cbbspraper.2.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {
    "scrolled": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<selenium.webdriver.remote.webelement.WebElement (session=\"9818bd51b8a0f5b899f5591cc40b45c7\", element=\"4ae50513-5672-4c7c-ba99-8dd699be1afe\")>\n",
      "<selenium.webdriver.remote.webelement.WebElement (session=\"9818bd51b8a0f5b899f5591cc40b45c7\", element=\"ffc7677b-3e7b-4b7d-93fc-16f06f6e2e6a\")>\n",
      "                              team\n",
      "0     21 Minnesota at\\n10 Michigan\n",
      "1             Michigan 78-73 (68%)\n",
      "2       8:30 pm\\n Big Ten Network \n",
      "3    Ann Arbor, MI\\nCrisler Center\n",
      "4                          72.6\\n1\n",
      "..                             ...\n",
      "198                        8:00 pm\n",
      "199   Houston, TX\\nSharp Gymnasium\n",
      "200                       13.0\\n29\n",
      "201                            \\n \n",
      "202                            \\n \n",
      "\n",
      "[203 rows x 1 columns]\n"
     ]
    }
   ],
   "source": [
    "\n",
    "import mechanicalsoup\n",
    "import requests, re\n",
    "import pandas as pd\n",
    "from bs4 import BeautifulSoup\n",
    "import numpy as np\n",
    "from selenium import webdriver\n",
    "from selenium.webdriver.common.by import By\n",
    "from selenium.webdriver.support.ui import WebDriverWait\n",
    "from selenium.webdriver.support import expected_conditions as EC\n",
    "from selenium.common.exceptions import TimeoutException\n",
    "\n",
    "driver = webdriver.Chrome(\"/opt/anaconda3/bin/chromedriver 2\") #path to webdriver\n",
    "driver.get('https://kenpom.com/index.php')\n",
    "\n",
    "\n",
    "driver.find_element_by_xpath('/html/body/div/div[1]/div[1]/div[1]/form')\n",
    "e = driver.find_element_by_xpath('/html/body/div/div[1]/div[1]/div[1]/form/input[1]')\n",
    "print(e)\n",
    "e.send_keys(\"username\") #kenpom username\n",
    "e = driver.find_element_by_xpath('/html/body/div/div[1]/div[1]/div[1]/form/input[2]')\n",
    "e.send_keys(\"password\")#kenpom password\n",
    "e = driver.find_element_by_xpath('/html/body/div/div[1]/div[1]/div[1]/form/input[3]')\n",
    "e.click()\n",
    "\n",
    "b = driver.find_element_by_xpath('/html/body/div/div[1]/div[1]/div[2]/nav/ul/li[2]/a')\n",
    "print(b)\n",
    "b.click()\n",
    "\n",
    "\n",
    "headers = {'User-Agent': 'Mozilla/5.0 (Macintosh; Intel Mac OS X 11_1) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/87.0.4280.88 Safari/537.36'}\n",
    "url = \"https://kenpom.com/fanmatch.php\"\n",
    "\n",
    "r=requests.get(url,headers=headers)\n",
    "soup = BeautifulSoup(r.content, \"html.parser\")\n",
    "list_category_elements = driver.find_element_by_xpath('/html/body/div/div[1]/div[3]/table') #finds table elements and prints as text\n",
    "links = list_category_elements.find_elements(By.TAG_NAME,\"td\")\n",
    "links_values=[]\n",
    "for i in range(len(links)):\n",
    "   \n",
    "    links_values.append(links[i].text)\n",
    "df=pd.DataFrame((links_values),columns=['team'])\n",
    "print(df)\n",
    "\n",
    "links_values=np.array(links_values)\n",
    "\n",
    "\n",
    "\n",
    "                           \n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "#creates kenpom df and names columns\n",
    "df2=pd.DataFrame(df.team.str.rsplit(' ',n=2,expand=True)) \n",
    "\n",
    "\n",
    "\n",
    "df3=df2.iloc[1::7,:2]\n",
    "df=df.iloc[0::7,:2]\n",
    "\n",
    "df3.columns=['team','score']\n",
    "df4=pd.DataFrame(df3.score.str.rsplit('-',n=2,expand=True))\n",
    "df4.columns=['score1','score2']\n",
    "\n",
    "Kenpom=pd.concat([df3['team'], df4.reindex(df3.index)], axis=1).iloc[0:100]\n",
    "\n",
    "\n",
    "\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {
    "scrolled": true
   },
   "outputs": [],
   "source": [
    "driver.get('https://haslametrics.com/ratings.php')\n",
    "list_category_elements = driver.find_element_by_xpath('/html/body/div/table/tbody/tr[5]/td/div[3]/div/div/table') #finds hasla table elements\n",
    "links = list_category_elements.find_elements(By.CLASS_NAME,\"scoreproj1\")\n",
    "links2= list_category_elements.find_elements(By.CLASS_NAME,\"scoreproj2\")\n",
    "links_values2=[]\n",
    "links2_values2=[]\n",
    "for i in range(len(links)):\n",
    "    \n",
    "     \n",
    "    links_values2.append(links[i].text)\n",
    "for i in range(len(links2)):\n",
    "    \n",
    "   \n",
    "    links2_values2.append(links2[i].text)\n",
    "\n",
    "\n",
    "dfh1=pd.DataFrame(links_values2)\n",
    "dfh2=pd.DataFrame(links2_values2)\n",
    "links_values2=np.array(links_values2)\n",
    "links2_values2=np.array(links2_values2)\n",
    "\n",
    "\n",
    "    "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {
    "scrolled": true
   },
   "outputs": [],
   "source": [
    "dfh4=pd.DataFrame((links_values2[0::2]),columns=['Home']) #creates hasla df\n",
    "dfh3=pd.DataFrame((links_values2[1::2]),columns=['HScore'])\n",
    "\n",
    "Hasla=pd.concat([dfh4, dfh3.reindex(dfh4.index)], axis=1).iloc[0:50]\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {
    "scrolled": true
   },
   "outputs": [],
   "source": [
    "dfh5=pd.DataFrame((links2_values2[0::2]),columns=['Away'])\n",
    "dfh6=pd.DataFrame((links2_values2[1::2]),columns=['Ascore'])\n",
    "\n",
    "Hasla2=pd.concat([dfh5, dfh6.reindex(dfh5.index)], axis=1).iloc[0:50]\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [],
   "source": [
    "Halsa=Hasla"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [],
   "source": [
    "Hasla2=Hasla2"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {
    "scrolled": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "                          team1\n",
      "0                     Minnesota\n",
      "1                      Michigan\n",
      "2    Michigan -6.3\\n79-72 (72%)\n",
      "3                              \n",
      "4                    Seton Hall\n",
      "5                     Creighton\n",
      "6   Creighton -5.6\\n77-71 (70%)\n",
      "7                              \n",
      "8                      Arkansas\n",
      "9                     Tennessee\n",
      "10  Tennessee -7.2\\n73-66 (77%)\n",
      "11                             \n",
      "12                 Rhode Island\n",
      "13                     Richmond\n",
      "14   Richmond -3.7\\n75-71 (64%)\n",
      "15                             \n",
      "16                     Oklahoma\n",
      "17                       Baylor\n",
      "18    Baylor -12.6\\n83-70 (87%)\n",
      "19                             \n"
     ]
    }
   ],
   "source": [
    "driver.get('https://barttorvik.com/schedule.php')\n",
    "list_category_elements = driver.find_element_by_xpath('/html/body/div/div/p[4]/table/tbody') #finds torvik table elements\n",
    "links = list_category_elements.find_elements(By.TAG_NAME,'a')\n",
    "links_values3=[]\n",
    "for i in range(len(links)):\n",
    "    \n",
    "    links_values3.append(links[i].text)\n",
    "    \n",
    "    \n",
    "\n",
    "dft=pd.DataFrame(links_values3)\n",
    "\n",
    "dft=pd.DataFrame(np.array((links_values3)),\n",
    "                         columns=['team1'])\n",
    "\n",
    "\n",
    "links_values3=np.array(links_values3)\n",
    "\n",
    "print(dft.iloc[0:20])\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [],
   "source": [
    "#creates torvik df\n",
    "dft2=dft.team1.str.split(expand=True)\n",
    "\n",
    "dft2=pd.DataFrame(dft.team1.str.split('\\n',1).tolist(), \n",
    "                         columns = ['Teams','PredictedScore'])\n",
    "\n",
    "Tovrik=dft2.iloc[2::4]\n",
    "Tovrik.columns=['score1','score2']\n",
    "\n",
    "\n",
    "\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [],
   "source": [
    "TovrikF=pd.DataFrame(Tovrik.score2.str.rsplit('-',n=2,expand=True))\n",
    "TovrikF.columns=['score1','score2']\n",
    "\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [],
   "source": [
    "TovrikFinal2=pd.DataFrame(TovrikF.score2.str.rsplit('(',n=2,expand=True))\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [],
   "source": [
    "Tovrikcombo=pd.concat([Tovrik, TovrikF.reindex(Tovrik.index)], axis=1).iloc[0:50]\n",
    "TovrikFinal2=pd.DataFrame(TovrikF.score2.str.rsplit('(',n=2,expand=True))\n",
    "Tovrikx=pd.concat([Tovrikcombo, TovrikFinal2.reindex(Tovrikcombo.index)], axis=1).iloc[0:50]\n",
    "Tovrikx.columns=['Team','Pred','Score1','-','Score2','-']\n",
    "\n",
    "\n",
    "\n",
    "TovFinal=Tovrikx\n",
    "TovFinal.drop(TovFinal.columns[[1,3,5]], axis=1, inplace=True)\n",
    "\n",
    "\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<selenium.webdriver.remote.webelement.WebElement (session=\"9818bd51b8a0f5b899f5591cc40b45c7\", element=\"3f2d76db-dfbb-4847-a593-7b59c6592991\")>\n"
     ]
    }
   ],
   "source": [
    "\n",
    "driver.get('https://il.sportsbook.fanduel.com/sports/navigation/11086.3/11087.3') #finds fanduel table elements \n",
    "b=driver.find_element_by_class_name(\"btn.tab.active\") #sends fanduel to 'all games' tab - may need tweaking if featured games tab present\n",
    "print(b)\n",
    "b.click()\n",
    "headers = {'User-Agent': 'Mozilla/5.0 (Macintosh; Intel Mac OS X 11_1) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/87.0.4280.88 Safari/537.36'}\n",
    "\n",
    "\n",
    "\n",
    "url = \"https://il.sportsbook.fanduel.com/sports/navigation/11086.3/11087.3\"\n",
    "\n",
    "r = requests.get(url, headers=headers)\n",
    "soup = BeautifulSoup(r.content, \"html.parser\")\n",
    "list_category_elements = driver.find_element_by_xpath('/html/body/div[1]/div/div/div[6]/main/div/div/div/div/div[1]/div[3]/div[2]/div/div/div/div[3]/div/div/div/div/div[2]')\n",
    "linksspread = list_category_elements.find_elements(By.CLASS_NAME,\"event\")\n",
    "\n",
    "links_valuesFD=[]\n",
    "for i in range(len(linksspread)):\n",
    "   \n",
    "    links_valuesFD.append(linksspread[i].text)\n",
    "\n",
    "dffd=pd.DataFrame((links_valuesFD[0::]),columns=['Fanduel']) #fanduel df\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {
    "scrolled": true
   },
   "outputs": [],
   "source": [
    "dffd=pd.DataFrame((links_valuesFD),columns=['Fanduel'])\n",
    "dffd.set_index('Fanduel')\n",
    "\n",
    "dffd3=pd.DataFrame(dffd.Fanduel.str.rsplit('\\n',n=25,expand=True))\n",
    "\n",
    "Fanduel=dffd3\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<AxesSubplot:>"
      ]
     },
     "execution_count": 15,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "import matplotlib.pyplot as plt\n",
    "Fanduel[2]=pd.to_numeric(Fanduel[2])\n",
    "Fanduel[2]=np.abs(Fanduel[2])\n",
    "Fanduel[9]=pd.to_numeric(Fanduel[9])\n",
    "\n",
    "plt.figure();\n",
    "\n",
    "Fanduel[2].plot(kind='bar') #fanduel bar graph of spreads by column"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>0</th>\n",
       "      <th>1</th>\n",
       "      <th>2</th>\n",
       "      <th>3</th>\n",
