Cargar el paquete dplyr. Usamos las funciones suppressWarnings y supperssMessages para que no se impriman mensajes ni advertencias al cargar el paquete.
suppressWarnings(suppressMessages(library(dplyr)))Comenzamos importando los datos que se encuentran en archivos csv a R
Creamos un vector de los urls
urls=c("https://www.football-data.co.uk/mmz4281/1718/SP1.csv",
"https://www.football-data.co.uk/mmz4281/1819/SP1.csv",
"https://www.football-data.co.uk/mmz4281/1920/SP1.csv")creamos un vector con el nombre para los archivos csv
names=c("url1718.csv","url1819.csv","url1920.csv")Descargamos los csv en caso de ser necesario
for (i in 1:length(urls)){
if (!file.exists(names[i])){
download.file(urls[i], destfile = names[i], mode = 'wb')
}
}Importamos los csv en una lista
lista <- lapply(list.files(pattern="*.csv"), read.csv)Obtenemos una mejor idea de los datos que se encuentran en los datos con las funciones str, head, View y summary
str(lista[[1]]); str(lista[[2]]); str(lista[[3]])## 'data.frame': 380 obs. of 64 variables:
## $ Div : chr "SP1" "SP1" "SP1" "SP1" ...
## $ Date : chr "18/08/17" "18/08/17" "19/08/17" "19/08/17" ...
## $ HomeTeam : chr "Leganes" "Valencia" "Celta" "Girona" ...
## $ AwayTeam : chr "Alaves" "Las Palmas" "Sociedad" "Ath Madrid" ...
## $ FTHG : int 1 1 2 2 1 0 2 0 1 0 ...
## $ FTAG : int 0 0 3 2 1 0 0 3 0 1 ...
## $ FTR : chr "H" "H" "A" "D" ...
## $ HTHG : int 1 1 1 2 1 0 2 0 0 0 ...
## $ HTAG : int 0 0 1 0 1 0 0 2 0 0 ...
## $ HTR : chr "H" "H" "D" "H" ...
## $ HS : int 16 22 16 13 9 12 15 12 14 10 ...
## $ AS : int 6 5 13 9 9 8 3 16 9 13 ...
## $ HST : int 9 6 5 6 4 2 2 6 3 4 ...
## $ AST : int 3 4 6 3 6 2 0 8 1 6 ...
## $ HF : int 14 25 12 15 14 16 16 16 18 16 ...
## $ AF : int 18 13 11 15 12 15 15 12 14 15 ...
## $ HC : int 4 5 5 6 7 7 8 4 11 3 ...
## $ AC : int 2 2 4 0 3 6 0 4 6 7 ...
## $ HY : int 0 3 3 2 2 1 2 5 1 2 ...
## $ AY : int 1 3 1 4 4 3 1 1 3 3 ...
## $ HR : int 0 0 0 0 1 0 0 0 0 0 ...
## $ AR : int 0 1 0 1 0 1 0 1 0 0 ...
## $ B365H : num 2.05 1.75 2.38 8 1.62 1.5 1.17 9.5 3.25 2.1 ...
## $ B365D : num 3.2 3.8 3.25 4.33 4 4 8 5.75 3.25 3.3 ...
## $ B365A : num 4.1 4.5 3.2 1.45 5.5 7.5 15 1.3 2.3 3.7 ...
## $ BWH : num 2.05 1.75 2.4 7.5 1.62 1.48 1.18 9.25 3.25 2.15 ...
## $ BWD : num 3.1 3.9 3.3 4.33 3.9 4.25 7.5 5.75 3.2 3.3 ...
## $ BWA : num 4.1 4.6 3 1.45 5.75 7 14.5 1.3 2.3 3.5 ...
## $ IWH : num 2.1 1.75 2.5 7.2 1.55 1.5 1.17 7.5 3.3 2.1 ...
## $ IWD : num 3.4 3.6 3.3 4.4 4 4.2 7.5 5.5 3.35 3.4 ...
## $ IWA : num 3.5 4.8 2.85 1.45 6.2 6.5 15 1.35 2.2 3.5 ...
## $ LBH : num 2.05 1.75 2.35 7.5 1.6 1.5 1.2 9.5 3.25 2.1 ...
## $ LBD : num 3 3.8 3.25 4 3.9 4 6.5 5.25 3.1 3.1 ...
## $ LBA : num 4.2 4.33 3 1.5 5.5 7 15 1.3 2.3 3.4 ...
## $ PSH : num 2.03 1.78 2.44 8.36 1.62 ...
## $ PSD : num 3.25 4.01 3.4 4.38 4.17 4.37 7.35 5.79 3.24 3.36 ...
## $ PSA : num 4.52 4.83 3.16 1.49 6.18 7.31 15.5 1.33 2.36 3.49 ...
## $ WHH : num 2.05 1.8 2.4 8 1.67 1.5 1.22 11 3.1 2.2 ...
## $ WHD : num 3.1 3.75 3.4 4.2 3.6 4 6 4.5 3.1 3.3 ...
## $ WHA : num 4 4.2 2.9 1.44 5.5 7 13 1.33 2.4 3.3 ...
## $ VCH : num 2.05 1.8 2.4 7.5 1.65 1.5 1.2 9.5 3.25 2.15 ...
## $ VCD : num 3.2 4 3.4 4.3 4 4.2 7 5.75 3.25 3.3 ...
## $ VCA : num 4.4 4.6 3.13 1.5 5.75 7 13 1.3 2.3 3.5 ...
## $ Bb1X2 : int 35 35 35 35 35 34 35 35 34 34 ...
## $ BbMxH : num 2.12 1.83 2.5 8.36 1.69 ...
## $ BbAvH : num 2.03 1.77 2.39 7.53 1.63 1.5 1.19 9.68 3.26 2.18 ...
## $ BbMxD : num 3.4 4.04 3.5 4.4 4.17 4.4 8 5.86 3.35 3.4 ...
## $ BbAvD : num 3.15 3.86 3.32 4.17 3.93 4.17 7.11 5.44 3.17 3.26 ...
## $ BbMxA : num 4.52 4.83 3.2 1.51 6.2 7.5 17 1.35 2.4 3.7 ...
## $ BbAvA : num 4.17 4.46 3.01 1.48 5.58 ...
## $ BbOU : int 31 33 34 34 33 32 27 27 32 32 ...
## $ BbMx.2.5 : num 2.84 1.69 2.03 2.2 1.81 2.01 1.44 1.5 2.42 2.25 ...
## $ BbAv.2.5 : num 2.68 1.64 1.98 2.11 1.75 1.94 1.4 1.46 2.36 2.14 ...
## $ BbMx.2.5.1: num 1.53 2.4 1.9 1.8 2.14 1.96 3.1 2.95 1.63 1.76 ...
## $ BbAv.2.5.1: num 1.46 2.27 1.84 1.74 2.09 1.87 2.88 2.64 1.58 1.7 ...
## $ BbAH : int 18 16 18 16 16 17 17 16 15 17 ...
## $ BbAHh : num -0.5 -0.75 -0.25 1.25 -1 -1 -2 1.5 0.25 -0.25 ...
## $ BbMxAHH : num 2.07 2.05 2.08 1.77 2.12 1.9 2.05 2.03 1.93 1.92 ...
## $ BbAvAHH : num 2.03 1.97 2.05 1.75 2.06 1.86 2 1.98 1.89 1.88 ...
## $ BbMxAHA : num 1.9 1.96 1.87 2.25 1.86 2.05 1.91 1.95 2.03 2.04 ...
## $ BbAvAHA : num 1.86 1.91 1.83 2.16 1.82 2.01 1.86 1.89 1.98 1.99 ...
## $ PSCH : num 1.98 1.78 2.12 6.93 1.64 1.53 1.2 12.4 3.31 2.2 ...
## $ PSCD : num 3.35 4.24 3.53 3.83 4.18 4.48 8.25 7 3.32 3.27 ...
## $ PSCA : num 4.63 4.43 3.74 1.63 5.82 6.91 15.2 1.26 2.4 3.85 ...## 'data.frame': 380 obs. of 61 variables:
## $ Div : chr "SP1" "SP1" "SP1" "SP1" ...
## $ Date : chr "17/08/2018" "17/08/2018" "18/08/2018" "18/08/2018" ...
## $ HomeTeam : chr "Betis" "Girona" "Barcelona" "Celta" ...
## $ AwayTeam : chr "Levante" "Valladolid" "Alaves" "Espanol" ...
## $ FTHG : int 0 0 3 1 1 1 2 1 2 1 ...
## $ FTAG : int 3 0 0 1 2 2 0 4 1 1 ...
## $ FTR : chr "A" "D" "H" "D" ...
## $ HTHG : int 0 0 0 0 1 0 1 0 1 0 ...
## $ HTAG : int 1 0 0 1 1 2 0 3 1 1 ...
## $ HTR : chr "A" "D" "D" "A" ...
## $ HS : int 22 13 25 12 16 18 10 13 17 13 ...
## $ AS : int 6 2 3 14 8 8 4 17 12 9 ...
## $ HST : int 8 1 9 2 7 6 3 2 5 4 ...
## $ AST : int 4 1 0 5 4 6 1 8 2 3 ...
## $ HF : int 10 21 6 13 16 12 11 6 12 10 ...
## $ AF : int 10 20 13 14 10 13 27 15 13 15 ...
## $ HC : int 5 3 7 8 4 7 3 2 6 4 ...
## $ AC : int 3 2 1 7 6 0 0 6 2 10 ...
## $ HY : int 0 1 0 3 2 1 1 1 4 2 ...
## $ AY : int 2 1 2 2 3 1 7 0 5 3 ...
## $ HR : int 0 0 0 0 0 0 0 0 0 0 ...
## $ AR : int 0 0 0 0 0 0 0 0 0 0 ...
## $ B365H : num 1.66 1.75 1.11 1.85 2.04 1.66 1.2 3.25 1.75 3 ...
## $ B365D : num 4 3.6 10 3.5 3.4 3.75 7 3.6 3.3 3.2 ...
## $ B365A : num 5 5 21 4.5 3.8 5.5 13 2.14 5.5 2.5 ...
## $ BWH : num 1.7 1.75 1.11 1.91 2.05 1.7 1.18 3.5 1.78 2.85 ...
## $ BWD : num 3.7 3.5 10 3.4 3.3 3.7 7.25 3.5 3.5 3.25 ...
## $ BWA : num 5.25 5.25 20 4.25 3.9 5.25 16 2.1 5 2.55 ...
## $ IWH : num 1.75 1.8 1.12 1.9 2 1.7 1.2 3.5 1.85 2.85 ...
## $ IWD : num 3.6 3.6 9 3.5 3.4 3.75 6.5 3.4 3.5 3.2 ...
## $ IWA : num 4.9 4.5 20 4.1 3.8 5 15 2.1 4.4 2.55 ...
