2020美赛D题哈士奇团队分析论文

2020美赛D题

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Team#2003758 Page 1 of 19

Problem Chosen

2020

MCM/ICM

Summary Sheet

Team Control Number

2003758

Individual Multidimensional Contribution Dynamic

Evaluation Model Based on Interaction Networks

Summary

In this article, we have established an Individual Multidimensional Contribution

Dynamic Evaluation Model（IMCODEM） based on Interactive Network, which can

be used to evaluate the dynamic performance of members of a team comprehensively,

dynamically and multi-dimensionally. A background introduction is given in the first

chapter.

In Chapter 2, we pre-processed the Huskies’ performance data last season and

normalized the representation of the data. Then we conducted a brief analysis of the

Huskies’ data and roughly understood the characteristics of this team. Finally, the main

players of the team were identified and analyzed as the focus in the following.

In Chapter 3, first we set up a passing interactive network for the main players of

the Huskies. The node position of this network is determined by the player's passing

position, and the width of the network line is determined by the player's passing

frequency. Then, we refined the network and selected important dyadic and triadic

combinations for analysis. Considering that the network's influencing factors are not

just passing, we have introduced Weighting Factor Vector (WFV) to optimize the

model. Considering the influence of various factors, the network has been optimally

configured.

In Chapter 4, we established Individual Multidimensional Contribution Dynamic

Evaluation Model（IMCODEM）. Taking into account multiple performance indicators,

we made a dynamic analysis of the player's performance within 90 minutes of a game.

Using this model, the relationship between the each player's contribution to the team

and the whole team's performance can be well explained. Then we summarized the

team's performance throughout the season and gave some advice in Chapter 5.

In Chapter 6, we re-standardize and summarize the Individual Multidimensional

Contribution Dynamic Evaluation Model (IMCODEM), and promote it so that it can

be used by every team in society to assess members’ performance. Finally, we put

forward improvement suggestions and prospects for the shortcomings of the model.

Keywords: team; interactive network; multi-dimensional; dynamic evaluation model;

individual performance

Team#2003758 Page 2 of 19

Contents

Summary ......................................................................................................................................... 1

Contents ........................................................................................................................................... 2

1 Introduction .................................................................................................................................. 3

2 Data Definition and Data Analysis ............................................................................................. 4

2.1 Data Definition and Standardization .................................................................................. 4

2.2 Data analysis overall ............................................................................................................. 5

3 Interaction Networks Model ....................................................................................................... 8

3.1 Passing Networks .................................................................................................................. 8

3.1.1 Team Overall Passing Network ..................................................................................... 8

3.1.2 Dyadic Passing Network ................................................................................................ 9

3.1.3 Triadic Passing Network .............................................................................................. 10

3.2 Multidimensional Interaction Networks ........................................................................... 12

3.2.1 Weighting Factor Vector(WFV) .................................................................................. 12

3.2.2 Multidimensional Interaction Networks .................................................................... 12

4 Individual Multidimensional Contribution Dynamic Evaluation Model .............................. 13

4.1 Introduction of IMCDEM .................................................................................................. 13

4.2 Analysis Results of IMCDEM ............................................................................................ 14

5 Conclusions and Advice ............................................................................................................. 17

6 Extension and Prospect of the Model ....................................................................................... 17

6.1 Generalized Models of Team Performance ....................................................................... 17

6.2 Further Work ...................................................................................................................... 18

References ...................................................................................................................................... 19

Team#2003758 Page 3 of 19

1 Introduction

With the progress and development of society, the importance of team has been

widely accepted. Individuals can not only rely on the team to exert their independent

value, but also can further magnify their contribution to the team through interaction

and cooperation with suitable team members. Over the past half-century, our

understanding of the concept of team success has improved significantly. The best

strategy for team building, the best interaction between teammates, and the ideal

leadership style have become the focus of research. A strong team can perform

complex tasks outstandingly. However, these tasks are not completed by simply

accumulating the contributions of team members. It is necessary to fully find the best

interaction and cooperation of some people in the team to maximize the effectiveness

of the team value. Therefore, when we study the effectiveness of teamwork, the

interaction network between team members cannot be ignored.

Football is a sport that values teamwork and interaction, and it is also a classic

object of our research on team effectiveness and team member interaction networks.

Because soccer scores tend to be low, simple statistics such as number of assists,

number of shots or number of goals only rarely provide a reliable measure of a

player ’s true impact on the match ’s outcome. Reference [1] used Guardiola's

Barcelona as a research object, analyzed the team members' passing network, and

studied the relationship between the passing network and the team's effectiveness.

However, they did not study other than the passing network. The impact of the network

formed by court events on the effectiveness of the game. Reference [2] considers that

the real measure of the performance of a player is ‘‘ hidden ’’ in the plays of a team.

From this we can see that the interactive network that affects the effectiveness of a

team is multifactorial, and the effectiveness of the team is the result of the combined

action of multiple interactive networks.

This article takes the Huskies football team as the research object, analyzes the

team's game data last season, and establishes various interactive networks such as the

passing network. Based on this, an Individual Multidimensional Contribution Dynamic

Evaluation Model (IMCDEM) is proposed. Used to reflect the individual, dyadic,

triadic or even team ’s multifaceted comprehensive performance in the research team

in real time. This model involves all aspects of individual or team performance, which

can provide timely and comprehensive guidance advice for individuals and even the

entire team. In addition, the model is also applicable to the performance analysis of

other social groups.

Team#2003758 Page 4 of 19

2 Data Definition and Data Analysis

2.1 Data Definition and Standardization

Team performance data refers to the statistics of a team's performance over a

period of time. The types of performance referenced in different fields are different. In

the field of football, team performance data relates to all events that occur on the field,

such as passing, dueling, fouling, etc. They are almost related to the team's

performance, and are also important indicators for evaluating the performance of a

player and the entire team. We screened and found stadium events that could be

quantified, and presented them in Table 2. First of all, we will normalize these

multidimensional representation data，and provide a standard data for subsequent

modeling. Regarding the player in the special position of goalkeeper, only one

goalkeeper has played throughout the season. We cannot compare his performance and

can only discuss it separately.

Table 1．Stadium events that can be quantified

Types

Subtypes

Pass

Head pass，Hand pass，Simple pass，Smart pass，Launch，

Cross，High pass

Duel

Air duel，Ground defending duel，Ground loose ball duel，

Ground attacking duel

Shot

Shot，Penalty，Free kick

Free Kick

Throw in，Free Kick，Corner，Free kick cross，Free kick shot

Foul

Foul，Late card foul，Simulation，Protest，Hand foul，

Violent Foul，Out of game foul，Time lost foul，Offside

Others on the ball

Touch，Clearance，Acceleration

Goalkeeper*

Save attempt，Reflexes，Goal kick，Goalkeeper leaving line

So we can represent Huskies as the following set:

{ 1, 2 , 6, 1, 2 , 13, 1, 2 , 10, }HU F F F M M M D D D G=   

(1)

In the formula,

indicates the set of Huskies’ players,

indicates the

forward player and all events related to him,

indicates the midfielder and all

events related to him,

indicates the defender and all events related to him,

indicates the goalkeeper and all events related to him. These events consist of 38

games. In order to analyze the performance of a player in a game, the event set of a

player can be expressed as follows, taking player

as an example:

1 2 38

1 { 1 , 1 , 1 , , 1 }

F F F F F=  

(2)

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