       "      <th>4</th>\n",
       "      <th>5</th>\n",
       "      <th>6</th>\n",
       "      <th>7</th>\n",
       "      <th>8</th>\n",
       "      <th>9</th>\n",
       "      <th>10</th>\n",
       "      <th>11</th>\n",
       "      <th>12</th>\n",
       "      <th>13</th>\n",
       "      <th>14</th>\n",
       "      <th>15</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>St Josephs</td>\n",
       "      <td>St. Bonaventure</td>\n",
       "      <td>12.5</td>\n",
       "      <td>-115</td>\n",
       "      <td>-12.5</td>\n",
       "      <td>-105</td>\n",
       "      <td>+700</td>\n",
       "      <td>-1100</td>\n",
       "      <td>O</td>\n",
       "      <td>152.5</td>\n",
       "      <td>-108</td>\n",
       "      <td>U</td>\n",
       "      <td>152.5</td>\n",
       "      <td>-112</td>\n",
       "      <td>Today 3:00PM</td>\n",
       "      <td>MORE WAGERS</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Tulsa</td>\n",
       "      <td>South Florida</td>\n",
       "      <td>1.5</td>\n",
       "      <td>-120</td>\n",
       "      <td>-1.5</td>\n",
       "      <td>-102</td>\n",
       "      <td>-102</td>\n",
       "      <td>-116</td>\n",
       "      <td>O</td>\n",
       "      <td>127.5</td>\n",
       "      <td>-106</td>\n",
       "      <td>U</td>\n",
       "      <td>127.5</td>\n",
       "      <td>-114</td>\n",
       "      <td>Today 3:00PM</td>\n",
       "      <td>MORE WAGERS</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>Pittsburgh</td>\n",
       "      <td>Syracuse</td>\n",
       "      <td>11.5</td>\n",
       "      <td>-112</td>\n",
       "      <td>-11.5</td>\n",
       "      <td>-108</td>\n",
       "      <td>+590</td>\n",
       "      <td>-850</td>\n",
       "      <td>O</td>\n",
       "      <td>139.5</td>\n",
       "      <td>-110</td>\n",
       "      <td>U</td>\n",
       "      <td>139.5</td>\n",
       "      <td>-110</td>\n",
       "      <td>Today 3:30PM</td>\n",
       "      <td>MORE WAGERS</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>Massachusetts</td>\n",
       "      <td>George Washington</td>\n",
       "      <td>5.5</td>\n",
       "      <td>-104</td>\n",
       "      <td>+5.5</td>\n",
       "      <td>-118</td>\n",
       "      <td>-230</td>\n",
       "      <td>+190</td>\n",
       "      <td>O</td>\n",
       "      <td>152.5</td>\n",
       "      <td>-106</td>\n",
       "      <td>U</td>\n",
       "      <td>152.5</td>\n",
       "      <td>-114</td>\n",
       "      <td>Today 5:00PM</td>\n",
       "      <td>MORE WAGERS</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>Rhode Island</td>\n",
       "      <td>Richmond</td>\n",
       "      <td>3.5</td>\n",
       "      <td>-104</td>\n",
       "      <td>-3.5</td>\n",
       "      <td>-118</td>\n",
       "      <td>+156</td>\n",
       "      <td>-186</td>\n",
       "      <td>O</td>\n",
       "      <td>144.5</td>\n",
       "      <td>-105</td>\n",
       "      <td>U</td>\n",
       "      <td>144.5</td>\n",
       "      <td>-115</td>\n",
       "      <td>Today 5:00PM</td>\n",
       "      <td>MORE WAGERS</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>Virginia Tech</td>\n",
       "      <td>Louisville</td>\n",
       "      <td>4.5</td>\n",
       "      <td>-114</td>\n",
       "      <td>-4.5</td>\n",
       "      <td>-106</td>\n",
       "      <td>+166</td>\n",
       "      <td>-198</td>\n",
       "      <td>O</td>\n",
       "      <td>131.5</td>\n",
       "      <td>-110</td>\n",
       "      <td>U</td>\n",
       "      <td>131.5</td>\n",
       "      <td>-110</td>\n",
       "      <td>Today 5:30PM</td>\n",
       "      <td>MORE WAGERS</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>Arkansas</td>\n",
       "      <td>Tennessee</td>\n",
       "      <td>8.5</td>\n",
       "      <td>-118</td>\n",
       "      <td>-8.5</td>\n",
       "      <td>-104</td>\n",
       "      <td>+310</td>\n",
       "      <td>-400</td>\n",
       "      <td>O</td>\n",
       "      <td>141.5</td>\n",
       "      <td>-110</td>\n",
       "      <td>U</td>\n",
       "      <td>141.5</td>\n",
       "      <td>-110</td>\n",
       "      <td>Today 6:00PM</td>\n",
       "      <td>MORE WAGERS</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>Georgetown</td>\n",
       "      <td>Butler</td>\n",
       "      <td>4.5</td>\n",
       "      <td>-112</td>\n",
       "      <td>-4.5</td>\n",
       "      <td>-108</td>\n",
       "      <td>+168</td>\n",
       "      <td>-200</td>\n",
       "      <td>O</td>\n",
       "      <td>140.5</td>\n",
       "      <td>-114</td>\n",
       "      <td>U</td>\n",
       "      <td>140.5</td>\n",
       "      <td>-105</td>\n",
       "      <td>Today 6:00PM</td>\n",
       "      <td>MORE WAGERS</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>Georgia</td>\n",
       "      <td>LSU</td>\n",
       "      <td>9.5</td>\n",
       "      <td>-104</td>\n",
       "      <td>-9.5</td>\n",
       "      <td>-118</td>\n",
       "      <td>+440</td>\n",
       "      <td>-590</td>\n",
       "      <td>O</td>\n",
       "      <td>155.5</td>\n",
       "      <td>-114</td>\n",
       "      <td>U</td>\n",
       "      <td>155.5</td>\n",
       "      <td>-106</td>\n",
       "      <td>Today 6:00PM</td>\n",
       "      <td>MORE WAGERS</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>Samford</td>\n",
       "      <td>Chattanooga</td>\n",
       "      <td>6.5</td>\n",
       "      <td>-104</td>\n",
       "      <td>-6.5</td>\n",
       "      <td>-118</td>\n",
       "      <td>+260</td>\n",
       "      <td>-320</td>\n",
       "      <td>O</td>\n",
       "      <td>154.5</td>\n",
       "      <td>-108</td>\n",
       "      <td>U</td>\n",
       "      <td>154.5</td>\n",
       "      <td>-112</td>\n",
       "      <td>Today 6:00PM</td>\n",
       "      <td>MORE WAGERS</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>VCU</td>\n",
       "      <td>George Mason</td>\n",
       "      <td>6.5</td>\n",
       "      <td>-112</td>\n",
       "      <td>+6.5</td>\n",
       "      <td>-108</td>\n",
       "      <td>-300</td>\n",
       "      <td>+245</td>\n",
       "      <td>O</td>\n",
       "      <td>136.5</td>\n",
       "      <td>-110</td>\n",
       "      <td>U</td>\n",
       "      <td>136.5</td>\n",
       "      <td>-110</td>\n",
       "      <td>Today 6:00PM</td>\n",
       "      <td>MORE WAGERS</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>Abilene Christian</td>\n",
       "      <td>Houston Baptist</td>\n",
       "      <td>15.5</td>\n",
       "      <td>-108</td>\n",
       "      <td>+15.5</td>\n",
       "      <td>-112</td>\n",
       "      <td>-2500</td>\n",
       "      <td>+1200</td>\n",
       "      <td>O</td>\n",
       "      <td>148.5</td>\n",
       "      <td>-110</td>\n",
       "      <td>U</td>\n",
       "      <td>148.5</td>\n",
       "      <td>-110</td>\n",
       "      <td>Today 7:00PM</td>\n",
       "      <td>MORE WAGERS</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>Lamar</td>\n",
       "      <td>Nicholls</td>\n",
       "      <td>7.5</td>\n",
       "      <td>-108</td>\n",
       "      <td>-7.5</td>\n",
       "      <td>-112</td>\n",
       "      <td>+290</td>\n",
       "      <td>-360</td>\n",
       "      <td>O</td>\n",
       "      <td>143.5</td>\n",
       "      <td>-115</td>\n",
       "      <td>U</td>\n",
       "      <td>143.5</td>\n",
       "      <td>-105</td>\n",
       "      <td>Today 7:00PM</td>\n",
       "      <td>MORE WAGERS</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13</th>\n",
       "      <td>New Orleans</td>\n",
       "      <td>Central Arkansas</td>\n",
       "      <td>7.5</td>\n",
       "      <td>-110</td>\n",
       "      <td>-7.5</td>\n",
       "      <td>-110</td>\n",
       "      <td>+280</td>\n",
       "      <td>-350</td>\n",
       "      <td>O</td>\n",
       "      <td>150.5</td>\n",
       "      <td>-114</td>\n",
       "      <td>U</td>\n",
       "      <td>150.5</td>\n",
       "      <td>-106</td>\n",
       "      <td>Today 7:00PM</td>\n",
       "      <td>MORE WAGERS</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14</th>\n",
       "      <td>Sam Houston State</td>\n",
       "      <td>SE Louisiana</td>\n",
       "      <td>4.5</td>\n",
       "      <td>-105</td>\n",
       "      <td>+4.5</td>\n",
       "      <td>-115</td>\n",
       "      <td>-194</td>\n",
       "      <td>+162</td>\n",
       "      <td>O</td>\n",
       "      <td>147.5</td>\n",
       "      <td>-105</td>\n",
       "      <td>U</td>\n",
       "      <td>147.5</td>\n",
       "      <td>-115</td>\n",
       "      <td>Today 7:00PM</td>\n",
       "      <td>MORE WAGERS</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15</th>\n",
       "      <td>St Johns</td>\n",
       "      <td>Xavier</td>\n",
       "      <td>7.5</td>\n",
       "      <td>-115</td>\n",
       "      <td>-7.5</td>\n",
       "      <td>-105</td>\n",
       "      <td>+270</td>\n",
       "      <td>-335</td>\n",
       "      <td>O</td>\n",
       "      <td>155.5</td>\n",
       "      <td>-106</td>\n",
       "      <td>U</td>\n",
       "      <td>155.5</td>\n",
       "      <td>-114</td>\n",
       "      <td>Today 7:00PM</td>\n",
       "      <td>MORE WAGERS</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16</th>\n",
       "      <td>Wichita State</td>\n",
       "      <td>Houston</td>\n",
       "      <td>11.5</td>\n",
       "      <td>-110</td>\n",
       "      <td>-11.5</td>\n",
       "      <td>-110</td>\n",
       "      <td>+610</td>\n",
       "      <td>-900</td>\n",
       "      <td>O</td>\n",
       "      <td>135.5</td>\n",
       "      <td>-110</td>\n",
       "      <td>U</td>\n",
       "      <td>135.5</td>\n",
       "      <td>-110</td>\n",
       "      <td>Today 7:00PM</td>\n",
       "      <td>MORE WAGERS</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>17</th>\n",
       "      <td>Boston College</td>\n",
       "      <td>Duke</td>\n",
       "      <td>12.5</td>\n",
       "      <td>-110</td>\n",
       "      <td>-12.5</td>\n",
       "      <td>-110</td>\n",
       "      <td>+750</td>\n",
       "      <td>-1200</td>\n",
       "      <td>O</td>\n",
       "      <td>150.5</td>\n",
       "      <td>-106</td>\n",
       "      <td>U</td>\n",
       "      <td>150.5</td>\n",
       "      <td>-114</td>\n",
       "      <td>Today 7:30PM</td>\n",
       "      <td>MORE WAGERS</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18</th>\n",
       "      <td>Minnesota</td>\n",
       "      <td>Michigan</td>\n",
       "      <td>7.5</td>\n",
       "      <td>-110</td>\n",
       "      <td>-7.5</td>\n",
       "      <td>-110</td>\n",
       "      <td>+290</td>\n",
       "      <td>-360</td>\n",
       "      <td>O</td>\n",
       "      <td>152.5</td>\n",
       "      <td>-110</td>\n",
       "      <td>U</td>\n",
       "      <td>152.5</td>\n",