## $ PSH : num 1.69 1.8 1.11 1.93 2.06 1.72 1.2 3.46 1.79 3.12 ...
## $ PSD : num 4.19 3.7 11.27 3.64 3.51 ...
## $ PSA : num 5.11 4.99 25.4 4.27 3.91 ...
## $ WHH : num 1.67 1.75 1.08 1.91 2.05 1.73 1.22 3.3 1.8 3 ...
## $ WHD : num 3.9 3.6 9 3.5 3.3 3.6 6 3.7 3.4 3.2 ...
## $ WHA : num 4.75 4.6 29 4 3.6 4.75 13 2.05 4.75 2.4 ...
## $ VCH : num 1.67 1.8 1.1 1.93 2.05 1.7 1.2 3.4 1.8 3 ...
## $ VCD : num 4.2 3.7 10.5 3.5 3.5 3.8 7 3.6 3.4 3.2 ...
## $ VCA : num 5.2 4.8 34 4.4 3.9 5 13 2.1 5 2.45 ...
## $ Bb1X2 : int 40 40 40 38 40 40 39 40 40 39 ...
## $ BbMxH : num 1.75 1.85 1.13 1.97 2.11 1.76 1.24 3.53 1.85 3.12 ...
## $ BbAvH : num 1.68 1.78 1.1 1.9 2.03 1.7 1.21 3.38 1.78 2.99 ...
## $ BbMxD : num 4.25 3.83 11.5 3.73 3.62 3.93 7.36 3.75 3.64 3.29 ...
## $ BbAvD : num 4 3.6 9.82 3.53 3.43 3.77 6.66 3.56 3.43 3.14 ...
## $ BbMxA : num 5.25 5.27 41 4.5 3.93 ...
## $ BbAvA : num 4.95 4.79 25.67 4.2 3.76 ...
## $ BbOU : int 38 38 32 36 37 37 33 37 36 36 ...
## $ BbMx.2.5 : num 1.82 2.21 1.39 2.13 2.05 1.95 1.5 1.83 2.49 2.45 ...
## $ BbAv.2.5 : num 1.76 2.13 1.34 2.06 1.99 1.88 1.45 1.76 2.35 2.33 ...
## $ BbMx.2.5.1: num 2.15 1.78 3.4 1.84 1.88 1.98 2.75 2.13 1.64 1.65 ...
## $ BbAv.2.5.1: num 2.06 1.71 3.18 1.76 1.81 1.91 2.66 2.04 1.58 1.59 ...
## $ BbAH : int 20 20 19 18 18 19 19 19 18 17 ...
## $ BbAHh : num -0.75 -0.75 -2.5 -0.75 -0.25 -0.75 -1.75 0.25 -0.75 0.25 ...
## $ BbMxAHH : num 1.89 2.06 1.95 2.26 1.76 1.96 1.85 2.08 2.11 1.82 ...
## $ BbAvAHH : num 1.85 2.01 1.91 2.18 1.74 1.91 1.8 2.03 2.04 1.75 ...
## $ BbMxAHA : num 2.07 1.9 2 1.74 2.23 2.01 2.15 1.86 1.86 2.23 ...
## $ BbAvAHA : num 2 1.85 1.95 1.71 2.14 1.94 2.07 1.83 1.82 2.12 ...
## $ PSCH : num 1.59 1.76 1.1 2.18 2.32 1.77 1.19 4.57 1.69 3.55 ...
## $ PSCD : num 4.42 3.57 11.85 3.26 3.21 ...
## $ PSCA : num 5.89 5.62 32.17 3.85 3.53 ...## 'data.frame': 380 obs. of 105 variables:
## $ Div : chr "SP1" "SP1" "SP1" "SP1" ...
## $ Date : chr "16/08/2019" "17/08/2019" "17/08/2019" "17/08/2019" ...
## $ Time : chr "20:00" "16:00" "18:00" "19:00" ...
## $ HomeTeam : chr "Ath Bilbao" "Celta" "Valencia" "Mallorca" ...
## $ AwayTeam : chr "Barcelona" "Real Madrid" "Sociedad" "Eibar" ...
## $ FTHG : int 1 1 1 2 0 4 1 0 1 1 ...
## $ FTAG : int 0 3 1 1 1 4 0 2 2 0 ...
## $ FTR : chr "H" "A" "D" "H" ...
## $ HTHG : int 0 0 0 1 0 1 0 0 0 1 ...
## $ HTAG : int 0 1 0 0 0 1 0 1 0 0 ...
## $ HTR : chr "D" "A" "D" "H" ...
## $ HS : int 11 7 14 16 13 12 9 7 13 5 ...
## $ AS : int 11 17 12 11 4 14 16 12 14 6 ...
## $ HST : int 5 4 6 4 2 7 2 2 4 5 ...
## $ AST : int 2 11 3 5 2 7 4 4 3 0 ...
## $ HF : int 14 17 13 13 17 10 18 11 11 19 ...
## $ AF : int 9 12 14 14 11 16 15 17 19 22 ...
## $ HC : int 3 6 3 9 8 2 2 8 6 3 ...
## $ AC : int 8 4 3 3 0 7 9 4 1 4 ...
## $ HY : int 1 5 4 2 1 3 2 2 2 3 ...
## $ AY : int 1 2 4 3 4 1 1 2 6 4 ...
## $ HR : int 0 0 1 0 1 0 0 0 1 1 ...
## $ AR : int 0 1 0 0 0 0 0 0 0 1 ...
## $ B365H : num 5.25 4.75 1.66 2.8 2 1.6 2.15 3.2 1.66 1.44 ...
## $ B365D : num 3.8 4.2 3.75 3.2 3.2 3.8 3.2 3.3 3.75 4.33 ...
## $ B365A : num 1.65 1.65 5.5 2.6 4.2 6.5 3.6 2.3 5.5 8 ...
## $ BWH : num 5.5 4.4 1.67 2.95 2.05 1.6 2.15 3.1 1.65 1.45 ...
## $ BWD : num 3.8 4.2 3.75 3.1 3.25 3.8 3.3 3.4 3.75 4.33 ...
## $ BWA : num 1.65 1.72 5.5 2.6 3.9 6.25 3.6 2.3 5.75 7.5 ...
## $ IWH : num 5 5.3 1.67 2.9 2.05 1.63 2.2 3.1 1.63 1.45 ...
## $ IWD : num 3.8 4.2 3.75 3.1 3.1 4 3.25 3.4 3.75 4.4 ...
## $ IWA : num 1.7 1.6 5.3 2.6 4.05 5.5 3.4 2.3 5.7 7.2 ...
## $ PSH : num 5.15 4.73 1.68 2.98 2.1 1.62 2.29 3.13 1.63 1.49 ...
## $ PSD : num 3.84 4.18 3.94 3.14 3.21 3.99 3.31 3.56 3.81 4.34 ...
## $ PSA : num 1.74 1.72 5.47 2.66 4.13 6.13 3.45 2.33 6.38 7.58 ...
## $ WHH : num 5 5.25 1.67 2.9 2.05 1.6 2.25 3 1.62 1.47 ...
## $ WHD : num 3.8 4.2 3.8 3.1 3.2 3.9 3.3 3.5 3.75 4.2 ...
## $ WHA : num 1.7 1.6 5.25 2.62 4 5.8 3.3 2.3 6 8 ...
## $ VCH : num 5 4.75 1.67 2.9 2.1 1.65 2.25 3 1.62 1.45 ...
## $ VCD : num 3.8 4.2 3.9 3.13 3.2 4 3.3 3.5 3.8 4.2 ...
## $ VCA : num 1.75 1.73 5.75 2.7 4.1 5.75 3.3 2.3 5.75 8 ...
## $ MaxH : num 5.5 5.3 1.72 3.05 2.1 1.65 2.31 3.2 1.67 1.52 ...
## $ MaxD : num 3.95 4.4 3.98 3.2 3.3 4.15 3.4 3.56 3.9 4.5 ...
## $ MaxA : num 1.76 1.73 5.75 2.7 4.25 6.5 3.6 2.4 6.5 8.5 ...
## $ AvgH : num 5.07 4.67 1.68 2.91 2.06 1.61 2.23 3.08 1.64 1.47 ...
## $ AvgD : num 3.81 4.12 3.8 3.09 3.18 3.95 3.25 3.41 3.76 4.23 ...
## $ AvgA : num 1.71 1.69 5.29 2.62 4.02 5.8 3.43 2.33 5.78 7.63 ...
## $ B365.2.5 : num 1.8 1.53 2 2.3 2.5 1.8 2.1 1.9 2.1 2.2 ...
## $ B365.2.5.1 : num 2 2.5 1.8 1.61 1.53 2 1.72 1.9 1.72 1.66 ...
## $ P.2.5 : num 1.81 1.52 2.08 2.45 2.72 1.88 2.16 1.95 2.16 2.3 ...
## $ P.2.5.1 : num 2.09 2.66 1.82 1.6 1.5 2.02 1.76 1.95 1.76 1.68 ...
## $ Max.2.5 : num 1.85 1.53 2.14 2.47 2.75 1.9 2.2 1.98 2.21 2.3 ...
## $ Max.2.5.1 : num 2.11 2.72 1.83 1.65 1.54 2.05 1.77 1.95 1.78 1.71 ...
## $ Avg.2.5 : num 1.79 1.49 2.07 2.34 2.59 1.84 2.13 1.92 2.13 2.23 ...
## $ Avg.2.5.1 : num 2.05 2.58 1.77 1.6 1.49 1.98 1.72 1.89 1.72 1.66 ...
## $ AHh : num 0.75 0.75 -0.75 0 -0.5 -1 -0.25 0.25 -0.75 -1 ...
## $ B365AHH : num 1.99 2.04 1.91 2.05 2.08 2.05 1.95 1.88 1.86 1.88 ...
## $ B365AHA : num 1.94 1.89 2.02 1.88 1.85 1.75 1.98 2.05 2.07 2.05 ...
## $ PAHH : num 1.98 2.01 1.91 2.07 2.1 2.11 1.96 1.9 1.84 1.88 ...
## $ PAHA : num 1.94 1.91 2.01 1.85 1.82 1.81 1.96 2.02 2.08 2.04 ...
## $ MaxAHH : num 2 2.05 1.93 2.07 2.1 2.14 1.97 1.9 1.87 1.89 ...
## $ MaxAHA : num 1.95 1.91 2.03 1.88 1.85 1.85 1.99 2.06 2.08 2.08 ...
## $ AvgAHH : num 1.96 2 1.89 2.04 2.06 2.07 1.93 1.87 1.83 1.85 ...
## $ AvgAHA : num 1.92 1.88 1.99 1.85 1.83 1.8 1.95 2.01 2.06 2.03 ...
## $ B365CH : num 5.25 5.25 1.66 2.87 1.9 1.53 2.3 3 1.8 1.5 ...
## $ B365CD : num 3.8 4.2 3.75 3.2 3.1 4 3.4 3.4 3.6 4 ...
## $ B365CA : num 1.65 1.57 5.5 2.55 5 6.5 3.2 2.4 4.75 8 ...
## $ BWCH : num 4.75 4.5 1.65 2.95 1.95 1.57 2.35 3 1.8 1.5 ...
## $ BWCD : num 3.75 4.1 3.8 3.1 3.2 3.8 3.2 3.4 3.4 3.9 ...
## $ BWCA : num 1.75 1.7 5.5 2.6 4.5 6.5 3.2 2.35 5 7.75 ...
## $ IWCH : num 5 4.6 1.67 2.9 1.9 1.55 2.35 3 1.85 1.5 ...
## $ IWCD : num 3.8 3.8 3.8 3.1 3.15 4.05 3.25 3.35 3.55 3.9 ...
## $ IWCA : num 1.7 1.75 5.3 2.6 4.85 6.3 3.15 2.35 4.4 7.6 ...
