HT  FT analysis.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "cfile=(\"/home/dark/Desktop/machine learning/season-1819_csv.csv\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### WHAT WE WILL DO\n",
    "We will try create the probability of a team winning a game if it was ahead at half time.\n",
    "\n",
    "We willl use the 2018 -2019 season to create this program."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [],
   "source": [
    "import pandas as pd\n",
    "import numpy as np\n",
    "import pylab as pl\n",
    "import matplotlib.pyplot as plt\n",
    "%matplotlib inline"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Div</th>\n",
       "      <th>Date</th>\n",
       "      <th>HomeTeam</th>\n",
       "      <th>AwayTeam</th>\n",
       "      <th>FTHG</th>\n",
       "      <th>FTAG</th>\n",
       "      <th>FTR</th>\n",
       "      <th>HTHG</th>\n",
       "      <th>HTAG</th>\n",
       "      <th>HTR</th>\n",
       "      <th>...</th>\n",
       "      <th>BbAv&lt;2.5</th>\n",
       "      <th>BbAH</th>\n",
       "      <th>BbAHh</th>\n",
       "      <th>BbMxAHH</th>\n",
       "      <th>BbAvAHH</th>\n",
       "      <th>BbMxAHA</th>\n",
       "      <th>BbAvAHA</th>\n",
       "      <th>PSCH</th>\n",
       "      <th>PSCD</th>\n",
       "      <th>PSCA</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>E0</td>\n",
       "      <td>10/08/2018</td>\n",
       "      <td>Man United</td>\n",
       "      <td>Leicester</td>\n",
       "      <td>2</td>\n",
       "      <td>1</td>\n",
       "      <td>H</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>H</td>\n",
       "      <td>...</td>\n",
       "      <td>1.79</td>\n",
       "      <td>17</td>\n",
       "      <td>-0.75</td>\n",
       "      <td>1.75</td>\n",
       "      <td>1.70</td>\n",
       "      <td>2.29</td>\n",
       "      <td>2.21</td>\n",
       "      <td>1.55</td>\n",
       "      <td>4.07</td>\n",
       "      <td>7.69</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>E0</td>\n",
       "      <td>11/08/2018</td>\n",
       "      <td>Bournemouth</td>\n",
       "      <td>Cardiff</td>\n",
       "      <td>2</td>\n",
       "      <td>0</td>\n",
       "      <td>H</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>H</td>\n",
       "      <td>...</td>\n",
       "      <td>1.83</td>\n",
       "      <td>20</td>\n",
       "      <td>-0.75</td>\n",
       "      <td>2.20</td>\n",
       "      <td>2.13</td>\n",
       "      <td>1.80</td>\n",
       "      <td>1.75</td>\n",
       "      <td>1.88</td>\n",
       "      <td>3.61</td>\n",
       "      <td>4.70</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>E0</td>\n",
       "      <td>11/08/2018</td>\n",
       "      <td>Fulham</td>\n",
       "      <td>Crystal Palace</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>A</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>A</td>\n",
       "      <td>...</td>\n",
       "      <td>1.87</td>\n",
       "      <td>22</td>\n",
       "      <td>-0.25</td>\n",
       "      <td>2.18</td>\n",
       "      <td>2.11</td>\n",
       "      <td>1.81</td>\n",
       "      <td>1.77</td>\n",
       "      <td>2.62</td>\n",
       "      <td>3.38</td>\n",
       "      <td>2.90</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>E0</td>\n",
       "      <td>11/08/2018</td>\n",
       "      <td>Huddersfield</td>\n",
       "      <td>Chelsea</td>\n",
       "      <td>0</td>\n",
       "      <td>3</td>\n",
       "      <td>A</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>A</td>\n",
       "      <td>...</td>\n",
       "      <td>1.84</td>\n",
       "      <td>23</td>\n",
       "      <td>1.00</td>\n",
       "      <td>1.84</td>\n",
       "      <td>1.80</td>\n",