       "      <td>-112</td>\n",
       "      <td>Today 7:30PM</td>\n",
       "      <td>MORE WAGERS</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>19</th>\n",
       "      <td>Auburn</td>\n",
       "      <td>Ole Miss</td>\n",
       "      <td>7.5</td>\n",
       "      <td>-118</td>\n",
       "      <td>-7.5</td>\n",
       "      <td>-104</td>\n",
       "      <td>+265</td>\n",
       "      <td>-330</td>\n",
       "      <td>O</td>\n",
       "      <td>137.5</td>\n",
       "      <td>-114</td>\n",
       "      <td>U</td>\n",
       "      <td>137.5</td>\n",
       "      <td>-106</td>\n",
       "      <td>Today 8:00PM</td>\n",
       "      <td>MORE WAGERS</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20</th>\n",
       "      <td>Oklahoma</td>\n",
       "      <td>Baylor</td>\n",
       "      <td>11.5</td>\n",
       "      <td>-102</td>\n",
       "      <td>-11.5</td>\n",
       "      <td>-120</td>\n",
       "      <td>+660</td>\n",
       "      <td>-1000</td>\n",
       "      <td>O</td>\n",
       "      <td>151.5</td>\n",
       "      <td>-106</td>\n",
       "      <td>U</td>\n",
       "      <td>151.5</td>\n",
       "      <td>-114</td>\n",
       "      <td>Today 8:00PM</td>\n",
       "      <td>MORE WAGERS</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>21</th>\n",
       "      <td>Seton Hall</td>\n",
       "      <td>Creighton</td>\n",
       "      <td>5.5</td>\n",
       "      <td>-110</td>\n",
       "      <td>-5.5</td>\n",
       "      <td>-110</td>\n",
       "      <td>+200</td>\n",
       "      <td>-245</td>\n",
       "      <td>O</td>\n",
       "      <td>148.5</td>\n",
       "      <td>-110</td>\n",
       "      <td>U</td>\n",
       "      <td>148.5</td>\n",
       "      <td>-110</td>\n",
       "      <td>Today 8:00PM</td>\n",
       "      <td>MORE WAGERS</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>22</th>\n",
       "      <td>Texas A&amp;M</td>\n",
       "      <td>South Carolina</td>\n",
       "      <td>3.5</td>\n",
       "      <td>-102</td>\n",
       "      <td>-3.5</td>\n",
       "      <td>-120</td>\n",
       "      <td>+158</td>\n",
       "      <td>-188</td>\n",
       "      <td>O</td>\n",
       "      <td>137.5</td>\n",
       "      <td>-110</td>\n",
       "      <td>U</td>\n",
       "      <td>137.5</td>\n",
       "      <td>-110</td>\n",
       "      <td>Today 8:00PM</td>\n",
       "      <td>MORE WAGERS</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>23</th>\n",
       "      <td>Wake Forest</td>\n",
       "      <td>Virginia</td>\n",
       "      <td>14.5</td>\n",
       "      <td>-110</td>\n",
       "      <td>-14.5</td>\n",
       "      <td>-110</td>\n",
       "      <td>+1040</td>\n",
       "      <td>-2000</td>\n",
       "      <td>O</td>\n",
       "      <td>123.5</td>\n",
       "      <td>-115</td>\n",
       "      <td>U</td>\n",
       "      <td>123.5</td>\n",
       "      <td>-105</td>\n",
       "      <td>Today 8:00PM</td>\n",
       "      <td>MORE WAGERS</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>24</th>\n",
       "      <td>Utah State</td>\n",
       "      <td>New Mexico</td>\n",
       "      <td>13.5</td>\n",
       "      <td>-110</td>\n",
       "      <td>+13.5</td>\n",
       "      <td>-110</td>\n",
       "      <td>-1500</td>\n",
       "      <td>+870</td>\n",
       "      <td>O</td>\n",
       "      <td>139.5</td>\n",
       "      <td>-106</td>\n",
       "      <td>U</td>\n",
       "      <td>139.5</td>\n",
       "      <td>-114</td>\n",
       "      <td>Today 9:00PM</td>\n",
       "      <td>MORE WAGERS</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25</th>\n",
       "      <td>Air Force</td>\n",
       "      <td>Boise State</td>\n",
       "      <td>18.5</td>\n",
       "      <td>-114</td>\n",
       "      <td>-18.5</td>\n",
       "      <td>-106</td>\n",
       "      <td>+1600</td>\n",
       "      <td>-4500</td>\n",
       "      <td>O</td>\n",
       "      <td>132.5</td>\n",
       "      <td>-105</td>\n",
       "      <td>U</td>\n",
       "      <td>132.5</td>\n",
       "      <td>-115</td>\n",
       "      <td>Today 10:00PM</td>\n",
       "      <td>MORE WAGERS</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                   0                  1     2     3      4     5      6   \\\n",
       "0          St Josephs    St. Bonaventure  12.5  -115  -12.5  -105   +700   \n",
       "1               Tulsa      South Florida   1.5  -120   -1.5  -102   -102   \n",
       "2          Pittsburgh           Syracuse  11.5  -112  -11.5  -108   +590   \n",
       "3       Massachusetts  George Washington   5.5  -104   +5.5  -118   -230   \n",
       "4        Rhode Island           Richmond   3.5  -104   -3.5  -118   +156   \n",
       "5       Virginia Tech         Louisville   4.5  -114   -4.5  -106   +166   \n",
       "6            Arkansas          Tennessee   8.5  -118   -8.5  -104   +310   \n",
       "7          Georgetown             Butler   4.5  -112   -4.5  -108   +168   \n",
       "8             Georgia                LSU   9.5  -104   -9.5  -118   +440   \n",
       "9             Samford        Chattanooga   6.5  -104   -6.5  -118   +260   \n",
       "10                VCU       George Mason   6.5  -112   +6.5  -108   -300   \n",
       "11  Abilene Christian    Houston Baptist  15.5  -108  +15.5  -112  -2500   \n",
       "12              Lamar           Nicholls   7.5  -108   -7.5  -112   +290   \n",
       "13        New Orleans   Central Arkansas   7.5  -110   -7.5  -110   +280   \n",
       "14  Sam Houston State       SE Louisiana   4.5  -105   +4.5  -115   -194   \n",
       "15           St Johns             Xavier   7.5  -115   -7.5  -105   +270   \n",
       "16      Wichita State            Houston  11.5  -110  -11.5  -110   +610   \n",
       "17     Boston College               Duke  12.5  -110  -12.5  -110   +750   \n",
       "18          Minnesota           Michigan   7.5  -110   -7.5  -110   +290   \n",
       "19             Auburn           Ole Miss   7.5  -118   -7.5  -104   +265   \n",
       "20           Oklahoma             Baylor  11.5  -102  -11.5  -120   +660   \n",
       "21         Seton Hall          Creighton   5.5  -110   -5.5  -110   +200   \n",
       "22          Texas A&M     South Carolina   3.5  -102   -3.5  -120   +158   \n",
       "23        Wake Forest           Virginia  14.5  -110  -14.5  -110  +1040   \n",
       "24         Utah State         New Mexico  13.5  -110  +13.5  -110  -1500   \n",
       "25          Air Force        Boise State  18.5  -114  -18.5  -106  +1600   \n",
       "\n",
       "       7  8      9     10 11     12    13             14           15  \n",
       "0   -1100  O  152.5  -108  U  152.5  -112   Today 3:00PM  MORE WAGERS  \n",
       "1    -116  O  127.5  -106  U  127.5  -114   Today 3:00PM  MORE WAGERS  \n",
       "2    -850  O  139.5  -110  U  139.5  -110   Today 3:30PM  MORE WAGERS  \n",
       "3    +190  O  152.5  -106  U  152.5  -114   Today 5:00PM  MORE WAGERS  \n",
       "4    -186  O  144.5  -105  U  144.5  -115   Today 5:00PM  MORE WAGERS  \n",
       "5    -198  O  131.5  -110  U  131.5  -110   Today 5:30PM  MORE WAGERS  \n",
       "6    -400  O  141.5  -110  U  141.5  -110   Today 6:00PM  MORE WAGERS  \n",
       "7    -200  O  140.5  -114  U  140.5  -105   Today 6:00PM  MORE WAGERS  \n",
       "8    -590  O  155.5  -114  U  155.5  -106   Today 6:00PM  MORE WAGERS  \n",
       "9    -320  O  154.5  -108  U  154.5  -112   Today 6:00PM  MORE WAGERS  \n",
       "10   +245  O  136.5  -110  U  136.5  -110   Today 6:00PM  MORE WAGERS  \n",
       "11  +1200  O  148.5  -110  U  148.5  -110   Today 7:00PM  MORE WAGERS  \n",
       "12   -360  O  143.5  -115  U  143.5  -105   Today 7:00PM  MORE WAGERS  \n",
       "13   -350  O  150.5  -114  U  150.5  -106   Today 7:00PM  MORE WAGERS  \n",
       "14   +162  O  147.5  -105  U  147.5  -115   Today 7:00PM  MORE WAGERS  \n",
       "15   -335  O  155.5  -106  U  155.5  -114   Today 7:00PM  MORE WAGERS  \n",
       "16   -900  O  135.5  -110  U  135.5  -110   Today 7:00PM  MORE WAGERS  \n",
       "17  -1200  O  150.5  -106  U  150.5  -114   Today 7:30PM  MORE WAGERS  \n",
       "18   -360  O  152.5  -110  U  152.5  -112   Today 7:30PM  MORE WAGERS  \n",
       "19   -330  O  137.5  -114  U  137.5  -106   Today 8:00PM  MORE WAGERS  \n",
       "20  -1000  O  151.5  -106  U  151.5  -114   Today 8:00PM  MORE WAGERS  \n",
       "21   -245  O  148.5  -110  U  148.5  -110   Today 8:00PM  MORE WAGERS  \n",
       "22   -188  O  137.5  -110  U  137.5  -110   Today 8:00PM  MORE WAGERS  \n",
       "23  -2000  O  123.5  -115  U  123.5  -105   Today 8:00PM  MORE WAGERS  \n",
       "24   +870  O  139.5  -106  U  139.5  -114   Today 9:00PM  MORE WAGERS  \n",
       "25  -4500  O  132.5  -105  U  132.5  -115  Today 10:00PM  MORE WAGERS  "
      ]
     },
     "execution_count": 16,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "\n",
    "Fanduel"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [],
   "source": [
    "Kenpom['score1']=pd.to_numeric(Kenpom['score1'])\n",
    "Kenpom['score2']=pd.to_numeric(Kenpom['score2'])\n",
    "Kenpom[\"Kspread\"]=np.abs((Kenpom['score2']-Kenpom['score1']))\n",
    "\n",
    "\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {
    "scrolled": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[Text(1, 0, 'Michigan'),\n",
       " Text(8, 0, 'Creighton'),\n",
       " Text(15, 0, 'Louisville'),\n",
       " Text(22, 0, 'Tennessee'),\n",
       " Text(29, 0, 'Richmond'),\n",
       " Text(36, 0, 'Mississippi'),\n",
       " Text(43, 0, 'South Carolina'),\n",
       " Text(50, 0, 'South Florida'),\n",
       " Text(57, 0, 'Baylor'),\n",
       " Text(64, 0, 'Xavier'),\n",
       " Text(71, 0, 'Syracuse'),\n",
       " Text(78, 0, 'Syracuse'),\n",
       " Text(85, 0, 'Butler'),\n",
       " Text(92, 0, 'LSU'),\n",
       " Text(99, 0, 'VCU'),\n",
       " Text(106, 0, 'Wofford'),\n",
       " Text(113, 0, 'Houston'),\n",
       " Text(120, 0, 'Massachusetts'),\n",
       " Text(127, 0, 'Duke'),\n",
       " Text(134, 0, 'Virginia'),\n",
       " Text(141, 0, 'Sam Houston St.'),\n",
       " Text(148, 0, 'St. Bonaventure'),\n",
       " Text(155, 0, 'Chattanooga'),\n",
       " Text(162, 0, 'Nicholls St.'),\n",
       " Text(169, 0, 'Central Arkansas'),\n",
       " Text(176, 0, 'Utah St.'),\n",
       " Text(183, 0, 'Northwestern St.'),\n",
       " Text(190, 0, 'Boise St.'),\n",
       " Text(197, 0, 'Abilene Christian')]"
      ]
     },
     "execution_count": 18,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "import matplotlib.pyplot as plt\n",
    "Kenpom['Kspread']=pd.to_numeric(Kenpom['Kspread']) \n",
    "\n",
    "kenvis= pd.DataFrame(Kenpom['Kspread'])\n",
    "\n",
    "plt.figure();\n",
    "ax = kenvis.Kspread.plot(xticks=Kenpom.index, rot=90)\n",
    "ax.set_xticklabels(Kenpom.team)\n",
    "#kenpom plot of spreads by team"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>team</th>\n",