## $ PSCH : num 5.34 5.1 1.69 2.96 1.9 1.54 2.43 3.13 1.82 1.57 ...
## $ PSCD : num 3.62 4.46 3.88 3.26 3.18 4.19 3.27 3.38 3.53 3.78 ...
## $ PSCA : num 1.78 1.65 5.47 2.6 5.3 6.87 3.2 2.41 5.07 7.66 ...
## $ WHCH : num 5 5 1.65 2.9 2.05 1.62 2.25 3 1.78 1.5 ...
## $ WHCD : num 3.8 4.2 3.9 3.1 3.2 3.9 3.3 3.4 3.5 3.8 ...
## $ WHCA : num 1.7 1.63 5.25 2.6 4 5.8 3.3 2.35 5 8 ...
## $ VCCH : num 4.8 5.2 1.7 3 1.9 1.57 2.45 3.13 1.87 1.55 ...
## $ VCCD : num 3.8 4.4 3.9 3.13 3.2 4 3.3 3.4 3.5 3.9 ...
## $ VCCA : num 1.8 1.65 5.5 2.63 5.2 7 3.13 2.4 4.6 8 ...
## $ MaxCH : num 5.8 6 1.72 3.05 1.95 1.58 2.46 3.38 1.87 1.58 ...
## $ MaxCD : num 3.9 4.52 3.95 3.29 3.26 4.2 3.42 3.47 3.65 4.05 ...
## $ MaxCA : num 1.81 1.75 6.2 2.72 5.3 7.3 3.58 2.48 5.35 8.9 ...
## $ AvgCH : num 5.03 4.93 1.68 2.93 1.9 1.54 2.37 3.05 1.83 1.53 ...
## $ AvgCD : num 3.66 4.26 3.82 3.14 3.16 4.05 3.25 3.34 3.5 3.84 ...
## $ AvgCA : num 1.76 1.65 5.37 2.59 4.91 6.66 3.18 2.39 4.74 7.68 ...
## $ B365C.2.5 : num 1.9 1.44 2 2.2 2.75 1.9 2.1 2 2 2.37 ...
## $ B365C.2.5.1: num 1.9 2.75 1.8 1.66 1.44 1.9 1.72 1.8 1.8 1.57 ...
## $ PC.2.5 : num 1.98 1.49 2.06 2.2 2.84 1.95 2.18 2.04 2.03 2.43 ...
## $ PC.2.5.1 : num 1.93 2.76 1.85 1.74 1.47 1.95 1.75 1.85 1.87 1.61 ...
## $ MaxC.2.5 : num 1.99 1.51 2.08 2.38 2.85 1.98 2.18 2.09 2.07 2.46 ...
## $ MaxC.2.5.1 : num 2.11 2.88 1.98 1.74 1.5 2.1 1.83 2.05 1.92 1.65 ...
## $ AvgC.2.5 : num 1.86 1.47 2 2.24 2.69 1.9 2.1 1.97 1.99 2.36 ...
## $ AvgC.2.5.1 : num 1.97 2.63 1.82 1.66 1.46 1.92 1.74 1.85 1.83 1.59 ...
## $ AHCh : num 0.75 1 -0.75 0 -0.5 -1 -0.25 0.25 -0.75 -1 ...
## $ B365CAHH : num 1.93 1.82 1.94 2.11 1.89 1.96 2.08 1.86 2.02 2.06 ...
## $ B365CAHA : num 2 1.97 1.99 1.82 2.04 1.97 1.85 2.07 1.77 1.87 ...
## [list output truncated]head(lista[[1]]); head(lista[[2]]); head(lista[[3]])## Div Date HomeTeam AwayTeam FTHG FTAG FTR HTHG HTAG HTR HS AS HST AST
## 1 SP1 18/08/17 Leganes Alaves 1 0 H 1 0 H 16 6 9 3
## 2 SP1 18/08/17 Valencia Las Palmas 1 0 H 1 0 H 22 5 6 4
## 3 SP1 19/08/17 Celta Sociedad 2 3 A 1 1 D 16 13 5 6
## 4 SP1 19/08/17 Girona Ath Madrid 2 2 D 2 0 H 13 9 6 3
## 5 SP1 19/08/17 Sevilla Espanol 1 1 D 1 1 D 9 9 4 6
## 6 SP1 20/08/17 Ath Bilbao Getafe 0 0 D 0 0 D 12 8 2 2
## HF AF HC AC HY AY HR AR B365H B365D B365A BWH BWD BWA IWH IWD IWA LBH
## 1 14 18 4 2 0 1 0 0 2.05 3.20 4.10 2.05 3.10 4.10 2.10 3.4 3.50 2.05
## 2 25 13 5 2 3 3 0 1 1.75 3.80 4.50 1.75 3.90 4.60 1.75 3.6 4.80 1.75
## 3 12 11 5 4 3 1 0 0 2.38 3.25 3.20 2.40 3.30 3.00 2.50 3.3 2.85 2.35
## 4 15 15 6 0 2 4 0 1 8.00 4.33 1.45 7.50 4.33 1.45 7.20 4.4 1.45 7.50
## 5 14 12 7 3 2 4 1 0 1.62 4.00 5.50 1.62 3.90 5.75 1.55 4.0 6.20 1.60
## 6 16 15 7 6 1 3 0 1 1.50 4.00 7.50 1.48 4.25 7.00 1.50 4.2 6.50 1.50
## LBD LBA PSH PSD PSA WHH WHD WHA VCH VCD VCA Bb1X2 BbMxH BbAvH BbMxD
## 1 3.00 4.20 2.03 3.25 4.52 2.05 3.10 4.00 2.05 3.2 4.40 35 2.12 2.03 3.40
## 2 3.80 4.33 1.78 4.01 4.83 1.80 3.75 4.20 1.80 4.0 4.60 35 1.83 1.77 4.04
## 3 3.25 3.00 2.44 3.40 3.16 2.40 3.40 2.90 2.40 3.4 3.13 35 2.50 2.39 3.50
## 4 4.00 1.50 8.36 4.38 1.49 8.00 4.20 1.44 7.50 4.3 1.50 35 8.36 7.53 4.40
## 5 3.90 5.50 1.62 4.17 6.18 1.67 3.60 5.50 1.65 4.0 5.75 35 1.69 1.63 4.17
## 6 4.00 7.00 1.53 4.37 7.31 1.50 4.00 7.00 1.50 4.2 7.00 34 1.53 1.50 4.40
## BbAvD BbMxA BbAvA BbOU BbMx.2.5 BbAv.2.5 BbMx.2.5.1 BbAv.2.5.1 BbAH BbAHh
## 1 3.15 4.52 4.17 31 2.84 2.68 1.53 1.46 18 -0.50
## 2 3.86 4.83 4.46 33 1.69 1.64 2.40 2.27 16 -0.75
## 3 3.32 3.20 3.01 34 2.03 1.98 1.90 1.84 18 -0.25
## 4 4.17 1.51 1.48 34 2.20 2.11 1.80 1.74 16 1.25
## 5 3.93 6.20 5.58 33 1.81 1.75 2.14 2.09 16 -1.00
## 6 4.17 7.50 6.94 32 2.01 1.94 1.96 1.87 17 -1.00
## BbMxAHH BbAvAHH BbMxAHA BbAvAHA PSCH PSCD PSCA
## 1 2.07 2.03 1.90 1.86 1.98 3.35 4.63
## 2 2.05 1.97 1.96 1.91 1.78 4.24 4.43
## 3 2.08 2.05 1.87 1.83 2.12 3.53 3.74
## 4 1.77 1.75 2.25 2.16 6.93 3.83 1.63
## 5 2.12 2.06 1.86 1.82 1.64 4.18 5.82
## 6 1.90 1.86 2.05 2.01 1.53 4.48 6.91## Div Date HomeTeam AwayTeam FTHG FTAG FTR HTHG HTAG HTR HS AS HST
## 1 SP1 17/08/2018 Betis Levante 0 3 A 0 1 A 22 6 8
## 2 SP1 17/08/2018 Girona Valladolid 0 0 D 0 0 D 13 2 1
## 3 SP1 18/08/2018 Barcelona Alaves 3 0 H 0 0 D 25 3 9
## 4 SP1 18/08/2018 Celta Espanol 1 1 D 0 1 A 12 14 2
## 5 SP1 18/08/2018 Villarreal Sociedad 1 2 A 1 1 D 16 8 7
## 6 SP1 19/08/2018 Eibar Huesca 1 2 A 0 2 A 18 8 6
## AST HF AF HC AC HY AY HR AR B365H B365D B365A BWH BWD BWA IWH IWD IWA
## 1 4 10 10 5 3 0 2 0 0 1.66 4.00 5.0 1.70 3.7 5.25 1.75 3.60 4.9
## 2 1 21 20 3 2 1 1 0 0 1.75 3.60 5.0 1.75 3.5 5.25 1.80 3.60 4.5
## 3 0 6 13 7 1 0 2 0 0 1.11 10.00 21.0 1.11 10.0 20.00 1.12 9.00 20.0
## 4 5 13 14 8 7 3 2 0 0 1.85 3.50 4.5 1.91 3.4 4.25 1.90 3.50 4.1
## 5 4 16 10 4 6 2 3 0 0 2.04 3.40 3.8 2.05 3.3 3.90 2.00 3.40 3.8
## 6 6 12 13 7 0 1 1 0 0 1.66 3.75 5.5 1.70 3.7 5.25 1.70 3.75 5.0
## PSH PSD PSA WHH WHD WHA VCH VCD VCA Bb1X2 BbMxH BbAvH BbMxD BbAvD
## 1 1.69 4.19 5.11 1.67 3.9 4.75 1.67 4.2 5.2 40 1.75 1.68 4.25 4.00
## 2 1.80 3.70 4.99 1.75 3.6 4.60 1.80 3.7 4.8 40 1.85 1.78 3.83 3.60
## 3 1.11 11.27 25.40 1.08 9.0 29.00 1.10 10.5 34.0 40 1.13 1.10 11.50 9.82
## 4 1.93 3.64 4.27 1.91 3.5 4.00 1.93 3.5 4.4 38 1.97 1.90 3.73 3.53
## 5 2.06 3.51 3.91 2.05 3.3 3.60 2.05 3.5 3.9 40 2.11 2.03 3.62 3.43
## 6 1.72 3.90 5.26 1.73 3.6 4.75 1.70 3.8 5.0 40 1.76 1.70 3.93 3.77
## BbMxA BbAvA BbOU BbMx.2.5 BbAv.2.5 BbMx.2.5.1 BbAv.2.5.1 BbAH BbAHh BbMxAHH
## 1 5.25 4.95 38 1.82 1.76 2.15 2.06 20 -0.75 1.89
## 2 5.27 4.79 38 2.21 2.13 1.78 1.71 20 -0.75 2.06
## 3 41.00 25.67 32 1.39 1.34 3.40 3.18 19 -2.50 1.95
## 4 4.50 4.20 36 2.13 2.06 1.84 1.76 18 -0.75 2.26
## 5 3.93 3.76 37 2.05 1.99 1.88 1.81 18 -0.25 1.76
## 6 5.50 5.08 37 1.95 1.88 1.98 1.91 19 -0.75 1.96
## BbAvAHH BbMxAHA BbAvAHA PSCH PSCD PSCA
## 1 1.85 2.07 2.00 1.59 4.42 5.89
## 2 2.01 1.90 1.85 1.76 3.57 5.62
## 3 1.91 2.00 1.95 1.10 11.85 32.17
## 4 2.18 1.74 1.71 2.18 3.26 3.85
## 5 1.74 2.23 2.14 2.32 3.21 3.53
## 6 1.91 2.01 1.94 1.77 3.68 5.32## Div Date Time HomeTeam AwayTeam FTHG FTAG FTR HTHG HTAG HTR HS AS
## 1 SP1 16/08/2019 20:00 Ath Bilbao Barcelona 1 0 H 0 0 D 11 11
## 2 SP1 17/08/2019 16:00 