       "      <td>2.13</td>\n",
       "      <td>2.06</td>\n",
       "      <td>7.24</td>\n",
       "      <td>3.95</td>\n",
       "      <td>1.58</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>E0</td>\n",
       "      <td>11/08/2018</td>\n",
       "      <td>Newcastle</td>\n",
       "      <td>Tottenham</td>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "      <td>A</td>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "      <td>A</td>\n",
       "      <td>...</td>\n",
       "      <td>1.81</td>\n",
       "      <td>20</td>\n",
       "      <td>0.25</td>\n",
       "      <td>2.20</td>\n",
       "      <td>2.12</td>\n",
       "      <td>1.80</td>\n",
       "      <td>1.76</td>\n",
       "      <td>4.74</td>\n",
       "      <td>3.53</td>\n",
       "      <td>1.89</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>5 rows × 62 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "  Div        Date      HomeTeam        AwayTeam  FTHG  FTAG FTR  HTHG  HTAG  \\\n",
       "0  E0  10/08/2018    Man United       Leicester     2     1   H     1     0   \n",
       "1  E0  11/08/2018   Bournemouth         Cardiff     2     0   H     1     0   \n",
       "2  E0  11/08/2018        Fulham  Crystal Palace     0     2   A     0     1   \n",
       "3  E0  11/08/2018  Huddersfield         Chelsea     0     3   A     0     2   \n",
       "4  E0  11/08/2018     Newcastle       Tottenham     1     2   A     1     2   \n",
       "\n",
       "  HTR  ... BbAv<2.5  BbAH  BbAHh  BbMxAHH  BbAvAHH  BbMxAHA  BbAvAHA  PSCH  \\\n",
       "0   H  ...     1.79    17  -0.75     1.75     1.70     2.29     2.21  1.55   \n",
       "1   H  ...     1.83    20  -0.75     2.20     2.13     1.80     1.75  1.88   \n",
       "2   A  ...     1.87    22  -0.25     2.18     2.11     1.81     1.77  2.62   \n",
       "3   A  ...     1.84    23   1.00     1.84     1.80     2.13     2.06  7.24   \n",
       "4   A  ...     1.81    20   0.25     2.20     2.12     1.80     1.76  4.74   \n",
       "\n",
       "   PSCD  PSCA  \n",
       "0  4.07  7.69  \n",
       "1  3.61  4.70  \n",
       "2  3.38  2.90  \n",
       "3  3.95  1.58  \n",
       "4  3.53  1.89  \n",
       "\n",
       "[5 rows x 62 columns]"
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df=pd.read_csv(cfile)\n",
    "\n",
    "df.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<bound method NDFrame.describe of     Div        Date      HomeTeam        AwayTeam  FTHG  FTAG FTR  HTHG  HTAG  \\\n",
       "0    E0  10/08/2018    Man United       Leicester     2     1   H     1     0   \n",
       "1    E0  11/08/2018   Bournemouth         Cardiff     2     0   H     1     0   \n",
       "2    E0  11/08/2018        Fulham  Crystal Palace     0     2   A     0     1   \n",
       "3    E0  11/08/2018  Huddersfield         Chelsea     0     3   A     0     2   \n",
       "4    E0  11/08/2018     Newcastle       Tottenham     1     2   A     1     2   \n",
       "..   ..         ...           ...             ...   ...   ...  ..   ...   ...   \n",
       "375  E0  12/05/2019     Liverpool          Wolves     2     0   H     1     0   \n",
       "376  E0  12/05/2019    Man United         Cardiff     0     2   A     0     1   \n",
       "377  E0  12/05/2019   Southampton    Huddersfield     1     1   D     1     0   \n",
       "378  E0  12/05/2019     Tottenham         Everton     2     2   D     1     0   \n",
       "379  E0  12/05/2019       Watford        West Ham     1     4   A     0     2   \n",
       "\n",
       "    HTR  ... BbAv<2.5  BbAH  BbAHh  BbMxAHH  BbAvAHH  BbMxAHA  BbAvAHA  PSCH  \\\n",
       "0     H  ...     1.79    17  -0.75     1.75     1.70     2.29     2.21  1.55   \n",
       "1     H  ...     1.83    20  -0.75     2.20     2.13     1.80     1.75  1.88   \n",