       "      <th>score1</th>\n",
       "      <th>score2</th>\n",
       "      <th>Kspread</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>50</th>\n",
       "      <td>South Florida</td>\n",
       "      <td>63</td>\n",
       "      <td>62</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>106</th>\n",
       "      <td>Wofford</td>\n",
       "      <td>71</td>\n",
       "      <td>69</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15</th>\n",
       "      <td>Louisville</td>\n",
       "      <td>67</td>\n",
       "      <td>64</td>\n",
       "      <td>3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>141</th>\n",
       "      <td>Sam Houston St.</td>\n",
       "      <td>75</td>\n",
       "      <td>72</td>\n",
       "      <td>3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>29</th>\n",
       "      <td>Richmond</td>\n",
       "      <td>75</td>\n",
       "      <td>71</td>\n",
       "      <td>4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>43</th>\n",
       "      <td>South Carolina</td>\n",
       "      <td>71</td>\n",
       "      <td>67</td>\n",
       "      <td>4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>120</th>\n",
       "      <td>Massachusetts</td>\n",
       "      <td>80</td>\n",
       "      <td>76</td>\n",
       "      <td>4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Michigan</td>\n",
       "      <td>78</td>\n",
       "      <td>73</td>\n",
       "      <td>5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>Creighton</td>\n",
       "      <td>77</td>\n",
       "      <td>72</td>\n",
       "      <td>5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>36</th>\n",
       "      <td>Mississippi</td>\n",
       "      <td>72</td>\n",
       "      <td>67</td>\n",
       "      <td>5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>85</th>\n",
       "      <td>Butler</td>\n",
       "      <td>73</td>\n",
       "      <td>68</td>\n",
       "      <td>5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>99</th>\n",
       "      <td>VCU</td>\n",
       "      <td>72</td>\n",
       "      <td>66</td>\n",
       "      <td>6</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>64</th>\n",
       "      <td>Xavier</td>\n",
       "      <td>81</td>\n",
       "      <td>75</td>\n",
       "      <td>6</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>22</th>\n",
       "      <td>Tennessee</td>\n",
       "      <td>74</td>\n",
       "      <td>67</td>\n",
       "      <td>7</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>155</th>\n",
       "      <td>Chattanooga</td>\n",
       "      <td>80</td>\n",
       "      <td>73</td>\n",
       "      <td>7</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>183</th>\n",
       "      <td>Northwestern St.</td>\n",
       "      <td>78</td>\n",
       "      <td>70</td>\n",
       "      <td>8</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>169</th>\n",
       "      <td>Central Arkansas</td>\n",
       "      <td>80</td>\n",
       "      <td>72</td>\n",
       "      <td>8</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>162</th>\n",
       "      <td>Nicholls St.</td>\n",
       "      <td>76</td>\n",
       "      <td>68</td>\n",
       "      <td>8</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>78</th>\n",
       "      <td>Syracuse</td>\n",
       "      <td>76</td>\n",
       "      <td>68</td>\n",
       "      <td>8</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>71</th>\n",
       "      <td>Syracuse</td>\n",
       "      <td>76</td>\n",
       "      <td>68</td>\n",
       "      <td>8</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>92</th>\n",
       "      <td>LSU</td>\n",
       "      <td>84</td>\n",
       "      <td>74</td>\n",
       "      <td>10</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>148</th>\n",
       "      <td>St. Bonaventure</td>\n",
       "      <td>83</td>\n",
       "      <td>72</td>\n",
       "      <td>11</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>113</th>\n",
       "      <td>Houston</td>\n",
       "      <td>73</td>\n",
       "      <td>62</td>\n",
       "      <td>11</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>57</th>\n",
       "      <td>Baylor</td>\n",
       "      <td>82</td>\n",
       "      <td>70</td>\n",
       "      <td>12</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>127</th>\n",
       "      <td>Duke</td>\n",
       "      <td>81</td>\n",
       "      <td>68</td>\n",
       "      <td>13</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>176</th>\n",
       "      <td>Utah St.</td>\n",
       "      <td>76</td>\n",
       "      <td>63</td>\n",
       "      <td>13</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>134</th>\n",
       "      <td>Virginia</td>\n",
       "      <td>68</td>\n",
       "      <td>55</td>\n",
       "      <td>13</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>190</th>\n",
       "      <td>Boise St.</td>\n",
       "      <td>72</td>\n",
       "      <td>57</td>\n",
       "      <td>15</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>197</th>\n",
       "      <td>Abilene Christian</td>\n",
       "      <td>81</td>\n",
       "      <td>65</td>\n",
       "      <td>16</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                  team  score1  score2  Kspread\n",
       "50       South Florida      63      62        1\n",
       "106            Wofford      71      69        2\n",
       "15          Louisville      67      64        3\n",
       "141    Sam Houston St.      75      72        3\n",
       "29            Richmond      75      71        4\n",
       "43      South Carolina      71      67        4\n",
       "120      Massachusetts      80      76        4\n",
       "1             Michigan      78      73        5\n",
       "8            Creighton      77      72        5\n",
       "36         Mississippi      72      67        5\n",
       "85              Butler      73      68        5\n",
       "99                 VCU      72      66        6\n",
       "64              Xavier      81      75        6\n",
       "22           Tennessee      74      67        7\n",
       "155        Chattanooga      80      73        7\n",
       "183   Northwestern St.      78      70        8\n",
       "169   Central Arkansas      80      72        8\n",
       "162       Nicholls St.      76      68        8\n",
       "78            Syracuse      76      68        8\n",
       "71            Syracuse      76      68        8\n",
       "92                 LSU      84      74       10\n",
       "148    St. Bonaventure      83      72       11\n",
       "113            Houston      73      62       11\n",
       "57              Baylor      82      70       12\n",
       "127               Duke      81      68       13\n",
       "176           Utah St.      76      63       13\n",
       "134           Virginia      68      55       13\n",
       "190          Boise St.      72      57       15\n",
       "197  Abilene Christian      81      65       16"
      ]
     },
     "execution_count": 19,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "Kenpom.sort_values('Kspread')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {},
   "outputs": [],
   "source": [
    "Hasla2=pd.concat([dfh5, dfh6], axis=1).iloc[0:50]\n",
    "HaslaF=pd.concat([Hasla, Hasla2], axis=1).iloc[0:25]\n",
    "\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[Text(0, 0, 'Baylor 1'),\n",
       " Text(1, 0, 'Michigan 5'),\n",
       " Text(2, 0, 'Tennessee 6'),\n",
       " Text(3, 0, 'Creighton 14'),\n",
       " Text(4, 0, 'Virginia 15'),\n",
       " Text(5, 0, 'LSU 16'),\n",
       " Text(6, 0, 'Houston 18'),\n",
       " Text(7, 0, 'Syracuse 20'),\n",
       " Text(8, 0, 'Duke 34'),\n",
       " Text(9, 0, 'Xavier 37'),\n",
       " Text(10, 0, 'Louisville 41'),\n",
       " Text(11, 0, 'VCU 40'),\n",
       " Text(12, 0, 'Ole Miss 49'),\n",
       " Text(13, 0, 'Richmond 61'),\n",
       " Text(14, 0, 'Utah State 67'),\n",
       " Text(15, 0, 'Boise State 68'),\n",
       " Text(16, 0, 'South Carolina 77'),\n",
       " Text(17, 0, 'St. Bonaventure 84'),\n",
       " Text(18, 0, 'USF 106'),\n",
       " Text(19, 0, 'Butler 102'),\n",
       " Text(20, 0, 'UMass 111'),\n",
       " Text(21, 0, 'Abil. Christian 116'),\n",
       " Text(22, 0, 'Wofford 122'),\n",
       " Text(23, 0, 'Chattanooga 183'),\n",
       " Text(24, 0, 'Cent. Arkansas 207')]"
      ]
     },
     "execution_count": 21,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "text/plain": [
       "<Figure size 432x288 with 0 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "import matplotlib.pyplot as plt\n",
    "HaslaF['HScore']=pd.to_numeric(HaslaF['HScore'])\n",
    "HaslaF['Ascore']=pd.to_numeric(HaslaF['Ascore'])\n",
    "HaslaF[\"Hspread\"]=np.abs((HaslaF['HScore']-HaslaF['Ascore']))\n",
    "HaslaF['Hspread']\n",
    "HaslaF['Hspread']=pd.to_numeric(HaslaF['Hspread'])\n",
    "Hvis= pd.DataFrame(HaslaF['Hspread'])\n",
    "\n",
    "plt.figure();\n",
    "plt.figure();\n",
    "ax = Hvis.Hspread.plot(xticks=HaslaF.index, rot=90)\n",
    "ax.set_xticklabels(HaslaF.Home)\n",
    "#hasla plot of spreads by team"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Home</th>\n",
       "      <th>HScore</th>\n",
       "      <th>Away</th>\n",
       "      <th>Ascore</th>\n",
       "      <th>Hspread</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>18</th>\n",
       "      <td>USF 106</td>\n",
       "      <td>63.65</td>\n",
       "      <td>Tulsa 85</td>\n",
       "      <td>63.40</td>\n",
       "      <td>0.25</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>Louisville 41</td>\n",
       "      <td>68.74</td>\n",
       "      <td>Virginia Tech 38</td>\n",
       "      <td>66.65</td>\n",
       "      <td>2.09</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>23</th>\n",
       "      <td>Chattanooga 183</td>\n",
       "      <td>77.23</td>\n",
       "      <td>Samford 197</td>\n",
       "      <td>73.66</td>\n",
       "      <td>3.57</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>Creighton 14</td>\n",
       "      <td>77.06</td>\n",
       "      <td>Seton Hall 19</td>\n",
       "      <td>72.80</td>\n",
       "      <td>4.26</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>22</th>\n",
       "      <td>Wofford 122</td>\n",
       "      <td>70.29</td>\n",
       "      <td>UNCG 164</td>\n",
       "      <td>65.45</td>\n",
       "      <td>4.84</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13</th>\n",
       "      <td>Richmond 61</td>\n",
       "      <td>74.65</td>\n",
       "      <td>URI 93</td>\n",
       "      <td>69.77</td>\n",
       "      <td>4.88</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>19</th>\n",
       "      <td>Butler 102</td>\n",
       "      <td>71.10</td>\n",
       "      <td>Georgetown 127</td>\n",
       "      <td>66.03</td>\n",