Celta Real Madrid 1 3 A 0 1 A 7 17
## 3 SP1 17/08/2019 18:00 Valencia Sociedad 1 1 D 0 0 D 14 12
## 4 SP1 17/08/2019 19:00 Mallorca Eibar 2 1 H 1 0 H 16 11
## 5 SP1 17/08/2019 20:00 Leganes Osasuna 0 1 A 0 0 D 13 4
## 6 SP1 17/08/2019 20:00 Villarreal Granada 4 4 D 1 1 D 12 14
## HST AST HF AF HC AC HY AY HR AR B365H B365D B365A BWH BWD BWA IWH IWD
## 1 5 2 14 9 3 8 1 1 0 0 5.25 3.80 1.65 5.50 3.80 1.65 5.00 3.80
## 2 4 11 17 12 6 4 5 2 0 1 4.75 4.20 1.65 4.40 4.20 1.72 5.30 4.20
## 3 6 3 13 14 3 3 4 4 1 0 1.66 3.75 5.50 1.67 3.75 5.50 1.67 3.75
## 4 4 5 13 14 9 3 2 3 0 0 2.80 3.20 2.60 2.95 3.10 2.60 2.90 3.10
## 5 2 2 17 11 8 0 1 4 1 0 2.00 3.20 4.20 2.05 3.25 3.90 2.05 3.10
## 6 7 7 10 16 2 7 3 1 0 0 1.60 3.80 6.50 1.60 3.80 6.25 1.63 4.00
## IWA PSH PSD PSA WHH WHD WHA VCH VCD VCA MaxH MaxD MaxA AvgH AvgD
## 1 1.70 5.15 3.84 1.74 5.00 3.8 1.70 5.00 3.80 1.75 5.50 3.95 1.76 5.07 3.81
## 2 1.60 4.73 4.18 1.72 5.25 4.2 1.60 4.75 4.20 1.73 5.30 4.40 1.73 4.67 4.12
## 3 5.30 1.68 3.94 5.47 1.67 3.8 5.25 1.67 3.90 5.75 1.72 3.98 5.75 1.68 3.80
## 4 2.60 2.98 3.14 2.66 2.90 3.1 2.62 2.90 3.13 2.70 3.05 3.20 2.70 2.91 3.09
## 5 4.05 2.10 3.21 4.13 2.05 3.2 4.00 2.10 3.20 4.10 2.10 3.30 4.25 2.06 3.18
## 6 5.50 1.62 3.99 6.13 1.60 3.9 5.80 1.65 4.00 5.75 1.65 4.15 6.50 1.61 3.95
## AvgA B365.2.5 B365.2.5.1 P.2.5 P.2.5.1 Max.2.5 Max.2.5.1 Avg.2.5 Avg.2.5.1
## 1 1.71 1.80 2.00 1.81 2.09 1.85 2.11 1.79 2.05
## 2 1.69 1.53 2.50 1.52 2.66 1.53 2.72 1.49 2.58
## 3 5.29 2.00 1.80 2.08 1.82 2.14 1.83 2.07 1.77
## 4 2.62 2.30 1.61 2.45 1.60 2.47 1.65 2.34 1.60
## 5 4.02 2.50 1.53 2.72 1.50 2.75 1.54 2.59 1.49
## 6 5.80 1.80 2.00 1.88 2.02 1.90 2.05 1.84 1.98
## AHh B365AHH B365AHA PAHH PAHA MaxAHH MaxAHA AvgAHH AvgAHA B365CH B365CD
## 1 0.75 1.99 1.94 1.98 1.94 2.00 1.95 1.96 1.92 5.25 3.80
## 2 0.75 2.04 1.89 2.01 1.91 2.05 1.91 2.00 1.88 5.25 4.20
## 3 -0.75 1.91 2.02 1.91 2.01 1.93 2.03 1.89 1.99 1.66 3.75
## 4 0.00 2.05 1.88 2.07 1.85 2.07 1.88 2.04 1.85 2.87 3.20
## 5 -0.50 2.08 1.85 2.10 1.82 2.10 1.85 2.06 1.83 1.90 3.10
## 6 -1.00 2.05 1.75 2.11 1.81 2.14 1.85 2.07 1.80 1.53 4.00
## B365CA BWCH BWCD BWCA IWCH IWCD IWCA PSCH PSCD PSCA WHCH WHCD WHCA VCCH VCCD
## 1 1.65 4.75 3.75 1.75 5.00 3.80 1.70 5.34 3.62 1.78 5.00 3.8 1.70 4.80 3.80
## 2 1.57 4.50 4.10 1.70 4.60 3.80 1.75 5.10 4.46 1.65 5.00 4.2 1.63 5.20 4.40
## 3 5.50 1.65 3.80 5.50 1.67 3.80 5.30 1.69 3.88 5.47 1.65 3.9 5.25 1.70 3.90
## 4 2.55 2.95 3.10 2.60 2.90 3.10 2.60 2.96 3.26 2.60 2.90 3.1 2.60 3.00 3.13
## 5 5.00 1.95 3.20 4.50 1.90 3.15 4.85 1.90 3.18 5.30 2.05 3.2 4.00 1.90 3.20
## 6 6.50 1.57 3.80 6.50 1.55 4.05 6.30 1.54 4.19 6.87 1.62 3.9 5.80 1.57 4.00
## VCCA MaxCH MaxCD MaxCA AvgCH AvgCD AvgCA B365C.2.5 B365C.2.5.1 PC.2.5
## 1 1.80 5.80 3.90 1.81 5.03 3.66 1.76 1.90 1.90 1.98
## 2 1.65 6.00 4.52 1.75 4.93 4.26 1.65 1.44 2.75 1.49
## 3 5.50 1.72 3.95 6.20 1.68 3.82 5.37 2.00 1.80 2.06
## 4 2.63 3.05 3.29 2.72 2.93 3.14 2.59 2.20 1.66 2.20
## 5 5.20 1.95 3.26 5.30 1.90 3.16 4.91 2.75 1.44 2.84
## 6 7.00 1.58 4.20 7.30 1.54 4.05 6.66 1.90 1.90 1.95
## PC.2.5.1 MaxC.2.5 MaxC.2.5.1 AvgC.2.5 AvgC.2.5.1 AHCh B365CAHH B365CAHA
## 1 1.93 1.99 2.11 1.86 1.97 0.75 1.93 2.00
## 2 2.76 1.51 2.88 1.47 2.63 1.00 1.82 1.97
## 3 1.85 2.08 1.98 2.00 1.82 -0.75 1.94 1.99
## 4 1.74 2.38 1.74 2.24 1.66 0.00 2.11 1.82
## 5 1.47 2.85 1.50 2.69 1.46 -0.50 1.89 2.04
## 6 1.95 1.98 2.10 1.90 1.92 -1.00 1.96 1.97
## PCAHH PCAHA MaxCAHH MaxCAHA AvgCAHH AvgCAHA
## 1 1.91 2.01 2.02 2.03 1.91 1.98
## 2 1.85 2.07 2.00 2.20 1.82 2.06
## 3 1.92 2.00 1.96 2.12 1.89 2.00
## 4 2.09 1.83 2.12 1.88 2.07 1.83
## 5 1.90 2.01 1.95 2.06 1.90 1.99
## 6 1.96 1.96 1.98 2.12 1.93 1.95View(lista[[1]]); View(lista[[2]]); View(lista[[3]])
summary(lista[[1]]); summary(lista[[2]]); summary(lista[[3]])## Div Date HomeTeam AwayTeam
## Length:380 Length:380 Length:380 Length:380
## Class :character Class :character Class :character Class :character
## Mode :character Mode :character Mode :character Mode :character
##
##
##
##
## FTHG FTAG FTR HTHG
## Min. :0.000 Min. :0.000 Length:380 Min. :0.0000
## 1st Qu.:0.750 1st Qu.:0.000 Class :character 1st Qu.:0.0000
## Median :1.000 Median :1.000 Mode :character Median :0.0000
## Mean :1.547 Mean :1.147 Mean :0.6605
## 3rd Qu.:2.000 3rd Qu.:2.000 3rd Qu.:1.0000
## Max. :7.000 Max. :6.000 Max. :5.0000
##
## HTAG HTR HS AS
## Min. :0.0000 Length:380 Min. : 2.00 Min. : 1.00
## 1st Qu.:0.0000 Class :character 1st Qu.:10.00 1st Qu.: 8.00
## Median :0.0000 Mode :character Median :13.00 Median :10.00
## Mean :0.4868 Mean :13.53 Mean :10.47
## 3rd Qu.:1.0000 3rd Qu.:16.00 3rd Qu.:13.00
## Max. :3.0000 Max. :30.00 Max. :24.00
##
## HST AST HF AF
## Min. : 0.000 Min. : 0.000 Min. : 4.00 Min. : 0.00
## 1st Qu.: 3.000 1st Qu.: 2.000 1st Qu.:11.00 1st Qu.:11.00
## Median : 4.500 Median : 3.000 Median :13.00 Median :14.00
## Mean : 4.758 Mean : 3.805 Mean :13.73 Mean :13.95
## 3rd Qu.: 6.000 3rd Qu.: 5.000 3rd Qu.:17.00 3rd Qu.:17.00
## Max. :14.000 Max. :13.000 Max. :29.00 Max. :29.00
##
## HC AC HY AY
## Min. : 0.000 Min. : 0.000 Min. :0.000 Min. :0.000
## 1st Qu.: 4.000 1st Qu.: 2.000 1st Qu.:1.000 1st Qu.:2.000
## Median : 5.000 Median : 4.000 Median :2.000 Median :3.000
## Mean : 5.613 Mean : 4.192 Mean :2.339 Mean :2.676
## 3rd Qu.: 7.000 3rd Qu.: 6.000 3rd Qu.:3.000 3rd Qu.:4.000
## Max. :16.000 Max. :14.000 Max. :8.000 Max. :9.000
##
## HR AR B365H B365D
## Min. :0.0000 Min. :0.00000 Min. : 1.050 Min. : 2.790
## 1st Qu.:0.0000 1st Qu.:0.00000 1st Qu.: 1.617 1st Qu.: 3.290
## Median :0.0000 Median :0.00000 Median : 2.075 Median : 3.500
## Mean :0.1105 Mean :0.07895 Mean : 2.777 Mean : 4.259
## 3rd Qu.:0.0000 3rd Qu.:0.00000 3rd Qu.: 2.790 3rd Qu.: 4.330
## Max. :2.0000 Max. :2.00000 Max. :17.000 Max. :15.000
##
## B365A BWH BWD BWA
## Min. : 1.170 Min. : 1.050 Min. : 2.950 Min. : 1.180
## 1st Qu.: 2.600 1st Qu.: 1.650 1st Qu.: 3.300 1st Qu.: 2.600
## Median : 3.700 Median : 2.100 Median : 3.600 Median : 3.700
## Mean : 5.192 Mean : 2.744 Mean : 4.278 Mean : 5.204
## 3rd Qu.: 5.500 3rd Qu.: 2.750 3rd Qu.: 4.330 3rd Qu.: 5.500
## Max. :34.000 Max. :14.500 Max. :15.500 Max. :34.000
##
## IWH IWD