       "2     A  ...     1.87    22  -0.25     2.18     2.11     1.81     1.77  2.62   \n",
       "3     A  ...     1.84    23   1.00     1.84     1.80     2.13     2.06  7.24   \n",
       "4     A  ...     1.81    20   0.25     2.20     2.12     1.80     1.76  4.74   \n",
       "..   ..  ...      ...   ...    ...      ...      ...      ...      ...   ...   \n",
       "375   H  ...     2.31    22  -1.50     1.98     1.91     2.01     1.95  1.32   \n",
       "376   A  ...     2.95    21  -2.00     2.52     2.32     1.72     1.64  1.30   \n",
       "377   H  ...     2.29    22  -1.50     2.27     2.16     1.80     1.73  1.37   \n",
       "378   H  ...     2.07    19  -0.50     2.13     2.08     1.85     1.80  1.91   \n",
       "379   A  ...     2.44    19  -0.50     2.25     2.19     1.78     1.72  2.11   \n",
       "\n",
       "     PSCD  PSCA  \n",
       "0    4.07  7.69  \n",
       "1    3.61  4.70  \n",
       "2    3.38  2.90  \n",
       "3    3.95  1.58  \n",
       "4    3.53  1.89  \n",
       "..    ...   ...  \n",
       "375  5.89  9.48  \n",
       "376  6.06  9.71  \n",
       "377  5.36  8.49  \n",
       "378  3.81  4.15  \n",
       "379  3.86  3.41  \n",
       "\n",
       "[380 rows x 62 columns]>"
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.describe"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Above is a view of the data of each game played in the premier league\n",
    "We will now try to estract the games and their half time/ full time statiatcs"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "    }\n",
       "\n",
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       "    }\n",
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Date</th>\n",
       "      <th>HomeTeam</th>\n",
       "      <th>AwayTeam</th>\n",
       "      <th>HTHG</th>\n",
       "      <th>HTAG</th>\n",
       "      <th>FTAG</th>\n",
       "      <th>FTHG</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>10/08/2018</td>\n",
       "      <td>Man United</td>\n",
       "      <td>Leicester</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>11/08/2018</td>\n",
       "      <td>Bournemouth</td>\n",
       "      <td>Cardiff</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>11/08/2018</td>\n",
       "      <td>Fulham</td>\n",
       "      <td>Crystal Palace</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>11/08/2018</td>\n",
       "      <td>Huddersfield</td>\n",
       "      <td>Chelsea</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>3</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>11/08/2018</td>\n",
       "      <td>Newcastle</td>\n",
       "      <td>Tottenham</td>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "         Date      HomeTeam        AwayTeam  HTHG  HTAG  FTAG  FTHG\n",
       "0  10/08/2018    Man United       Leicester     1     0     1     2\n",
       "1  11/08/2018   Bournemouth         Cardiff     1     0     0     2\n",
       "2  11/08/2018        Fulham  Crystal Palace     0     1     2     0\n",
       "3  11/08/2018  Huddersfield         Chelsea     0     2     3     0\n",
       "4  11/08/2018     Newcastle       Tottenham     1     2     2     1"
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "dat=df[['Date','HomeTeam','AwayTeam','HTHG','HTAG','FTAG','FTHG']]\n",
    "dat.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# We will describe the meaning of HTHG, HTAG,FTAG,FTHG\n",
    "HTHG-Half Time Home Goals. \n",
    "\n",
    "HTAG- Half Time Away Goals.\n",
    "\n",
    "FTAG-Full Time Away Goals.\n",
    "\n",
    "FTHG-Full Time Home Goals."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
  
   ]
  }
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