Table 3: Wickets in Matches Table 4: Runs in Matches
T1
|
|
NO. OF MATCHS
|
NO. OF WICKETS
|
1
|
10
|
2
|
9
|
3
|
8
|
4
|
8
|
5
|
7
|
6
|
2
|
7
|
3
|
8
|
1
|
Total__48'>Total
|
48
|
T2
|
|
NO. OF MATCHS
|
NO. OF RUNS
|
1
|
138
|
2
|
99
|
3
|
86
|
4
|
84
|
5
|
52
|
6
|
40
|
7
|
23
|
Total
|
522
|
Using the above tables we can find out T1, T2 as follows
=
And
=
So
=
-
TEAM RANK
Team rank is an adoption of page rank algorithm [2]. Page Rank of a team should be high if the team wins many matches from other teams and those teams are good (those teams also had won many matches).
. The algorithm may be applied to any collection of entities with reciprocal quotations and references.
TR(A) = +d (4)
Here inlinks refer to the matches won and outlinks refer to the matches loss from another team. Finally, the sum of the weighted Team Ranks of all teams Ti is multiplied with a damping factor d which can be set between 0 and 1.
Table 5: Team Rank of all Teams
TEAM
|
INDIA
|
PAK
|
SRI
LANKA
|
SOUTH AFRICA
|
NEW ZEALAND
|
ENG
|
WEST INDIES
|
BANG
|
ZIMB
|
AUS
|
TOTAL
|
INDIA
|
0
|
22
|
26
|
20
|
13
|
14
|
17
|
2
|
5
|
32
|
151
|
PAKISTAN
|
20
|
0
|
22
|
23
|
17
|
14
|
10
|
0
|
0
|
16
|
122
|
SRILANKA
|
34
|
26
|
0
|
16
|
11
|
12
|
4
|
2
|
2
|
22
|
129
|
SOUTH AFRICA
|
15
|
11
|
18
|
0
|
11
|
13
|
5
|
1
|
1
|
22
|
97
|
Figure 2:
-
WEIGHTED TEAM RANK ALGORITHM
Assigns larger rank values to more important (popular) teams instead of dividing the rank value of a team evenly among it’s outlink matches [1]. Each outlink match gets a value proportional to its highest score in that match.
(5)
-
TR(A) is the TeamRank of Team A ,
-
TR(Ti) is the TeamRank of Teams Ti which link to Team A,
-
WC(Ti) is the number of outbound(matcheswin) links on team Ti ,
-
d is a damping factor which can be set between 0 and 1.
In order to calculate WC (Ti) (weighted outlinks) we use weighted arithmetic mean formula
(6)
And we will also calculate weighted outlinks by using these values to check values
(7)
(8)
EXAMPLE 2:
Calculating weighted team rank of team West Indies using weighted outlink formula
WEST INDIES
|
PAKISTAN =>60(20)+20(67)+20(274)/20+67+274=>8080/361=>22.38
|
SRI LANKA =>60(10)+20(29)+20(386)/10+29+386=>8900/425=>20.94
|
SOUTH AFRICA =>60(26)+20(99)+20(714)/26+99+714=>178200/839=>21.23
|
INDIA =>60(25)+20(71)+20(641)/25+71+641=>15740/737=>21.36
|
ENGLAND =>60(14)+20(33)+20(182)/14+33+182=>5140 /229=>22.44
|
Table 6: Weighted team rank (outlink)
TEAM
|
INDIA
|
PAKISTAN
|
SRILANKA
|
SOUTH AFRICA
|
NEW ZEALAND
|
ENGLAND
|
WEST INDIES
|
BANGLADESH
|
ZIMBABWE
|
AUSTRALIA
|
TOTAL
|
INDIA
|
0
|
21.02
|
20.85
|
21.01
|
21.05
|
21.58
|
21.74
|
23.64
|
27.69
|
20.83
|
199.41
|
PAKISTAN
|
21.43
|
0
|
20.96
|
21.01
|
21.34
|
21.40
|
20.93
|
0
|
0
|
21.00
|
148.07
|
SRILANKA
|
21.30
|
21.09
|
0
|
20.82
|
22.13
|
21.04
|
21.72
|
27.27
|
25.71
|
20.87
|
201.95
|
SOUTH AFRICA
|
21.18
|
20.83
|
21.28
|
0
|
22.26
|
21.92
|
26.25
|
20.59
|
33.34
|
20.98
|
208.63
|
-
UNIFIED WEIGHTED TEAM RANK
It is calculated by combining the results of T-index and the weighted team rank [2].