IWA LBH
## Min. : 1.070 Min. : 3.050 Min. : 1.200 Min. : 1.050
## 1st Qu.: 1.650 1st Qu.: 3.300 1st Qu.: 2.600 1st Qu.: 1.610
## Median : 2.100 Median : 3.500 Median : 3.500 Median : 2.050
## Mean : 2.721 Mean : 4.161 Mean : 5.041 Mean : 2.742
## 3rd Qu.: 2.700 3rd Qu.: 4.200 3rd Qu.: 5.300 3rd Qu.: 2.750
## Max. :15.000 Max. :12.000 Max. :27.000 Max. :19.000
## NA's :1
## LBD LBA PSH PSD
## Min. : 2.900 Min. : 1.170 Min. : 1.050 Min. : 3.020
## 1st Qu.: 3.250 1st Qu.: 2.575 1st Qu.: 1.660 1st Qu.: 3.410
## Median : 3.500 Median : 3.600 Median : 2.120 Median : 3.705
## Mean : 4.152 Mean : 5.375 Mean : 2.857 Mean : 4.539
## 3rd Qu.: 4.200 3rd Qu.: 5.500 3rd Qu.: 2.850 3rd Qu.: 4.455
## Max. :17.000 Max. :41.000 Max. :19.650 Max. :20.380
## NA's :1 NA's :1
## PSA WHH WHD WHA
## Min. : 1.180 Min. : 1.060 Min. : 2.900 Min. : 1.170
## 1st Qu.: 2.670 1st Qu.: 1.665 1st Qu.: 3.250 1st Qu.: 2.600
## Median : 3.845 Median : 2.100 Median : 3.500 Median : 3.550
## Mean : 5.522 Mean : 2.738 Mean : 4.092 Mean : 5.041
## 3rd Qu.: 5.942 3rd Qu.: 2.750 3rd Qu.: 4.200 3rd Qu.: 5.500
## Max. :36.500 Max. :17.000 Max. :15.000 Max. :26.000
##
## VCH VCD VCA Bb1X2
## Min. : 1.040 Min. : 3.000 Min. : 1.180 Min. : 3.00
## 1st Qu.: 1.650 1st Qu.: 3.400 1st Qu.: 2.630 1st Qu.:35.00
## Median : 2.100 Median : 3.700 Median : 3.700 Median :37.00
## Mean : 2.762 Mean : 4.416 Mean : 5.472 Mean :37.71
## 3rd Qu.: 2.800 3rd Qu.: 4.400 3rd Qu.: 5.750 3rd Qu.:40.00
## Max. :15.000 Max. :17.000 Max. :36.000 Max. :43.00
##
## BbMxH BbAvH BbMxD BbAvD
## Min. : 1.080 Min. : 1.050 Min. : 3.110 Min. : 2.940
## 1st Qu.: 1.700 1st Qu.: 1.640 1st Qu.: 3.478 1st Qu.: 3.328
## Median : 2.200 Median : 2.090 Median : 3.750 Median : 3.570
## Mean : 2.966 Mean : 2.743 Mean : 4.636 Mean : 4.261
## 3rd Qu.: 2.882 3rd Qu.: 2.765 3rd Qu.: 4.553 3rd Qu.: 4.272
## Max. :19.650 Max. :16.300 Max. :20.380 Max. :15.320
##
## BbMxA BbAvA BbOU BbMx.2.5
## Min. : 1.210 Min. : 1.170 Min. : 3.00 Min. :1.130
## 1st Qu.: 2.728 1st Qu.: 2.607 1st Qu.:31.75 1st Qu.:1.667
## Median : 3.920 Median : 3.665 Median :34.00 Median :1.960
## Mean : 6.107 Mean : 5.190 Mean :34.06 Mean :1.950
## 3rd Qu.: 6.105 3rd Qu.: 5.543 3rd Qu.:37.00 3rd Qu.:2.203
## Max. :67.000 Max. :33.420 Max. :42.00 Max. :3.080
##
## BbAv.2.5 BbMx.2.5.1 BbAv.2.5.1 BbAH
## Min. :1.120 Min. :1.470 Min. :1.410 Min. : 1.00
## 1st Qu.:1.617 1st Qu.:1.780 1st Qu.:1.718 1st Qu.:17.00
## Median :1.880 Median :2.000 Median :1.920 Median :18.00
## Mean :1.872 Mean :2.284 Mean :2.162 Mean :18.16
## 3rd Qu.:2.120 3rd Qu.:2.402 3rd Qu.:2.283 3rd Qu.:19.00
## Max. :2.850 Max. :7.000 Max. :5.970 Max. :24.00
##
## BbAHh BbMxAHH BbAvAHH BbMxAHA
## Min. :-3.2500 Min. :1.610 Min. :1.580 Min. :1.680
## 1st Qu.:-0.7500 1st Qu.:1.890 1st Qu.:1.840 1st Qu.:1.897
## Median :-0.2500 Median :1.985 Median :1.930 Median :1.970
## Mean :-0.4059 Mean :1.988 Mean :1.938 Mean :1.988
## 3rd Qu.: 0.0625 3rd Qu.:2.070 3rd Qu.:2.020 3rd Qu.:2.080
## Max. : 2.0000 Max. :2.420 Max. :2.340 Max. :2.520
##
## BbAvAHA PSCH PSCD PSCA
## Min. :1.630 Min. : 1.060 Min. : 2.930 Min. : 1.160
## 1st Qu.:1.850 1st Qu.: 1.640 1st Qu.: 3.410 1st Qu.: 2.590
## Median :1.930 Median : 2.120 Median : 3.700 Median : 3.850
## Mean :1.937 Mean : 2.839 Mean : 4.508 Mean : 5.695
## 3rd Qu.:2.030 3rd Qu.: 2.980 3rd Qu.: 4.560 3rd Qu.: 6.095
## Max. :2.440 Max. :18.700 Max. :18.500 Max. :46.000
## NA's :1 NA's :1 NA's :1## Div Date HomeTeam AwayTeam
## Length:380 Length:380 Length:380 Length:380
## Class :character Class :character Class :character Class :character
## Mode :character Mode :character Mode :character Mode :character
##
##
##
## FTHG FTAG FTR HTHG
## Min. :0.000 Min. :0.000 Length:380 Min. :0.0000
## 1st Qu.:1.000 1st Qu.:0.000 Class :character 1st Qu.:0.0000
## Median :1.000 Median :1.000 Mode :character Median :0.0000
## Mean :1.453 Mean :1.134 Mean :0.5447
## 3rd Qu.:2.000 3rd Qu.:2.000 3rd Qu.:1.0000
## Max. :8.000 Max. :6.000 Max. :3.0000
## HTAG HTR HS AS
## Min. :0.0000 Length:380 Min. : 3.00 Min. : 2.00
## 1st Qu.:0.0000 Class :character 1st Qu.:10.00 1st Qu.: 8.00
## Median :0.0000 Mode :character Median :13.00 Median :10.00
## Mean :0.5132 Mean :13.87 Mean :10.43
## 3rd Qu.:1.0000 3rd Qu.:17.00 3rd Qu.:13.00
## Max. :5.0000 Max. :34.00 Max. :21.00
## HST AST HF AF
## Min. : 0.000 Min. : 0.000 Min. : 1.00 Min. : 3.00
## 1st Qu.: 3.000 1st Qu.: 2.000 1st Qu.:11.00 1st Qu.:11.00
## Median : 5.000 Median : 3.000 Median :13.00 Median :13.00
## Mean : 4.834 Mean : 3.589 Mean :13.63 Mean :13.45
## 3rd Qu.: 6.000 3rd Qu.: 5.000 3rd Qu.:16.00 3rd Qu.:16.00
## Max. :15.000 Max. :11.000 Max. :26.00 Max. :27.00
## HC AC HY AY
## Min. : 0.000 Min. : 0.000 Min. :0.000 Min. :0.000
## 1st Qu.: 4.000 1st Qu.: 2.000 1st Qu.:1.000 1st Qu.:2.000
## Median : 5.000 Median : 4.000 Median :2.000 Median :3.000
## Mean : 5.574 Mean : 4.021 Mean :2.529 Mean :2.642
## 3rd Qu.: 7.000 3rd Qu.: 6.000 3rd Qu.:4.000 3rd Qu.:3.000
## Max. :15.000 Max. :12.000 Max. :8.000 Max. :7.000
## HR AR B365H B365D
## Min. :0.00000 Min. :0.0000 Min. : 1.080 Min. : 2.870
## 1st Qu.:0.00000 1st Qu.:0.0000 1st Qu.: 1.660 1st Qu.: 3.300
## Median :0.00000 Median :0.0000 Median : 2.120 Median : 3.500
## Mean :0.08684 Mean :0.1211 Mean : 2.596 Mean : 3.996
## 3rd Qu.:0.00000 3rd Qu.:0.0000 3rd Qu.: 2.800 3rd Qu.: 4.000
## Max. :1.00000 Max. :2.0000 Max. :17.000 Max. :11.000
## B365A BWH BWD BWA
## Min. : 1.160 Min. : 1.060 Min. : 2.900 Min. : 1.190
## 1st Qu.: 2.547 1st Qu.: 1.670 1st Qu.: 3.300 1st Qu.: 2.600
## Median : 3.500 Median : 2.150 Median : 3.500 Median : 3.500
## Mean : 4.790 Mean : 2.579 Mean : 3.991 Mean : 4.745
## 3rd Qu.: 5.062 3rd Qu.: 2.800 3rd Qu.: 4.000 3rd Qu.: 5.250
## Max. :29.000 Max. :15.000 Max. :12.000 Max. :36.000
## IWH IWD IWA PSH
## Min. : 1.070 Min. : 2.850 Min. : 1.200 Min. : 1.080
## 1st Qu.: 1.700 1st Qu.: 3.300 1st Qu.: 2.600 1st Qu.: 1.700
## Median : 2.150 Median : 3.500 Median : 3.450 Median : 2.180
## Mean : 2.553 Mean : 3.943 Mean : 4.587 Mean : 2.639
## 3rd Qu.: 2.763 3rd Qu.: 4.000 3rd Qu.: 4.950 3rd Qu.: 2.840
## Max. :13.000 Max. :13.000 Max. :28.000 Max. :19.070
## PSD PSA WHH WHD
## Min. : 