

team’s average tactical efficiency throughout a game,

a team can distinguish between scenarios in which

they were taking poor shots and scenarios where they

were just shooting poorly. A team can evaluate their

defensive performance by comparing the actual

number of goals allowed with the expected number

based on predicted shot probabilities and number of

shots allowed. These advanced statistical features

icSPORTS 2019 - 7th International Conference on Sport Sciences Research and Technology Support

178

allow players and coaches to make better use of their

data and gain a competitive edge in the sport.

4 EVALUATION

To perform an initial evaluation of PoloTrac we

conducted usability testing (Rogers et al., 2011) with

five members of the local water polo community who

each had experience coaching or playing the sport.

The goal of our usability testing was to determine

ways that the interface of PoloTrac could be

improved to create a more usable and useful

application. Three of our participants used PoloTrac

to record statistics at live water polo games and two

participants recorded statistics of previously recorded

games that they watched on television. All

participants were asked to track the statistics of the

game they watched and told that they could use the

Advanced Statistics button on the home screen to see

reports for their inputs. Participants were observed

while they used the application, and then asked to

comment on the usability and usefulness of PoloTrac

at the conclusion of the game that they tracked.

Participants found the overall experience of using

PoloTrac to be “positive” and “successful.”

Participants also used words such as “easy” and

“intuitive” to describe the interface. They were

generally pleased with the “two-thumbed” layout of

the application. In addition, they found dragging or

tapping the ball to a specific location in the pool to be

convenient. Participants also felt that buttons such as

Submit, Start, and Stop were “in the correct place”.

However, participants found inputting shot

information to be somewhat challenging at times. In

PoloTrac, users are able to select menu buttons (such

as Player, Shot Type, and Tactic) in any order they

choose. However, during our evaluation users

occasionally forgot what information had already

been entered as they recorded some of the shots. This

led to incorrect data entries, which decreased the

accuracy of the statistical output. Participants also

commented on the order of many of the selection tabs.

For example, a “skip shot” is used often in water polo.

However, users had to scroll to the bottom of the shot

type list to select skip shot, which slowed them down.

Participants were generally pleased with the

functionality provided by the Advanced Statistics

screen to filter information based on criteria such as

team, player, and game. Participants commented that

that the layout and appearance of this screen looked

“professional” and “sleek.” However, participants

requested that a cumulative statistics screen also be

provided to display statistics for all the players on

both the home and away teams for a specific game.

Participants suggested it would be useful to see the

comparison between two teams for a specific game

for information and strategic purposes.

5 CONCLUSION

In this paper we describe PoloTrac, an application

that allows users to record statistics of live water polo

competitions, and that utilizes advanced statistical

models to provide reports and analysis not found in

other similar applications. Our initial usability testing

suggests that while users found many aspects of the

application to be intuitive, they sometimes struggled

to accurately record shot data in real time as games

progressed. PoloTrac has already been modified to

place the most recently selected shot types at the top

of the shot type list to improve the speed of the shot

entry process. To improve the accuracy of shot entry,

we plan to modify PoloTrac to require that users input

information on each option (such as Shot Type and

Outcome) before the Submit button is enabled to

record a shot. This should help remind users of all the

information required before a shot can be correctly

recorded. In response to user feedback, we also plan

to implement an additional statistics screen that

allows users to compare game statistics for two teams.

In the future, to further improve the application,

we would like to collect feedback from coaches who

use PoloTrac’s other features before, during, and after

matches. Future work could also include modifying

PoloTrac to allow users to record additional match

information. The tactical efficiency statistic

calculated by PoloTrac takes into account features

such as a player’s shot location, type of shot taken,

and specific tactic used (such as perimeter attack or

direct attack). However, PoloTrac does not currently

record other player responsibilities in the pool and

how those responsibilities are carried out. Tracking

information such as the length of passes between

players, whether or not plays are executed correctly,

and goalkeeper efficiency is not currently supported.

Our hope is that PoloTrac can provide users with

a powerful tool for real time tracking and analysis of

water polo games. PoloTrac's ability to isolate teams

allows coaches to perform in-depth analyses of

opponents' shot taking tendencies and evaluate their

own team's performance. The ability to isolate

individuals can also be used for player development

and training. We believe PoloTrac can provide the

water polo community with advanced knowledge of

their sport, revealing new insights about how shots

are made and ultimately, how games are won.

PoloTrac: A Water Polo Tracking and Advanced Statistics Application

179

ACKNOWLEDGEMENTS

The authors would like to thank James Graham, the

participants in our usability testing, and the School of

Engineering and Computer Science at University of

the Pacific for supporting this work.

REFERENCES

Argudo, F. M., Ruiz, E., & Alonso, J. I. (2009). Were

differences in tactical efficacy between the winners and

losers teams and the final classification in the 2003

Water Polo World Championship? Journal of Human

Sport and Exercise, 4(II), 142-153.

Ault, A., Krogmeier, J. V., Dunlop, S. R., & Coyle, E. J.

(2008). eStadium: The mobile wireless football

experience. Proceedings of the Third International

Conference on Internet and Web Applications and

Services, 644-649.