       "      <td>5.07</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16</th>\n",
       "      <td>South Carolina 77</td>\n",
       "      <td>73.44</td>\n",
       "      <td>Texas A&amp;M 129</td>\n",
       "      <td>65.88</td>\n",
       "      <td>7.56</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>Ole Miss 49</td>\n",
       "      <td>74.15</td>\n",
       "      <td>Auburn 96</td>\n",
       "      <td>66.40</td>\n",
       "      <td>7.75</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20</th>\n",
       "      <td>UMass 111</td>\n",
       "      <td>81.43</td>\n",
       "      <td>G. Washington 283</td>\n",
       "      <td>72.87</td>\n",
       "      <td>8.56</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Michigan 5</td>\n",
       "      <td>77.85</td>\n",
       "      <td>Minnesota 25</td>\n",
       "      <td>69.24</td>\n",
       "      <td>8.61</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>17</th>\n",
       "      <td>St. Bonaventure 84</td>\n",
       "      <td>77.49</td>\n",
       "      <td>Saint Joe's 158</td>\n",
       "      <td>68.83</td>\n",
       "      <td>8.66</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>Tennessee 6</td>\n",
       "      <td>77.73</td>\n",
       "      <td>Arkansas 33</td>\n",
       "      <td>68.38</td>\n",
       "      <td>9.35</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>24</th>\n",
       "      <td>Cent. Arkansas 207</td>\n",
       "      <td>79.03</td>\n",
       "      <td>New Orleans 312</td>\n",
       "      <td>69.17</td>\n",
       "      <td>9.86</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>Syracuse 20</td>\n",
       "      <td>72.49</td>\n",
       "      <td>Pittsburgh 76</td>\n",
       "      <td>62.53</td>\n",
       "      <td>9.96</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>Houston 18</td>\n",
       "      <td>73.07</td>\n",
       "      <td>Wichita State 74</td>\n",
       "      <td>62.86</td>\n",
       "      <td>10.21</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>Xavier 37</td>\n",
       "      <td>83.71</td>\n",
       "      <td>St. John's 104</td>\n",
       "      <td>72.84</td>\n",
       "      <td>10.87</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>Duke 34</td>\n",
       "      <td>79.96</td>\n",
       "      <td>Boston College 100</td>\n",
       "      <td>68.78</td>\n",
       "      <td>11.18</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14</th>\n",
       "      <td>Utah State 67</td>\n",
       "      <td>76.61</td>\n",
       "      <td>New Mexico 267</td>\n",
       "      <td>65.27</td>\n",
       "      <td>11.34</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>LSU 16</td>\n",
       "      <td>83.55</td>\n",
       "      <td>Georgia 80</td>\n",
       "      <td>71.44</td>\n",
       "      <td>12.11</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>VCU 40</td>\n",
       "      <td>73.61</td>\n",
       "      <td>George Mason 185</td>\n",
       "      <td>61.46</td>\n",
       "      <td>12.15</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>Virginia 15</td>\n",
       "      <td>70.05</td>\n",
       "      <td>Wake Forest 105</td>\n",
       "      <td>57.12</td>\n",
       "      <td>12.93</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>Baylor 1</td>\n",
       "      <td>86.37</td>\n",
       "      <td>Oklahoma 45</td>\n",
       "      <td>69.64</td>\n",
       "      <td>16.73</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>21</th>\n",
       "      <td>Abil. Christian 116</td>\n",
       "      <td>81.62</td>\n",
       "      <td>Houston Baptist 352</td>\n",
       "      <td>63.64</td>\n",
       "      <td>17.98</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15</th>\n",
       "      <td>Boise State 68</td>\n",
       "      <td>76.68</td>\n",
       "      <td>Air Force 317</td>\n",
       "      <td>56.58</td>\n",
       "      <td>20.10</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                   Home  HScore                 Away  Ascore  Hspread\n",
       "18              USF 106   63.65             Tulsa 85   63.40     0.25\n",
       "10        Louisville 41   68.74     Virginia Tech 38   66.65     2.09\n",
       "23      Chattanooga 183   77.23          Samford 197   73.66     3.57\n",
       "3          Creighton 14   77.06        Seton Hall 19   72.80     4.26\n",
       "22          Wofford 122   70.29             UNCG 164   65.45     4.84\n",
       "13          Richmond 61   74.65               URI 93   69.77     4.88\n",
       "19           Butler 102   71.10       Georgetown 127   66.03     5.07\n",
       "16    South Carolina 77   73.44        Texas A&M 129   65.88     7.56\n",
       "12          Ole Miss 49   74.15            Auburn 96   66.40     7.75\n",
       "20            UMass 111   81.43    G. Washington 283   72.87     8.56\n",
       "1            Michigan 5   77.85         Minnesota 25   69.24     8.61\n",
       "17   St. Bonaventure 84   77.49      Saint Joe's 158   68.83     8.66\n",
       "2           Tennessee 6   77.73          Arkansas 33   68.38     9.35\n",
       "24   Cent. Arkansas 207   79.03      New Orleans 312   69.17     9.86\n",
       "7           Syracuse 20   72.49        Pittsburgh 76   62.53     9.96\n",
       "6            Houston 18   73.07     Wichita State 74   62.86    10.21\n",
       "9             Xavier 37   83.71       St. John's 104   72.84    10.87\n",
       "8               Duke 34   79.96   Boston College 100   68.78    11.18\n",
       "14        Utah State 67   76.61       New Mexico 267   65.27    11.34\n",
       "5                LSU 16   83.55           Georgia 80   71.44    12.11\n",
       "11               VCU 40   73.61     George Mason 185   61.46    12.15\n",
       "4           Virginia 15   70.05      Wake Forest 105   57.12    12.93\n",
       "0              Baylor 1   86.37          Oklahoma 45   69.64    16.73\n",
       "21  Abil. Christian 116   81.62  Houston Baptist 352   63.64    17.98\n",
       "15       Boise State 68   76.68        Air Force 317   56.58    20.10"
      ]
     },
     "execution_count": 22,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "HaslaF.sort_values('Hspread')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[Text(2, 0, 'Michigan -6.3'),\n",
       " Text(6, 0, 'Creighton -5.6'),\n",
       " Text(10, 0, 'Tennessee -7.2'),\n",
       " Text(14, 0, 'Richmond -3.7'),\n",
       " Text(18, 0, 'Baylor -12.6'),\n",
       " Text(22, 0, 'Louisville -4.1'),\n",
       " Text(26, 0, 'South Florida -1.5'),\n",
       " Text(30, 0, 'Syracuse -8.3'),\n",
       " Text(34, 0, 'Xavier -8.3'),\n",
       " Text(38, 0, 'Butler -2.8'),\n",
       " Text(42, 0, 'LSU -9.7'),\n",
       " Text(46, 0, 'South Carolina -4.7'),\n",
       " Text(50, 0, 'Mississippi -7.7'),\n",
       " Text(54, 0, 'VCU -6.2'),\n",
       " Text(58, 0, 'Houston -10.1'),\n",
       " Text(62, 0, 'Wofford -2.0'),\n",
       " Text(66, 0, 'Massachusetts -3.3'),\n",
       " Text(70, 0, 'Duke -12.1'),\n",
       " Text(74, 0, 'St. Bonaventure -10.5'),\n",
       " Text(78, 0, 'Chattanooga -5.7'),\n",
       " Text(82, 0, 'Sam Houston St. -1.3'),\n",
       " Text(86, 0, 'Virginia -12.9'),\n",
       " Text(90, 0, 'Utah St. -10.2'),\n",
       " Text(94, 0, 'Northwestern St. -4.6'),\n",
       " Text(98, 0, 'Nicholls St. -6.8'),\n",
       " Text(102, 0, 'Central Arkansas -9.3'),\n",
       " Text(106, 0, 'Boise St. -17.5'),\n",
       " Text(110, 0, 'Abilene Christian -17.1')]"
      ]
     },
     "execution_count": 23,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "import matplotlib.pyplot as plt\n",
    "\n",
    "TovFinal['Score1']=pd.to_numeric(TovFinal['Score1'])\n",
    "TovFinal['Score2']=pd.to_numeric(TovFinal['Score2'])\n",
    "TovFinal[\"Tspread\"]=np.abs((TovFinal['Score2']-TovFinal['Score1']))\n",
    "TovFinal['Tspread']=pd.to_numeric(TovFinal['Tspread'])\n",
    "\n",
    "Torvis= pd.DataFrame(TovFinal['Tspread'])\n",
    "plt.figure();\n",
    "ax = Torvis.Tspread.plot(xticks=TovFinal.index, rot=90)\n",
    "ax.set_xticklabels(TovFinal.Team)\n",
    "\n",
    "#torvis plot of spreads by team"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {
    "scrolled": false
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Team</th>\n",
       "      <th>Score1</th>\n",
       "      <th>Score2</th>\n",
       "      <th>Tspread</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>82</th>\n",
       "      <td>Sam Houston St. -1.3</td>\n",
       "      <td>73</td>\n",
       "      <td>72</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>26</th>\n",
       "      <td>South Florida -1.5</td>\n",
       "      <td>63</td>\n",
       "      <td>61</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>62</th>\n",
       "      <td>Wofford -2.0</td>\n",
       "      <td>69</td>\n",
       "      <td>67</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>38</th>\n",
       "      <td>Butler -2.8</td>\n",
       "      <td>71</td>\n",
       "      <td>68</td>\n",
       "      <td>3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14</th>\n",
       "      <td>Richmond -3.7</td>\n",
       "      <td>75</td>\n",
       "      <td>71</td>\n",
       "      <td>4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>22</th>\n",
       "      <td>Louisville -4.1</td>\n",
       "      <td>68</td>\n",
       "      <td>64</td>\n",
       "      <td>4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>66</th>\n",
       "      <td>Massachusetts -3.3</td>\n",
       "      <td>82</td>\n",
       "      <td>78</td>\n",
       "      <td>4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>94</th>\n",
       "      <td>Northwestern St. -4.6</td>\n",
       "      <td>78</td>\n",
       "      <td>73</td>\n",
       "      <td>5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>46</th>\n",
       "      <td>South Carolina -4.7</td>\n",
       "      <td>71</td>\n",
       "      <td>66</td>\n",
       "      <td>5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>54</th>\n",
       "      <td>VCU -6.2</td>\n",
       "      <td>71</td>\n",
       "      <td>65</td>\n",
       "      <td>6</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>Creighton -5.6</td>\n",
       "      <td>77</td>\n",
       "      <td>71</td>\n",
       "      <td>6</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>78</th>\n",
       "      <td>Chattanooga -5.7</td>\n",
       "      <td>81</td>\n",
       "      <td>75</td>\n",
       "      <td>6</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>98</th>\n",
       "      <td>Nicholls St. -6.8</td>\n",
       "      <td>74</td>\n",
       "      <td>67</td>\n",
       "      <td>7</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>Michigan -6.3</td>\n",
       "      <td>79</td>\n",
       "      <td>72</td>\n",
       "      <td>7</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>50</th>\n",
       "      <td>Mississippi -7.7</td>\n",
       "      <td>72</td>\n",