2.990 Min. : 1.180 Min. : 1.050 Min. : 2.500
## 1st Qu.: 3.357 1st Qu.: 2.652 1st Qu.: 1.700 1st Qu.: 3.300
## Median : 3.640 Median : 3.575 Median : 2.150 Median : 3.500
## Mean : 4.133 Mean : 4.994 Mean : 2.564 Mean : 3.997
## 3rd Qu.: 4.170 3rd Qu.: 5.230 3rd Qu.: 2.800 3rd Qu.: 4.000
## Max. :13.220 Max. :36.830 Max. :17.000 Max. :13.000
## WHA VCH VCD VCA
## Min. : 1.150 Min. : 1.060 Min. : 3.000 Min. : 1.18
## 1st Qu.: 2.587 1st Qu.: 1.700 1st Qu.: 3.300 1st Qu.: 2.60
## Median : 3.500 Median : 2.150 Median : 3.600 Median : 3.60
## Mean : 4.779 Mean : 2.627 Mean : 4.097 Mean : 5.00
## 3rd Qu.: 5.000 3rd Qu.: 2.800 3rd Qu.: 4.200 3rd Qu.: 5.20
## Max. :34.000 Max. :21.000 Max. :13.000 Max. :41.00
## Bb1X2 BbMxH BbAvH BbMxD
## Min. :31.00 Min. : 1.100 Min. : 1.070 Min. : 3.040
## 1st Qu.:34.00 1st Qu.: 1.750 1st Qu.: 1.690 1st Qu.: 3.420
## Median :36.00 Median : 2.250 Median : 2.160 Median : 3.735
## Mean :36.13 Mean : 2.739 Mean : 2.582 Mean : 4.251
## 3rd Qu.:38.00 3rd Qu.: 2.913 3rd Qu.: 2.792 3rd Qu.: 4.250
## Max. :41.00 Max. :21.000 Max. :16.550 Max. :15.000
## BbAvD BbMxA BbAvA BbOU
## Min. : 2.920 Min. : 1.200 Min. : 1.170 Min. :28.00
## 1st Qu.: 3.288 1st Qu.: 2.750 1st Qu.: 2.620 1st Qu.:32.00
## Median : 3.550 Median : 3.695 Median : 3.495 Median :34.00
## Mean : 4.005 Mean : 5.361 Mean : 4.763 Mean :33.84
## 3rd Qu.: 4.032 3rd Qu.: 5.370 3rd Qu.: 5.043 3rd Qu.:35.00
## Max. :12.430 Max. :52.000 Max. :33.380 Max. :39.00
## BbMx.2.5 BbAv.2.5 BbMx.2.5.1 BbAv.2.5.1
## Min. :1.200 Min. :1.170 Min. :1.420 Min. :1.380
## 1st Qu.:1.710 1st Qu.:1.650 1st Qu.:1.710 1st Qu.:1.650
## Median :2.000 Median :1.940 Median :1.950 Median :1.870
## Mean :2.029 Mean :1.947 Mean :2.116 Mean :2.018
## 3rd Qu.:2.315 3rd Qu.:2.230 3rd Qu.:2.303 3rd Qu.:2.210
## Max. :3.200 Max. :2.890 Max. :5.250 Max. :4.740
## BbAH BbAHh BbMxAHH BbAvAHH
## Min. :15.00 Min. :-3.0000 Min. :1.560 Min. :1.520
## 1st Qu.:19.00 1st Qu.:-1.0000 1st Qu.:1.850 1st Qu.:1.800
## Median :20.00 Median :-0.2500 Median :2.030 Median :1.970
## Mean :19.88 Mean :-0.4033 Mean :2.055 Mean :1.992
## 3rd Qu.:21.00 3rd Qu.: 0.2500 3rd Qu.:2.200 3rd Qu.:2.130
## Max. :24.00 Max. : 2.0000 Max. :3.270 Max. :3.020
## BbMxAHA BbAvAHA PSCH PSCD
## Min. :1.450 Min. :1.410 Min. : 1.070 Min. : 2.860
## 1st Qu.:1.800 1st Qu.:1.750 1st Qu.: 1.698 1st Qu.: 3.310
## Median :1.950 Median :1.890 Median : 2.190 Median : 3.610
## Mean :1.972 Mean :1.915 Mean : 2.726 Mean : 4.102
## 3rd Qu.:2.130 3rd Qu.:2.070 3rd Qu.: 2.970 3rd Qu.: 4.202
## Max. :2.850 Max. :2.670 Max. :18.040 Max. :14.910
## PSCA
## Min. : 1.190
## 1st Qu.: 2.612
## Median : 3.645
## Mean : 5.100
## 3rd Qu.: 5.575
## Max. :36.030## Div Date Time HomeTeam
## Length:380 Length:380 Length:380 Length:380
## Class :character Class :character Class :character Class :character
## Mode :character Mode :character Mode :character Mode :character
##
##
##
##
## AwayTeam FTHG FTAG FTR
## Length:380 Min. :0.000 Min. :0.000 Length:380
## Class :character 1st Qu.:1.000 1st Qu.:0.000 Class :character
## Mode :character Median :1.000 Median :1.000 Mode :character
## Mean :1.437 Mean :1.042
## 3rd Qu.:2.000 3rd Qu.:2.000
## Max. :6.000 Max. :5.000
##
## HTHG HTAG HTR HS
## Min. :0.0000 Min. :0.00 Length:380 Min. : 3.00
## 1st Qu.:0.0000 1st Qu.:0.00 Class :character 1st Qu.: 9.00
## Median :0.0000 Median :0.00 Mode :character Median :12.00
## Mean :0.6026 Mean :0.45 Mean :12.46
## 3rd Qu.:1.0000 3rd Qu.:1.00 3rd Qu.:15.00
## Max. :4.0000 Max. :3.00 Max. :25.00
##
## AS HST AST HF
## Min. : 1.00 Min. : 0.000 Min. : 0.000 Min. : 4.00
## 1st Qu.: 7.00 1st Qu.: 3.000 1st Qu.: 2.000 1st Qu.:11.00
## Median :10.00 Median : 4.000 Median : 3.000 Median :13.00
## Mean :10.14 Mean : 4.337 Mean : 3.511 Mean :13.66
## 3rd Qu.:12.25 3rd Qu.: 6.000 3rd Qu.: 5.000 3rd Qu.:16.00
## Max. :24.00 Max. :17.000 Max. :12.000 Max. :28.00
##
## AF HC AC HY
## Min. : 5.00 Min. : 0.000 Min. : 0.000 Min. :0.000
## 1st Qu.:11.00 1st Qu.: 3.000 1st Qu.: 2.750 1st Qu.:1.000
## Median :13.00 Median : 5.000 Median : 4.000 Median :2.000
## Mean :13.79 Mean : 5.042 Mean : 4.195 Mean :2.547
## 3rd Qu.:16.00 3rd Qu.: 7.000 3rd Qu.: 6.000 3rd Qu.:4.000
## Max. :30.00 Max. :14.000 Max. :12.000 Max. :7.000
##
## AY HR AR B365H
## Min. :0.000 Min. :0.0 Min. :0.0000 Min. : 1.120
## 1st Qu.:2.000 1st Qu.:0.0 1st Qu.:0.0000 1st Qu.: 1.700
## Median :2.000 Median :0.0 Median :0.0000 Median : 2.200
## Mean :2.584 Mean :0.1 Mean :0.1263 Mean : 2.595
## 3rd Qu.:4.000 3rd Qu.:0.0 3rd Qu.:0.0000 3rd Qu.: 2.900
## Max. :8.000 Max. :2.0 Max. :2.0000 Max. :10.000
##
## B365D B365A BWH BWD
## Min. :2.800 Min. : 1.280 Min. : 1.120 Min. :2.700
## 1st Qu.:3.200 1st Qu.: 2.500 1st Qu.: 1.700 1st Qu.:3.200
## Median :3.400 Median : 3.500 Median : 2.200 Median :3.400
## Mean :3.805 Mean : 4.465 Mean : 2.599 Mean :3.813
## 3rd Qu.:4.000 3rd Qu.: 5.062 3rd Qu.: 2.900 3rd Qu.:4.000
## Max. :9.500 Max. :21.000 Max. :10.000 Max. :9.500
##
## BWA IWH IWD IWA
## Min. : 1.280 Min. :1.130 Min. :2.750 Min. : 1.280
## 1st Qu.: 2.550 1st Qu.:1.730 1st Qu.:3.188 1st Qu.: 2.550
## Median : 3.500 Median :2.200 Median :3.400 Median : 3.450
## Mean : 4.438 Mean :2.603 Mean :3.770 Mean : 4.378
## 3rd Qu.: 5.250 3rd Qu.:2.913 3rd Qu.:4.000 3rd Qu.: 5.000
## Max. :20.000 Max. :9.900 Max. :8.800 Max. :19.500
##
## PSH PSD PSA WHH
## Min. : 1.120 Min. :2.780 Min. : 1.290 Min. : 1.110
## 1st Qu.: 1.720 1st Qu.:3.230 1st Qu.: 2.600 1st Qu.: 1.700
## Median : 2.260 Median :3.515 Median : 3.520 Median : 2.225
## Mean : 2.650 Mean :3.894 Mean : 4.673 Mean : 2.616
## 3rd Qu.: 2.958 3rd Qu.:4.088 3rd Qu.: 5.230 3rd Qu.: 2.900
## Max. :10.020 Max. :9.950 Max. :25.500 Max. :10.000
## NA's :2 NA's :2 NA's :2
## WHD WHA VCH VCD
## Min. :2.800 Min. : 1.270 Min. : 1.100 Min. :2.800
## 1st Qu.:3.200 1st Qu.: 2.550 1st Qu.: 1.700 1st Qu.:3.200
## Median :3.400 Median : 3.450 Median : 2.200 Median :3.500
## Mean :3.802 Mean : 4.623 Mean : 2.582 Mean :3.831
## 3rd Qu.:4.000 3rd Qu.: 5.250 3rd Qu.: 2.885 3rd Qu.:4.025
## Max. :9.000 Max. :26.000 Max. :10.500 Max. :9.500
##
## VCA MaxH MaxD MaxA
## Min. : 1.250 Min. : 1.160 Min. : 2.900 Min. : 