Baumer, B. & Zimbalist, A. (2014). The Sabermetric

Revolution: assessing the growth of analytics in

baseball. Philadelphia: University of Pennsylvania

Press.

Beernaerts, J., De Baets, B., Lenoir, M., De Mey, K., & Van

de Weghe, N. (2018). Analysing team formations in

football with the static qualitative trajectory calculus.

Proceedings of the 6th International Congress on Sport

Sciences Research and Technology Support, 15-22.

Berentowicz, M., Zajac, P., & Zabierowski, W. (2017). The

use of mobile technology on the example of health and

sports statistics application. Proceedings of the XIIIth

International Conference on Perspective Technologies

and Methods in MEMS Design, 187-189.

Can, Y. S. & Donmez, M. Y. (2015). Sport Sense: A mobile

sensor data collection, labeling and display application

for sport centers. Proceedings of the 23rd Signal

Processing and Communications Applications

Conference, 624-627.

Enomoto, I., Suga, M., Takahashi, M., Komori, Y.,

Minami, T., Fujimoto, H., Saito, M., Suzuki, S., &

Takahashi, J. (2003). A notational match analysis of the

2001 Women’s Water Polo World Championships.

Proceedings of Biomechanics and Medicine in

Swimming IX, 487-492.

Escalante, Y., Saavedra, J. M., Mansilla, M., & Tella, V.

(2011). Discriminatory power of water polo game-

related statistics at the 2008 Olympic Games. Journal

of Sports Sciences, 29(3), 291-298.

Escalante, Y., Saavedra, J. M., Tella, V., Mansilla, M.,

García-Hermoso, A., & Domínguez, A. M. (2013).

Differences and discriminatory power of water polo

game-related statistics in men in international

championships and their relationship with the phase of

the competition. The Journal of Strength &

Conditioning Research, 27(4), 893-901.

Graham, J. & Mayberry, J. (2014). Measures of tactical

efficiency in water polo. Journal of Quantitative

Analysis in Sports, 10(1), 67-79.

Graham, J. & Mayberry, J. (2016). The ebb and flow of

official calls in water polo. Journal of Sports

Analytics, 2(2), 61-71.

Gruic, A. S. & Gruic, I. (2018). Application of linear

programming on example of relationship between two

types of activity and optimized dietary supplement

intake. Proceedings of the 6th International Congress

on Sport Sciences Research and Technology Support,

197-202.

Harris, J. S. & Graham, J. (n.d.). Hot hands in cold water:

An investigation of the "myth" using NCAA division I

water polo. Retrieved April 23, 2019, from:

https://www.jillsharrisphd.com/upload/Hot Hands in

Cold Water.doc.

Hlupic, T., Jandrijevic, F., Kovacev, J., Petricioli, L.,

Gracin, T., & Baranovic, M. (2015). System for

monitoring and advanced analysis of handball matches.

Proceedings of the 38

International Convention on

Information and Communication Technology,

Electronics and Microelectronics, 1428-1433.

Kubatko, J., Oliver, D., Pelton, K., & Rosenbaum, D. T.

(2007). A starting point for analyzing basketball

statistics. Journal of Quantitative Analysis in

Sports, 3(3).

Legg, P. A., Chung, D. H. S., Parry, M. L., Jones, M. W.,

Long, R., Griffiths, I. W., & Chen, M. (2012).

MatchPad: Interactive glyph‐based visualization for

real‐time sports performance analysis. Computer

Graphics Forum, 31(3pt4), 1255-1264.

Lupo, C., Tessitore, A., Minganti, C., & Capranica, L.

(2010). Notational analysis of elite and sub-elite water

polo matches. The Journal of Strength & Conditioning

Research, 24(1), 223-229.

Lupo, C., Tessitore, A., Minganti, C., King, B., Cortis, C.,

& Capranica, L. (2011). Notational analysis of

American womenʼs collegiate water polo

matches. Journal of Strength and Conditioning

Research, 25(3), 753-757.

Park, S. J., Lim, M., Kim, M., Han, Y., & Choi, J. (2014).

Mobile personal sports activity management app.

Proceedings of the 18

IEEE International Symposium

on Consumer Electronics, 1-2.

Rogers, Y., Sharp, H., & Preece, J. (2011). Interaction

Design: beyond human-computer interaction (3rd ed.).

West Sussex, United Kingdom: Wiley.

Savva, A., Domenach, F., Stylianou, V., & Hadjidakis, S.

(2015). An F1 mobile application, Proceedings of the

2015 International Conference on Interactive Mobile

Communication Technologies and Learning, 172-175.

Suomela, H. & Soinio, A. (2005). Scorekeeping with smart

phones mobile solution for outdoor team sports

tournaments. Proceedings of HCI International 2005.

Wang, S. & Hsieh, W. (2016). Performance analysis of

basketball referees by machine learning techniques.

Proceedings of the 4th International Congress on Sport

Sciences Research and Technology Support, 165-170.

icSPORTS 2019 - 7th International Conference on Sport Sciences Research and Technology Support

180