This section contains two parts. The first part studies T-index with different damping factors and the second part deals with different weighted Page Rank algorithms.
Following is the formula.
(9)
-
d is a damping factor which can be set between 0 and 1.
CHAPTER 4
IMPLIMENTATION
4. Implementation
This chapter introduces how we have implemented our algorithms and their results in coding. For this purpose we have used some development tools and technologies. Reasons for selecting these tools are also discussed.
4.1 Tools & Technologies
We used the following tools and technologies:
-
Microsoft Visual C++ 6.0
-
Ms word
-
Ms excel
-
Notepad
4.1.1 Visual C++
Visual C# is a high level programming language .Visual C# is relatively easy to learn and use. Learning Visual C# is quite easier than other programming languages such as C++, visual basic etc. This is because Visual C# enables you to work in a graphical user interface. I chose this language, because this very easy to use and learn and is also fast processing.
4.1.2 Microsoft Word and Excel
It is an application software for calculations analyzing information and manage the lists in spread sheet or comma separated files. The commonly use of Excel is to manage data records and name lists. You don't have to plan in advance on how the table should look like, as the preset layout allows you to create the tables on the fly, just fill in the information, the table is developed on the go. Another more attractive point is that you have the ability to sort the list and filter the listing like a database tool.
4.1.3 Notepad
We use notepad files to store and retrieve results to make processing fast.
4.2 Project Codes
4.2.1 Team Rank Code With Respect To Odis
void cal_pr()
{
float * pr;
pr= new float[3];
pr[0]=1;
pr[1]=1;
pr[2]=1;
pr[3]=1;
pr[4]=1;
pr[5]=1;
pr[6]=1;
pr[7]=1;
pr[8]=1;
pr[9]=1;
float * tt;
tt= new float[10];
tt[0]=0;
tt[1]=0;
tt[2]=0;
tt[3]=0;
tt[4]=0;
tt[5]=0;
tt[6]=0;
tt[7]=0;
tt[8]=0;
tt[9]=0;
for(int k=1;k<=30;k++)
{
for(int i=0;i
{
tt[i]=0;
for(int j=0;j{
if(net[j][i] > 0)
{
int count=0;
for(int k=0;k
{
if(net[j][k] > 0)
count+=net[j][k];
}
float aa =pr[j]/count;
aa*=net[j][i];
tt[i]+=aa;
}
}
float temp=0.0;
float temp1=0.0;
temp1=alpha*tt[i];
temp=(1-alpha)/size;
pr[i]=temp+temp1;
}
//cout<<"\t"<
}
cout<<"****************TEAM RANKING WITH RESPECT TO ODIS***************";
cout<
for(int t=0;t<10;t++)
{
cout<
}
float high=pr[0];
int no=0;
for(int i=1;i
{
if(high
{
high=pr[i];
no=i;
}
}
cout<
}
void main()
{
int data,i=0,j=0;
string file_name = "file.txt";
ifstream fin(file_name.c_str());
if(!fin)
{
cout<<" File not found "<
//return 0;
}
while(fin>>data)
{
net[i][j++] = data;
}
cout<<" ";
for(int t=0;t<10;t++)
{
cout<
}
cout<
for(int k=0;k
{
cout<
for(int l=0;l
{
cout<
}
cout<
}
cout<
cal_pr();
}
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