1.320
## 1st Qu.: 2.500 1st Qu.: 1.778 1st Qu.: 3.340 1st Qu.: 2.678
## Median : 3.400 Median : 2.310 Median : 3.600 Median : 3.625
## Mean : 4.453 Mean : 2.757 Mean : 4.019 Mean : 4.951
## 3rd Qu.: 5.000 3rd Qu.: 3.055 3rd Qu.: 4.202 3rd Qu.: 5.500
## Max. :26.000 Max. :11.000 Max. :10.500 Max. :31.000
##
## AvgH AvgD AvgA B365.2.5
## Min. :1.120 Min. :2.780 Min. : 1.280 Min. :1.280
## 1st Qu.:1.718 1st Qu.:3.210 1st Qu.: 2.550 1st Qu.:1.800
## Median :2.220 Median :3.435 Median : 3.455 Median :2.100
## Mean :2.608 Mean :3.813 Mean : 4.483 Mean :2.108
## 3rd Qu.:2.917 3rd Qu.:4.022 3rd Qu.: 5.093 3rd Qu.:2.500
## Max. :9.910 Max. :9.160 Max. :21.610 Max. :3.400
##
## B365.2.5.1 P.2.5 P.2.5.1 Max.2.5
## Min. :1.330 Min. :1.310 Min. :1.370 Min. :1.310
## 1st Qu.:1.530 1st Qu.:1.810 1st Qu.:1.570 1st Qu.:1.850
## Median :1.720 Median :2.145 Median :1.770 Median :2.175
## Mean :1.867 Mean :2.162 Mean :1.912 Mean :2.196
## 3rd Qu.:2.000 3rd Qu.:2.520 3rd Qu.:2.098 3rd Qu.:2.553
## Max. :3.750 Max. :3.340 Max. :3.640 Max. :3.400
## NA's :2 NA's :2
## Max.2.5.1 Avg.2.5 Avg.2.5.1 AHh
## Min. :1.380 Min. :1.260 Min. :1.350 Min. :-2.5000
## 1st Qu.:1.610 1st Qu.:1.780 1st Qu.:1.560 1st Qu.:-0.7500
## Median :1.820 Median :2.080 Median :1.750 Median :-0.2500
## Mean :1.950 Mean :2.099 Mean :1.869 Mean :-0.3289
## 3rd Qu.:2.132 3rd Qu.:2.440 3rd Qu.:2.040 3rd Qu.: 0.0000
## Max. :3.950 Max. :3.160 Max. :3.680 Max. : 1.7500
##
## B365AHH B365AHA PAHH PAHA
## Min. :1.670 Min. :1.650 Min. :1.750 Min. :1.680
## 1st Qu.:1.900 1st Qu.:1.890 1st Qu.:1.890 1st Qu.:1.880
## Median :1.970 Median :1.960 Median :1.970 Median :1.950
## Mean :1.963 Mean :1.954 Mean :1.966 Mean :1.954
## 3rd Qu.:2.040 3rd Qu.:2.030 3rd Qu.:2.040 3rd Qu.:2.030
## Max. :2.200 Max. :2.160 Max. :2.310 Max. :2.200
## NA's :10 NA's :10 NA's :2 NA's :2
## MaxAHH MaxAHA AvgAHH AvgAHA
## Min. :1.800 Min. :1.710 Min. :1.740 Min. :1.670
## 1st Qu.:1.920 1st Qu.:1.910 1st Qu.:1.870 1st Qu.:1.860
## Median :1.990 Median :1.980 Median :1.940 Median :1.930
## Mean :1.995 Mean :1.988 Mean :1.939 Mean :1.932
## 3rd Qu.:2.070 3rd Qu.:2.060 3rd Qu.:2.010 3rd Qu.:2.000
## Max. :2.330 Max. :2.250 Max. :2.270 Max. :2.170
##
## B365CH B365CD B365CA BWCH
## Min. : 1.100 Min. : 2.700 Min. : 1.250 Min. :1.100
## 1st Qu.: 1.700 1st Qu.: 3.200 1st Qu.: 2.600 1st Qu.:1.715
## Median : 2.150 Median : 3.400 Median : 3.550 Median :2.200
## Mean : 2.598 Mean : 3.857 Mean : 4.628 Mean :2.603
## 3rd Qu.: 2.870 3rd Qu.: 4.000 3rd Qu.: 5.250 3rd Qu.:2.900
## Max. :11.000 Max. :10.000 Max. :26.000 Max. :9.750
##
## BWCD BWCA IWCH IWCD
## Min. : 2.750 Min. : 1.28 Min. : 1.120 Min. :2.700
## 1st Qu.: 3.200 1st Qu.: 2.60 1st Qu.: 1.730 1st Qu.:3.150
## Median : 3.400 Median : 3.50 Median : 2.225 Median :3.400
## Mean : 3.817 Mean : 4.55 Mean : 2.609 Mean :3.747
## 3rd Qu.: 4.000 3rd Qu.: 5.25 3rd Qu.: 2.900 3rd Qu.:4.000
## Max. :10.000 Max. :23.00 Max. :11.000 Max. :9.000
##
## IWCA PSCH PSCD PSCA
## Min. : 1.250 Min. : 1.100 Min. : 2.710 Min. : 1.270
## 1st Qu.: 2.600 1st Qu.: 1.720 1st Qu.: 3.188 1st Qu.: 2.688
## Median : 3.500 Median : 2.275 Median : 3.480 Median : 3.640
## Mean : 4.368 Mean : 2.672 Mean : 3.900 Mean : 4.873
## 3rd Qu.: 5.100 3rd Qu.: 2.975 3rd Qu.: 4.062 3rd Qu.: 5.440
## Max. :20.000 Max. :10.930 Max. :11.520 Max. :28.530
##
## WHCH WHCD WHCA VCCH
## Min. : 1.080 Min. : 2.620 Min. : 1.250 Min. : 1.080
## 1st Qu.: 1.700 1st Qu.: 3.200 1st Qu.: 2.600 1st Qu.: 1.722
## Median : 2.225 Median : 3.400 Median : 3.600 Median : 2.225
## Mean : 2.647 Mean : 3.827 Mean : 4.793 Mean : 2.600
## 3rd Qu.: 2.900 3rd Qu.: 4.000 3rd Qu.: 5.250 3rd Qu.: 2.880
## Max. :11.000 Max. :11.000 Max. :26.000 Max. :10.500
##
## VCCD VCCA MaxCH MaxCD
## Min. : 2.750 Min. : 1.250 Min. : 1.130 Min. : 2.860
## 1st Qu.: 3.200 1st Qu.: 2.600 1st Qu.: 1.788 1st Qu.: 3.320
## Median : 3.450 Median : 3.400 Median : 2.355 Median : 3.610
## Mean : 3.845 Mean : 4.549 Mean : 2.836 Mean : 4.062
## 3rd Qu.: 4.000 3rd Qu.: 5.050 3rd Qu.: 3.105 3rd Qu.: 4.242
## Max. :10.500 Max. :26.000 Max. :13.000 Max. :12.400
##
## MaxCA AvgCH AvgCD AvgCA
## Min. : 1.320 Min. : 1.100 Min. : 2.710 Min. : 1.280
## 1st Qu.: 2.743 1st Qu.: 1.710 1st Qu.: 3.167 1st Qu.: 2.618
## Median : 3.870 Median : 2.235 Median : 3.430 Median : 3.545
## Mean : 5.215 Mean : 2.625 Mean : 3.824 Mean : 4.630
## 3rd Qu.: 5.750 3rd Qu.: 2.908 3rd Qu.: 4.032 3rd Qu.: 5.282
## Max. :31.370 Max. :10.390 Max. :10.410 Max. :24.600
##
## B365C.2.5 B365C.2.5.1 PC.2.5 PC.2.5.1 MaxC.2.5
## Min. :1.220 Min. :1.30 Min. :1.220 Min. :1.320 Min. :1.260
## 1st Qu.:1.720 1st Qu.:1.53 1st Qu.:1.795 1st Qu.:1.570 1st Qu.:1.857
## Median :2.100 Median :1.72 Median :2.125 Median :1.790 Median :2.190
## Mean :2.142 Mean :1.87 Mean :2.188 Mean :1.922 Mean :2.241
## 3rd Qu.:2.500 3rd Qu.:2.10 3rd Qu.:2.530 3rd Qu.:2.110 3rd Qu.:2.560
## Max. :3.500 Max. :4.33 Max. :3.720 Max. :4.520 Max. :3.720
##
## MaxC.2.5.1 AvgC.2.5 AvgC.2.5.1 AHCh
## Min. :1.330 Min. :1.220 Min. :1.290 Min. :-2.7500
## 1st Qu.:1.627 1st Qu.:1.760 1st Qu.:1.550 1st Qu.:-0.7500
## Median :1.840 Median :2.080 Median :1.750 Median :-0.2500
## Mean :1.997 Mean :2.118 Mean :1.878 Mean :-0.3329
## 3rd Qu.:2.223 3rd Qu.:2.440 3rd Qu.:2.062 3rd Qu.: 0.0000
## Max. :4.610 Max. :3.520 Max. :4.130 Max. : 1.7500
##
## B365CAHH B365CAHA PCAHH PCAHA
## Min. :1.700 Min. :1.670 Min. :1.750 Min. :1.750
## 1st Qu.:1.880 1st Qu.:1.880 1st Qu.:1.880 1st Qu.:1.880
## Median :1.960 Median :1.960 Median :1.960 Median :1.960
## Mean :1.959 Mean :1.956 Mean :1.962 Mean :1.959
## 3rd Qu.:2.040 3rd Qu.:2.040 3rd Qu.:2.040 3rd Qu.:2.040
## Max. :2.160 Max. :2.160 Max. :2.200 Max. :2.210
##
## MaxCAHH MaxCAHA AvgCAHH AvgCAHA
## Min. :1.780 Min. :1.800 Min. :1.72 Min. :1.750
## 1st Qu.:1.940 1st Qu.:1.930 1st Qu.:1.86 1st Qu.:1.860
## Median :2.020 Median :2.020 Median :1.93 Median :1.940
## Mean :2.021 Mean :2.016 Mean :1.94 Mean :1.938
## 3rd Qu.:2.100 3rd Qu.:2.100 3rd Qu.:2.02 3rd Qu.:2.010
## Max. :2.260 Max. :2.270 Max. :2.15 Max. :2.180
## Ahora seleccionaremos Unicamente las columnas Date, HomeTeam, AwayTeam, FTHG, FTAG y FTR en cada uno de los data frames.