       "      <td>65</td>\n",
       "      <td>7</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>Tennessee -7.2</td>\n",
       "      <td>73</td>\n",
       "      <td>66</td>\n",
       "      <td>7</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>34</th>\n",
       "      <td>Xavier -8.3</td>\n",
       "      <td>84</td>\n",
       "      <td>75</td>\n",
       "      <td>9</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>30</th>\n",
       "      <td>Syracuse -8.3</td>\n",
       "      <td>77</td>\n",
       "      <td>68</td>\n",
       "      <td>9</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>58</th>\n",
       "      <td>Houston -10.1</td>\n",
       "      <td>72</td>\n",
       "      <td>62</td>\n",
       "      <td>10</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>42</th>\n",
       "      <td>LSU -9.7</td>\n",
       "      <td>84</td>\n",
       "      <td>74</td>\n",
       "      <td>10</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>74</th>\n",
       "      <td>St. Bonaventure -10.5</td>\n",
       "      <td>83</td>\n",
       "      <td>73</td>\n",
       "      <td>10</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>90</th>\n",
       "      <td>Utah St. -10.2</td>\n",
       "      <td>73</td>\n",
       "      <td>63</td>\n",
       "      <td>10</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>102</th>\n",
       "      <td>Central Arkansas -9.3</td>\n",
       "      <td>81</td>\n",
       "      <td>71</td>\n",
       "      <td>10</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>70</th>\n",
       "      <td>Duke -12.1</td>\n",
       "      <td>82</td>\n",
       "      <td>70</td>\n",
       "      <td>12</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>86</th>\n",
       "      <td>Virginia -12.9</td>\n",
       "      <td>69</td>\n",
       "      <td>56</td>\n",
       "      <td>13</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18</th>\n",
       "      <td>Baylor -12.6</td>\n",
       "      <td>83</td>\n",
       "      <td>70</td>\n",
       "      <td>13</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>106</th>\n",
       "      <td>Boise St. -17.5</td>\n",
       "      <td>72</td>\n",
       "      <td>55</td>\n",
       "      <td>17</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>110</th>\n",
       "      <td>Abilene Christian -17.1</td>\n",
       "      <td>82</td>\n",
       "      <td>65</td>\n",
       "      <td>17</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                        Team  Score1  Score2  Tspread\n",
       "82      Sam Houston St. -1.3      73      72        1\n",
       "26        South Florida -1.5      63      61        2\n",
       "62              Wofford -2.0      69      67        2\n",
       "38               Butler -2.8      71      68        3\n",
       "14             Richmond -3.7      75      71        4\n",
       "22           Louisville -4.1      68      64        4\n",
       "66        Massachusetts -3.3      82      78        4\n",
       "94     Northwestern St. -4.6      78      73        5\n",
       "46       South Carolina -4.7      71      66        5\n",
       "54                  VCU -6.2      71      65        6\n",
       "6             Creighton -5.6      77      71        6\n",
       "78          Chattanooga -5.7      81      75        6\n",
       "98         Nicholls St. -6.8      74      67        7\n",
       "2              Michigan -6.3      79      72        7\n",
       "50          Mississippi -7.7      72      65        7\n",
       "10            Tennessee -7.2      73      66        7\n",
       "34               Xavier -8.3      84      75        9\n",
       "30             Syracuse -8.3      77      68        9\n",
       "58             Houston -10.1      72      62       10\n",
       "42                  LSU -9.7      84      74       10\n",
       "74     St. Bonaventure -10.5      83      73       10\n",
       "90            Utah St. -10.2      73      63       10\n",
       "102    Central Arkansas -9.3      81      71       10\n",
       "70                Duke -12.1      82      70       12\n",
       "86            Virginia -12.9      69      56       13\n",
       "18              Baylor -12.6      83      70       13\n",
       "106          Boise St. -17.5      72      55       17\n",
       "110  Abilene Christian -17.1      82      65       17"
      ]
     },
     "execution_count": 24,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "\n",
    "TovFinal.sort_values('Tspread')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<AxesSubplot:>"
      ]
     },
     "execution_count": 25,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "frame=[Torvis,Hvis,kenvis,Fanduel[2]]\n",
    "frames=pd.concat(frame, axis=1)\n",
    "frames.plot.box()\n",
    "#avg spreads by site 2=fanduel "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<AxesSubplot:ylabel='Frequency'>"
      ]
     },
     "execution_count": 26,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "frames.plot.hist() #frequency of predicted spreads per site"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<AxesSubplot:ylabel='Density'>"
      ]
     },
     "execution_count": 27,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "frames.plot.kde(bw_method=0.3) #density of predicted spreads per site"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "metadata": {},
   "outputs": [],
   "source": [
    "TovFinal[\"TTotal\"]=np.abs((TovFinal['Score2']+TovFinal['Score1']))\n",
    "\n",
    "HaslaF[\"HTotal\"]=np.abs((HaslaF['HScore']+HaslaF['Ascore']))\n",
    "\n",
    "Kenpom[\"KTotal\"]=np.abs((Kenpom['score2']+Kenpom['score1']))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<AxesSubplot:ylabel='Density'>"
      ]
     },
     "execution_count": 29,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "TTvis=pd.DataFrame(TovFinal[\"TTotal\"])\n",
    "HTvis=pd.DataFrame(HaslaF['HTotal'])\n",
    "KTvis=pd.DataFrame(Kenpom[\"KTotal\"])\n",
    "FDTotal=pd.DataFrame(Fanduel[9])\n",
    "Tframes=[TTvis,HTvis,KTvis,FDTotal]\n",
    "Tframe=pd.concat(Tframes, axis=1)\n",
    "Tframe.plot.kde(bw_method=0.3)\n",
    "#density of predicted totals per site 9=fanduel"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<AxesSubplot:ylabel='Frequency'>"
      ]
     },
     "execution_count": 30,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "Tframe.plot.hist() #frequency of predicted total per site"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<AxesSubplot:>"
      ]
     },
     "execution_count": 31,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "Tframe.plot.box() #avg predicted total per site"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Team</th>\n",
       "      <th>Score1</th>\n",
       "      <th>Score2</th>\n",
       "      <th>Tspread</th>\n",
       "      <th>TTotal</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>26</th>\n",
       "      <td>South Florida -1.5</td>\n",
       "      <td>63</td>\n",
       "      <td>61</td>\n",
       "      <td>2</td>\n",
       "      <td>124</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>86</th>\n",
       "      <td>Virginia -12.9</td>\n",
       "      <td>69</td>\n",
       "      <td>56</td>\n",
       "      <td>13</td>\n",
       "      <td>125</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>106</th>\n",
       "      <td>Boise St. -17.5</td>\n",
       "      <td>72</td>\n",
       "      <td>55</td>\n",
       "      <td>17</td>\n",
       "      <td>127</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>22</th>\n",
       "      <td>Louisville -4.1</td>\n",
       "      <td>68</td>\n",
       "      <td>64</td>\n",
       "      <td>4</td>\n",
       "      <td>132</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>58</th>\n",
       "      <td>Houston -10.1</td>\n",
       "      <td>72</td>\n",
       "      <td>62</td>\n",
       "      <td>10</td>\n",
       "      <td>134</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>54</th>\n",
       "      <td>VCU -6.2</td>\n",
       "      <td>71</td>\n",
       "      <td>65</td>\n",
       "      <td>6</td>\n",
       "      <td>136</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>90</th>\n",
       "      <td>Utah St. -10.2</td>\n",
       "      <td>73</td>\n",
       "      <td>63</td>\n",
       "      <td>10</td>\n",
       "      <td>136</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>62</th>\n",
       "      <td>Wofford -2.0</td>\n",
       "      <td>69</td>\n",
       "      <td>67</td>\n",
       "      <td>2</td>\n",
       "      <td>136</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>46</th>\n",
       "      <td>South Carolina -4.7</td>\n",
       "      <td>71</td>\n",
       "      <td>66</td>\n",
       "      <td>5</td>\n",
       "      <td>137</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>50</th>\n",
       "      <td>Mississippi -7.7</td>\n",
       "      <td>72</td>\n",
       "      <td>65</td>\n",
       "      <td>7</td>\n",
       "      <td>137</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>Tennessee -7.2</td>\n",
       "      <td>73</td>\n",
       "      <td>66</td>\n",
       "      <td>7</td>\n",
       "      <td>139</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>38</th>\n",
       "      <td>Butler -2.8</td>\n",
       "      <td>71</td>\n",
       "      <td>68</td>\n",
       "      <td>3</td>\n",
       "      <td>139</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>98</th>\n",
       "      <td>Nicholls St. -6.8</td>\n",
       "      <td>74</td>\n",
       "      <td>67</td>\n",
       "      <td>7</td>\n",
       "      <td>141</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>30</th>\n",
       "      <td>Syracuse -8.3</td>\n",
       "      <td>77</td>\n",
       "      <td>68</td>\n",
       "      <td>9</td>\n",
       "      <td>145</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>82</th>\n",
       "      <td>Sam Houston St. -1.3</td>\n",
       "      <td>73</td>\n",
       "      <td>72</td>\n",
       "      <td>1</td>\n",
       "      <td>145</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14</th>\n",
       "      <td>Richmond -3.7</td>\n",
       "      <td>75</td>\n",
       "      <td>71</td>\n",
       "      <td>4</td>\n",
       "      <td>146</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>110</th>\n",
       "      <td>Abilene Christian -17.1</td>\n",
       "      <td>82</td>\n",
       "      <td>65</td>\n",
       "      <td>17</td>\n",
       "      <td>147</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>Creighton -5.6</td>\n",
       "      <td>77</td>\n",
       "      <td>71</td>\n",
       "      <td>6</td>\n",
       "      <td>148</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>94</th>\n",
       "      <td>Northwestern St. -4.6</td>\n",
       "      <td>78</td>\n",
       "      <td>73</td>\n",
       "      <td>5</td>\n",
