Description of the
data
The Premier League data contains information on the following: With
in my report I will concentrate on Liverpool. I will display a histogram
of home shots and the actual amount of goals scored. We will do a table
displaying percentage of goals from Away shots for Liverpool and a
boxplot of Home goals scored.
- Date: Match Day Time & Date
- Teams: Details of Home & Away TEams
- Goals: Goals Scored Home and Away!
- Full Time Results : (1=Home Win , 2=Draw, 3=Away
Win)
- Shots: Shots taken Home and Away
- Shots on Taregt: Shots actually on Target both Home
& Away
- Fouls Committed: Fouls Committed both Home and
Away
- Yellow Card: number of yellow cards recieved by the
Team
- Red Cards: number of red cards recieved by the
Team
Exploratory analysis of
Home goals
Home Shots &
Goals Scored balance…
Histogram of the all home shots and actual goals scored. some
interesting stats here detailing the more shots you have the better
chance you have scoring a goal. The largest amount of home shots reached
was 10, happenting 32 times resulting in 35 goals being scored.
## Warning: The following aesthetics were dropped during statistical transformation: fill
## ℹ This can happen when ggplot fails to infer the correct grouping structure in
## the data.
## ℹ Did you forget to specify a `group` aesthetic or to convert a numerical
## variable into a factor?
Percentage Away
shots
Percentage of times Liverpool shot away. Maximum of 28 happened 1 time.
Information in a table
|
HomeTeam == “Liverpool”
|
AS
|
n
|
prop
|
percent
|
|
FALSE
|
1
|
2
|
0.0028011
|
0.2801120
|
|
FALSE
|
2
|
2
|
0.0056022
|
0.5602241
|
|
FALSE
|
3
|
6
|
0.0084034
|
0.8403361
|
|
FALSE
|
4
|
12
|
0.0112045
|
1.1204482
|
|
FALSE
|
5
|
15
|
0.0140056
|
1.4005602
|
|
FALSE
|
6
|
20
|
0.0168067
|
1.6806723
|
|
FALSE
|
7
|
22
|
0.0196078
|
1.9607843
|
|
FALSE
|
8
|
23
|
0.0224090
|
2.2408964
|
|
FALSE
|
9
|
34
|
0.0252101
|
2.5210084
|
|
FALSE
|
10
|
33
|
0.0280112
|
2.8011204
|
|
FALSE
|
11
|
27
|
0.0308123
|
3.0812325
|
|
FALSE
|
12
|
15
|
0.0336134
|
3.3613445
|
|
FALSE
|
13
|
24
|
0.0364146
|
3.6414566
|
|
FALSE
|
14
|
31
|
0.0392157
|
3.9215686
|
|
FALSE
|
15
|
27
|
0.0420168
|
4.2016807
|
|
FALSE
|
16
|
14
|
0.0448179
|
4.4817927
|
|
FALSE
|
17
|
13
|
0.0476190
|
4.7619048
|
|
FALSE
|
18
|
9
|
0.0504202
|
5.0420168
|
|
FALSE
|
19
|
7
|
0.0532213
|
5.3221289
|
|
FALSE
|
20
|
7
|
0.0560224
|
5.6022409
|
|
FALSE
|
21
|
5
|
0.0588235
|
5.8823529
|
|
FALSE
|
22
|
5
|
0.0616246
|
6.1624650
|
|
FALSE
|
23
|
5
|
0.0644258
|
6.4425770
|
|
FALSE
|
26
|
1
|
0.0728291
|
7.2829132
|
|
FALSE
|
27
|
1
|
0.0756303
|
7.5630252
|
|
FALSE
|
28
|
1
|
0.0784314
|
7.8431373
|
|
TRUE
|
4
|
2
|
0.0470588
|
4.7058824
|
|
TRUE
|
5
|
2
|
0.0588235
|
5.8823529
|
|
TRUE
|
6
|
2
|
0.0705882
|
7.0588235
|
|
TRUE
|
7
|
1
|
0.0823529
|
8.2352941
|
|
TRUE
|
8
|
3
|
0.0941176
|
9.4117647
|
|
TRUE
|
9
|
3
|
0.1058824
|
10.5882353
|
|
TRUE
|
10
|
1
|
0.1176471
|
11.7647059
|
|
TRUE
|
11
|
2
|
0.1294118
|
12.9411765
|
|
TRUE
|
12
|
1
|
0.1411765
|
14.1176471
|
|
TRUE
|
13
|
2
|
0.1529412
|
15.2941176
|
Deeper Analysis
Larger interactive Boxplot for home goals scored by Liverpool. There
maximum home goals was 7
Comparision to
Manchester City
Same Boxplot but as an interest lets identify the Man City maximum of
home goals
Main Findings
Over 380 matches there was 481 goals scored and interestingly 483
away goals. The total of home shots was 4558 compared to the away total
of 4045. We discovered that Liverpool only scored 4 or more goals in 1
away game ( 7 against Palace) throughout the season and the lowest
amount of shots they had at home was 9. Using the mutate command and
percentage to proportion formula we discovered 29 shots were taken in 7%
of matches. We ran a comparison to Man city and they scored a maximum of
8 and the also won the League!!
Summary
From my analysis I have concluded for Liverpool to win the league
next year they will need to create more shots at goal both home and away
to beat Man City in the league. Another area they can do this is by
improving their discipline. Reducing their amount of yellow cards can
help here. To wrap up I would to present the final results below
displaying and calculating the the meadian & IQR of Home goals by
the Home Teams
## # A tibble: 20 × 3
## HomeTeam med_FTHG IQR_FTHG
## <chr> <dbl> <dbl>
## 1 Arsenal 1 2
## 2 Aston Villa 1 1.5
## 3 Brighton 1 1
## 4 Burnley 1 1
## 5 Chelsea 2 2.5
## 6 Crystal Palace 1 1
## 7 Everton 1 1
## 8 Fulham 0 1
## 9 Leeds 1 2.5
## 10 Leicester 2 1.5
## 11 Liverpool 2 2
## 12 Man City 2 2.5
## 13 Man United 1 1.5
## 14 Newcastle 1 1
## 15 Sheffield United 1 1
## 16 Southampton 1 1
## 17 Tottenham 2 1.5
## 18 West Brom 1 1
## 19 West Ham 2 1.5
## 20 Wolves 1 1