lista <- lapply(lista, select, Date, HomeTeam, AwayTeam, FTHG, FTAG, FTR)Con las funciones lapply y str observaremos la estrucura de nuestros nuevos data frames
lapply(lista, str)## 'data.frame': 380 obs. of 6 variables:
## $ Date : chr "18/08/17" "18/08/17" "19/08/17" "19/08/17" ...
## $ HomeTeam: chr "Leganes" "Valencia" "Celta" "Girona" ...
## $ AwayTeam: chr "Alaves" "Las Palmas" "Sociedad" "Ath Madrid" ...
## $ FTHG : int 1 1 2 2 1 0 2 0 1 0 ...
## $ FTAG : int 0 0 3 2 1 0 0 3 0 1 ...
## $ FTR : chr "H" "H" "A" "D" ...
## 'data.frame': 380 obs. of 6 variables:
## $ Date : chr "17/08/2018" "17/08/2018" "18/08/2018" "18/08/2018" ...
## $ HomeTeam: chr "Betis" "Girona" "Barcelona" "Celta" ...
## $ AwayTeam: chr "Levante" "Valladolid" "Alaves" "Espanol" ...
## $ FTHG : int 0 0 3 1 1 1 2 1 2 1 ...
## $ FTAG : int 3 0 0 1 2 2 0 4 1 1 ...
## $ FTR : chr "A" "D" "H" "D" ...
## 'data.frame': 380 obs. of 6 variables:
## $ Date : chr "16/08/2019" "17/08/2019" "17/08/2019" "17/08/2019" ...
## $ HomeTeam: chr "Ath Bilbao" "Celta" "Valencia" "Mallorca" ...
## $ AwayTeam: chr "Barcelona" "Real Madrid" "Sociedad" "Eibar" ...
## $ FTHG : int 1 1 1 2 0 4 1 0 1 1 ...
## $ FTAG : int 0 3 1 1 1 4 0 2 2 0 ...
## $ FTR : chr "H" "A" "D" "H" ...## [[1]]
## NULL
##
## [[2]]
## NULL
##
## [[3]]
## NULLArreglamos las columnas Date para que R reconozca los elementos como fechas, esto lo hacemos con las funciones mutate (paquete dplyr) y as.Date.
lista<-lapply(lista,mutate,Date = as.Date(Date, "%d/%m/%y"))Verificamos que nuestros cambios se hayan llevado a cabo
lapply(lista, str)## 'data.frame': 380 obs. of 6 variables:
## $ Date : Date, format: "2017-08-18" "2017-08-18" ...
## $ HomeTeam: chr "Leganes" "Valencia" "Celta" "Girona" ...
## $ AwayTeam: chr "Alaves" "Las Palmas" "Sociedad" "Ath Madrid" ...
## $ FTHG : int 1 1 2 2 1 0 2 0 1 0 ...
## $ FTAG : int 0 0 3 2 1 0 0 3 0 1 ...
## $ FTR : chr "H" "H" "A" "D" ...
## 'data.frame': 380 obs. of 6 variables:
## $ Date : Date, format: "2020-08-17" "2020-08-17" ...
## $ HomeTeam: chr "Betis" "Girona" "Barcelona" "Celta" ...
## $ AwayTeam: chr "Levante" "Valladolid" "Alaves" "Espanol" ...
## $ FTHG : int 0 0 3 1 1 1 2 1 2 1 ...
## $ FTAG : int 3 0 0 1 2 2 0 4 1 1 ...
## $ FTR : chr "A" "D" "H" "D" ...
## 'data.frame': 380 obs. of 6 variables:
## $ Date : Date, format: "2020-08-16" "2020-08-17" ...
## $ HomeTeam: chr "Ath Bilbao" "Celta" "Valencia" "Mallorca" ...
## $ AwayTeam: chr "Barcelona" "Real Madrid" "Sociedad" "Eibar" ...
## $ FTHG : int 1 1 1 2 0 4 1 0 1 1 ...
## $ FTAG : int 0 3 1 1 1 4 0 2 2 0 ...
## $ FTR : chr "H" "A" "D" "H" ...## [[1]]
## NULL
##
## [[2]]
## NULL
##
## [[3]]
## NULLFinalmente, con ayuda de las funciones rbind y do.call combinamos los data frames contenidos en nlista como un único data frame
data <- do.call(rbind, lista)
dim(data)## [1] 1140 6Goles anotados por los equipos que jugaron en casa
FTHG <- data$FTHG Goles anotados por los equipos que jugaron como visitante
FTAG<-data$FTAG
View(FTAG)La probabilidad (marginal) de que el equipo que juega en casa anote x goles (x = 0, 1, 2, …)
(pgol_casa<-(table(FTHG)/length(FTHG)))## FTHG
## 0 1 2 3 4 5
## 0.232456140 0.327192982 0.266666667 0.112280702 0.035087719 0.019298246
## 6 7 8
## 0.005263158 0.000877193 0.000877193La probabilidad (marginal) de que el equipo que juega como visitante anote y goles (y = 0, 1, 2, …)
(pgol_vis<-(table(FTAG)/length(FTAG)))## FTAG
## 0 1 2 3 4 5
## 0.351754386 0.340350877 0.212280702 0.054385965 0.028947368 0.009649123
## 6
## 0.002631579La probabilidad (conjunta) de que el equipo que juega en casa anote x goles y el equipo que juega como visitante anote y goles (x = 0, 1, 2, …, y = 0, 1, 2, …)
(pc_gol<-(table(FTHG,FTAG)/dim(data)[1]))## FTAG
## FTHG 0 1 2 3 4 5
## 0 0.078070175 0.080701754 0.045614035 0.018421053 0.005263158 0.004385965
## 1 0.115789474 0.114912281 0.068421053 0.017543860 0.008771930 0.001754386
## 2 0.087719298 0.093859649 0.061403509 0.011403509 0.008771930 0.001754386
## 3 0.044736842 0.032456140 0.024561404 0.006140351 0.001754386 0.001754386
## 4 0.014035088 0.010526316 0.007017544 0.000000000 0.003508772 0.000000000
## 5 0.008771930 0.005263158 0.004385965 0.000000000 0.000877193 0.000000000
## 6 0.002631579 0.001754386 0.000000000 0.000877193 0.000000000 0.000000000
## 7 0.000000000 0.000877193 0.000000000 0.000000000 0.000000000 0.000000000
## 8 0.000000000 0.000000000 0.000877193 0.000000000 0.000000000 0.000000000
## FTAG
## FTHG 6
## 0 0.000000000
## 1 0.000000000
## 2 0.001754386
## 3 0.000877193
## 4 0.000000000
## 5 0.000000000
## 6 0.000000000
## 7 0.000000000
## 8 0.000000000pgol_casa<- as.data.frame(pgol_casa)
str(pgol_casa)## 'data.frame': 9 obs. of 2 variables:
## $ FTHG: Factor w/ 9 levels "0","1","2","3",..: 1 2 3 4 5 6 7 8 9
## $ Freq: num 0.2325 0.3272 0.2667 0.1123 0.0351 ...(pgol_casa<- pgol_casa%>% rename(Goles = FTHG, Frecuencia = Freq))## Goles Frecuencia
## 1 0 0.232456140
## 2 1 0.327192982
## 3 2 0.266666667
## 4 3 0.112280702
## 5 4 0.035087719
## 6 5 0.019298246
## 7 6 0.005263158
## 8 7 0.000877193
## 9 8 0.000877193pgol_vis<- as.data.frame(pgol_vis)
str(pgol_vis)## 'data.frame': 7 obs. of 2 variables:
## $ FTAG: Factor w/ 7 levels "0","1","2","3",..: 1 2 3 4 5 6 7
## $ Freq: num 0.3518 0.3404 0.2123 0.0544 0.0289 ...(pgol_vis<- pgol_vis%>% rename(Goles = FTAG, Frecuencia = Freq))## Goles Frecuencia
## 1 0 0.351754386
## 2 1 0.340350877
## 3 2 0.212280702
## 4 3 0.054385965
## 5 4 0.028947368
## 6 5 0.009649123
## 7 6 0.002631579