       "      <td>151</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>Michigan -6.3</td>\n",
       "      <td>79</td>\n",
       "      <td>72</td>\n",
       "      <td>7</td>\n",
       "      <td>151</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>70</th>\n",
       "      <td>Duke -12.1</td>\n",
       "      <td>82</td>\n",
       "      <td>70</td>\n",
       "      <td>12</td>\n",
       "      <td>152</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>102</th>\n",
       "      <td>Central Arkansas -9.3</td>\n",
       "      <td>81</td>\n",
       "      <td>71</td>\n",
       "      <td>10</td>\n",
       "      <td>152</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18</th>\n",
       "      <td>Baylor -12.6</td>\n",
       "      <td>83</td>\n",
       "      <td>70</td>\n",
       "      <td>13</td>\n",
       "      <td>153</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>74</th>\n",
       "      <td>St. Bonaventure -10.5</td>\n",
       "      <td>83</td>\n",
       "      <td>73</td>\n",
       "      <td>10</td>\n",
       "      <td>156</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>78</th>\n",
       "      <td>Chattanooga -5.7</td>\n",
       "      <td>81</td>\n",
       "      <td>75</td>\n",
       "      <td>6</td>\n",
       "      <td>156</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>42</th>\n",
       "      <td>LSU -9.7</td>\n",
       "      <td>84</td>\n",
       "      <td>74</td>\n",
       "      <td>10</td>\n",
       "      <td>158</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>34</th>\n",
       "      <td>Xavier -8.3</td>\n",
       "      <td>84</td>\n",
       "      <td>75</td>\n",
       "      <td>9</td>\n",
       "      <td>159</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>66</th>\n",
       "      <td>Massachusetts -3.3</td>\n",
       "      <td>82</td>\n",
       "      <td>78</td>\n",
       "      <td>4</td>\n",
       "      <td>160</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                        Team  Score1  Score2  Tspread  TTotal\n",
       "26        South Florida -1.5      63      61        2     124\n",
       "86            Virginia -12.9      69      56       13     125\n",
       "106          Boise St. -17.5      72      55       17     127\n",
       "22           Louisville -4.1      68      64        4     132\n",
       "58             Houston -10.1      72      62       10     134\n",
       "54                  VCU -6.2      71      65        6     136\n",
       "90            Utah St. -10.2      73      63       10     136\n",
       "62              Wofford -2.0      69      67        2     136\n",
       "46       South Carolina -4.7      71      66        5     137\n",
       "50          Mississippi -7.7      72      65        7     137\n",
       "10            Tennessee -7.2      73      66        7     139\n",
       "38               Butler -2.8      71      68        3     139\n",
       "98         Nicholls St. -6.8      74      67        7     141\n",
       "30             Syracuse -8.3      77      68        9     145\n",
       "82      Sam Houston St. -1.3      73      72        1     145\n",
       "14             Richmond -3.7      75      71        4     146\n",
       "110  Abilene Christian -17.1      82      65       17     147\n",
       "6             Creighton -5.6      77      71        6     148\n",
       "94     Northwestern St. -4.6      78      73        5     151\n",
       "2              Michigan -6.3      79      72        7     151\n",
       "70                Duke -12.1      82      70       12     152\n",
       "102    Central Arkansas -9.3      81      71       10     152\n",
       "18              Baylor -12.6      83      70       13     153\n",
       "74     St. Bonaventure -10.5      83      73       10     156\n",
       "78          Chattanooga -5.7      81      75        6     156\n",
       "42                  LSU -9.7      84      74       10     158\n",
       "34               Xavier -8.3      84      75        9     159\n",
       "66        Massachusetts -3.3      82      78        4     160"
      ]
     },
     "execution_count": 32,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "TovFinal.sort_values('TTotal') #final tables with totals"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Home</th>\n",
       "      <th>HScore</th>\n",
       "      <th>Away</th>\n",
       "      <th>Ascore</th>\n",
       "      <th>Hspread</th>\n",
       "      <th>HTotal</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>18</th>\n",
       "      <td>USF 106</td>\n",
       "      <td>63.65</td>\n",
       "      <td>Tulsa 85</td>\n",
       "      <td>63.40</td>\n",
       "      <td>0.25</td>\n",
       "      <td>127.05</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>Virginia 15</td>\n",
       "      <td>70.05</td>\n",
       "      <td>Wake Forest 105</td>\n",
       "      <td>57.12</td>\n",
       "      <td>12.93</td>\n",
       "      <td>127.17</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15</th>\n",
       "      <td>Boise State 68</td>\n",
       "      <td>76.68</td>\n",
       "      <td>Air Force 317</td>\n",
       "      <td>56.58</td>\n",
       "      <td>20.10</td>\n",
       "      <td>133.26</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>Syracuse 20</td>\n",
       "      <td>72.49</td>\n",
       "      <td>Pittsburgh 76</td>\n",
       "      <td>62.53</td>\n",
       "      <td>9.96</td>\n",
       "      <td>135.02</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>VCU 40</td>\n",
       "      <td>73.61</td>\n",
       "      <td>George Mason 185</td>\n",
       "      <td>61.46</td>\n",
       "      <td>12.15</td>\n",
       "      <td>135.07</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>Louisville 41</td>\n",
       "      <td>68.74</td>\n",
       "      <td>Virginia Tech 38</td>\n",
       "      <td>66.65</td>\n",
       "      <td>2.09</td>\n",
       "      <td>135.39</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>22</th>\n",
       "      <td>Wofford 122</td>\n",
       "      <td>70.29</td>\n",
       "      <td>UNCG 164</td>\n",
       "      <td>65.45</td>\n",
       "      <td>4.84</td>\n",
       "      <td>135.74</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>Houston 18</td>\n",
       "      <td>73.07</td>\n",
       "      <td>Wichita State 74</td>\n",
       "      <td>62.86</td>\n",
       "      <td>10.21</td>\n",
       "      <td>135.93</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>19</th>\n",
       "      <td>Butler 102</td>\n",
       "      <td>71.10</td>\n",
       "      <td>Georgetown 127</td>\n",
       "      <td>66.03</td>\n",
       "      <td>5.07</td>\n",
       "      <td>137.13</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16</th>\n",
       "      <td>South Carolina 77</td>\n",
       "      <td>73.44</td>\n",
       "      <td>Texas A&amp;M 129</td>\n",
       "      <td>65.88</td>\n",
       "      <td>7.56</td>\n",
       "      <td>139.32</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>Ole Miss 49</td>\n",
       "      <td>74.15</td>\n",
       "      <td>Auburn 96</td>\n",
       "      <td>66.40</td>\n",
       "      <td>7.75</td>\n",
       "      <td>140.55</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14</th>\n",
       "      <td>Utah State 67</td>\n",
       "      <td>76.61</td>\n",
       "      <td>New Mexico 267</td>\n",
       "      <td>65.27</td>\n",
       "      <td>11.34</td>\n",
       "      <td>141.88</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13</th>\n",
       "      <td>Richmond 61</td>\n",
       "      <td>74.65</td>\n",
       "      <td>URI 93</td>\n",
       "      <td>69.77</td>\n",
       "      <td>4.88</td>\n",
       "      <td>144.42</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>21</th>\n",
       "      <td>Abil. Christian 116</td>\n",
       "      <td>81.62</td>\n",
       "      <td>Houston Baptist 352</td>\n",
       "      <td>63.64</td>\n",
       "      <td>17.98</td>\n",
       "      <td>145.26</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>Tennessee 6</td>\n",
       "      <td>77.73</td>\n",
       "      <td>Arkansas 33</td>\n",
       "      <td>68.38</td>\n",
       "      <td>9.35</td>\n",
       "      <td>146.11</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>17</th>\n",
       "      <td>St. Bonaventure 84</td>\n",
       "      <td>77.49</td>\n",
       "      <td>Saint Joe's 158</td>\n",
       "      <td>68.83</td>\n",
       "      <td>8.66</td>\n",
       "      <td>146.32</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Michigan 5</td>\n",
       "      <td>77.85</td>\n",
       "      <td>Minnesota 25</td>\n",
       "      <td>69.24</td>\n",
       "      <td>8.61</td>\n",
       "      <td>147.09</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>24</th>\n",
       "      <td>Cent. Arkansas 207</td>\n",
       "      <td>79.03</td>\n",
       "      <td>New Orleans 312</td>\n",
       "      <td>69.17</td>\n",
       "      <td>9.86</td>\n",
       "      <td>148.20</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>Duke 34</td>\n",
       "      <td>79.96</td>\n",
       "      <td>Boston College 100</td>\n",
       "      <td>68.78</td>\n",
       "      <td>11.18</td>\n",
       "      <td>148.74</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>Creighton 14</td>\n",
       "      <td>77.06</td>\n",
       "      <td>Seton Hall 19</td>\n",
       "      <td>72.80</td>\n",
       "      <td>4.26</td>\n",
       "      <td>149.86</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>23</th>\n",
       "      <td>Chattanooga 183</td>\n",
       "      <td>77.23</td>\n",
       "      <td>Samford 197</td>\n",
       "      <td>73.66</td>\n",
       "      <td>3.57</td>\n",
       "      <td>150.89</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20</th>\n",
       "      <td>UMass 111</td>\n",
       "      <td>81.43</td>\n",
       "      <td>G. Washington 283</td>\n",
       "      <td>72.87</td>\n",
       "      <td>8.56</td>\n",
       "      <td>154.30</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>LSU 16</td>\n",
       "      <td>83.55</td>\n",
       "      <td>Georgia 80</td>\n",
       "      <td>71.44</td>\n",
       "      <td>12.11</td>\n",
       "      <td>154.99</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>Baylor 1</td>\n",
       "      <td>86.37</td>\n",
       "      <td>Oklahoma 45</td>\n",
       "      <td>69.64</td>\n",
       "      <td>16.73</td>\n",
       "      <td>156.01</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>Xavier 37</td>\n",
       "      <td>83.71</td>\n",
       "      <td>St. John's 104</td>\n",
       "      <td>72.84</td>\n",
       "      <td>10.87</td>\n",
       "      <td>156.55</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                   Home  HScore                 Away  Ascore  Hspread  HTotal\n",
       "18              USF 106   63.65             Tulsa 85   63.40     0.25  127.05\n",
       "4           Virginia 15   70.05      Wake Forest 105   57.12    12.93  127.17\n",
       "15       Boise State 68   76.68        Air Force 317   56.58    20.10  133.26\n",
       "7           Syracuse 20   72.49        Pittsburgh 76   62.53     9.96  135.02\n",
       "11               VCU 40   73.61     George Mason 185   61.46    12.15  135.07\n",
       "10        Louisville 41   68.74     Virginia Tech 38   66.65     2.09  135.39\n",
       "22          Wofford 122   70.29             UNCG 164   65.45     4.84  135.74\n",
       "6            Houston 18   73.07     Wichita State 74   62.86    10.21  135.93\n",
       "19           Butler 102   71.10       Georgetown 127   66.03     5.07  137.13\n",
       "16    South Carolina 77   73.44        Texas A&M 129   65.88     7.56  139.32\n",
       "12          Ole Miss 49   74.15            Auburn 96   66.40     7.75  140.55\n",
       "14        Utah State 67   76.61       New Mexico 267   65.27    11.34  141.88\n",
       "13          Richmond 61   74.65               URI 93   69.77     4.88  144.42\n",
       "21  Abil. Christian 116   81.62  Houston Baptist 352   63.64    17.98  145.26\n",
       "2           Tennessee 6   77.73          Arkansas 33   68.38     9.35  146.11\n",
       "17   St. Bonaventure 84   77.49      Saint Joe's 158   68.83     8.66  146.32\n",
       "1            Michigan 5   77.85         Minnesota 25   69.24     8.61  147.09\n",
       "24   Cent. Arkansas 207   79.03      New Orleans 312   69.17     9.86  148.20\n",
       "8               Duke 34   79.96   Boston College 100   68.78    11.18  148.74\n",
       "3          Creighton 14   77.06        Seton Hall 19   72.80     4.26  149.86\n",
       "23      Chattanooga 183   77.23          Samford 197   73.66     3.57  150.89\n",
       "20            UMass 111   81.43    G. Washington 283   72.87     8.56  154.30\n",
       "5                LSU 16   83.55           Georgia 80   71.44    12.11  154.99\n",
       "0              Baylor 1   86.37          Oklahoma 45   69.64    16.73  156.01\n",
       "9             Xavier 37   83.71       St. John's 104   72.84    10.87  156.55"
      ]
     },
     "execution_count": 33,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "HaslaF.sort_values('HTotal')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>team</th>\n",
       "      <th>score1</th>\n",
       "      <th>score2</th>\n",
       "      <th>Kspread</th>\n",
       "      <th>KTotal</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>134</th>\n",
       "      <td>Virginia</td>\n",
       "      <td>68</td>\n",
       "      <td>55</td>\n",
       "      <td>13</td>\n",
       "      <td>123</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>50</th>\n",
       "      <td>South Florida</td>\n",
       "      <td>63</td>\n",
       "      <td>62</td>\n",
       "      <td>1</td>\n",
       "      <td>125</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>190</th>\n",
       "      <td>Boise St.</td>\n",
       "      <td>72</td>\n",
       "      <td>57</td>\n",
       "      <td>15</td>\n",
       "      <td>129</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15</th>\n",
       "      <td>Louisville</td>\n",
       "      <td>67</td>\n",
       "      <td>64</td>\n",
       "      <td>3</td>\n",
       "      <td>131</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>113</th>\n",
       "      <td>Houston</td>\n",
       "      <td>73</td>\n",
       "      <td>62</td>\n",
       "      <td>11</td>\n",
       "      <td>135</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>99</th>\n",
       "      <td>VCU</td>\n",
       "      <td>72</td>\n",
       "      <td>66</td>\n",
       "      <td>6</td>\n",
       "      <td>138</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>43</th>\n",
       "      <td>South Carolina</td>\n",
       "      <td>71</td>\n",
       "      <td>67</td>\n",
       "      <td>4</td>\n",
       "      <td>138</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>176</th>\n",
       "      <td>Utah St.</td>\n",
       "      <td>76</td>\n",
       "      <td>63</td>\n",
       "      <td>13</td>\n",
       "      <td>139</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>36</th>\n",
       "      <td>Mississippi</td>\n",
       "      <td>72</td>\n",
       "      <td>67</td>\n",
       "      <td>5</td>\n",
       "      <td>139</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>106</th>\n",
       "      <td>Wofford</td>\n",
       "      <td>71</td>\n",
       "      <td>69</td>\n",
       "      <td>2</td>\n",
       "      <td>140</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>22</th>\n",
       "      <td>Tennessee</td>\n",
       "      <td>74</td>\n",
       "      <td>67</td>\n",
       "      <td>7</td>\n",
       "      <td>141</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>85</th>\n",
       "      <td>Butler</td>\n",
       "      <td>73</td>\n",
       "      <td>68</td>\n",
       "      <td>5</td>\n",
       "      <td>141</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>162</th>\n",
       "      <td>Nicholls St.</td>\n",
       "      <td>76</td>\n",
       "      <td>68</td>\n",
       "      <td>8</td>\n",
       "      <td>144</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>71</th>\n",
       "      <td>Syracuse</td>\n",
       "      <td>76</td>\n",
       "      <td>68</td>\n",
       "      <td>8</td>\n",
       "      <td>144</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>78</th>\n",
       "      <td>Syracuse</td>\n",
       "      <td>76</td>\n",
       "      <td>68</td>\n",
       "      <td>8</td>\n",
       "      <td>144</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>197</th>\n",
       "      <td>Abilene Christian</td>\n",
       "      <td>81</td>\n",
       "      <td>65</td>\n",
       "      <td>16</td>\n",
       "      <td>146</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>29</th>\n",
       "      <td>Richmond</td>\n",
       "      <td>75</td>\n",
       "      <td>71</td>\n",
       "      <td>4</td>\n",
       "      <td>146</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>141</th>\n",
       "      <td>Sam Houston St.</td>\n",
       "      <td>75</td>\n",
       "      <td>72</td>\n",
       "      <td>3</td>\n",
       "      <td>147</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>183</th>\n",
       "      <td>Northwestern St.</td>\n",
       "      <td>78</td>\n",
       "      <td>70</td>\n",
       "      <td>8</td>\n",
       "      <td>148</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>127</th>\n",
       "      <td>Duke</td>\n",
       "      <td>81</td>\n",
       "      <td>68</td>\n",
       "      <td>13</td>\n",
       "      <td>149</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>Creighton</td>\n",
       "      <td>77</td>\n",
       "      <td>72</td>\n",
       "      <td>5</td>\n",
       "      <td>149</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Michigan</td>\n",
       "      <td>78</td>\n",
       "      <td>73</td>\n",
       "      <td>5</td>\n",
       "      <td>151</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>57</th>\n",
       "      <td>Baylor</td>\n",
       "      <td>82</td>\n",
       "      <td>70</td>\n",
       "      <td>12</td>\n",
       "      <td>152</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>169</th>\n",
       "      <td>Central Arkansas</td>\n",
       "      <td>80</td>\n",
       "      <td>72</td>\n",
       "      <td>8</td>\n",
       "      <td>152</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>155</th>\n",
       "      <td>Chattanooga</td>\n",
       "      <td>80</td>\n",
       "      <td>73</td>\n",
       "      <td>7</td>\n",
       "      <td>153</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>148</th>\n",
       "      <td>St. Bonaventure</td>\n",
       "      <td>83</td>\n",
       "      <td>72</td>\n",
       "      <td>11</td>\n",
       "      <td>155</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>64</th>\n",
       "      <td>Xavier</td>\n",
       "      <td>81</td>\n",
       "      <td>75</td>\n",
       "      <td>6</td>\n",
       "      <td>156</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>120</th>\n",
       "      <td>Massachusetts</td>\n",
       "      <td>80</td>\n",
       "      <td>76</td>\n",
       "      <td>4</td>\n",
       "      <td>156</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>92</th>\n",
       "      <td>LSU</td>\n",
       "      <td>84</td>\n",
       "      <td>74</td>\n",
       "      <td>10</td>\n",
       "      <td>158</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                  team  score1  score2  Kspread  KTotal\n",
       "134           Virginia      68      55       13     123\n",
       "50       South Florida      63      62        1     125\n",
       "190          Boise St.      72      57       15     129\n",
       "15          Louisville      67      64        3     131\n",
       "113            Houston      73      62       11     135\n",
       "99                 VCU      72      66        6     138\n",
       "43      South Carolina      71      67        4     138\n",
       "176           Utah St.      76      63       13     139\n",
       "36         Mississippi      72      67        5     139\n",
       "106            Wofford      71      69        2     140\n",
       "22           Tennessee      74      67        7     141\n",
       "85              Butler      73      68        5     141\n",
       "162       Nicholls St.      76      68        8     144\n",
       "71            Syracuse      76      68        8     144\n",
       "78            Syracuse      76      68        8     144\n",
       "197  Abilene Christian      81      65       16     146\n",
       "29            Richmond      75      71        4     146\n",
       "141    Sam Houston St.      75      72        3     147\n",
       "183   Northwestern St.      78      70        8     148\n",
       "127               Duke      81      68       13     149\n",
       "8            Creighton      77      72        5     149\n",
       "1             Michigan      78      73        5     151\n",
       "57              Baylor      82      70       12     152\n",
       "169   Central Arkansas      80      72        8     152\n",
       "155        Chattanooga      80      73        7     153\n",
       "148    St. Bonaventure      83      72       11     155\n",
       "64              Xavier      81      75        6     156\n",
       "120      Massachusetts      80      76        4     156\n",
       "92                 LSU      84      74       10     158"
      ]
     },
     "execution_count": 34,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "Kenpom.sort_values('KTotal')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "celltoolbar": "Raw Cell Format",
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.8.5"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 4
}