Update PitchPlotFunctions.py

PitchPlotFunctions.py

@@ -1,622 +1,623 @@
-import polars as pl
-import numpy as np
-import matplotlib.pyplot as plt
-import seaborn as sns
-from PIL import Image
-import requests
-from io import BytesIO
-from matplotlib.offsetbox import OffsetImage, AnnotationBbox
-from matplotlib.ticker import FuncFormatter
-import matplotlib.transforms as transforms
-from matplotlib.patches import Ellipse
-import matplotlib.gridspec as gridspec
-import matplotlib.patches as mpatches
-import matplotlib.lines as mlines
-from matplotlib.figure import Figure
-import streamlit as st
-import api_scraper
-
-# Initialize the scraper
-scraper = api_scraper.MLB_Scrape()
-
-class PitchPlotFunctions:
-    # Define the pitch_colours method
-    def pitch_colours(self):
-        # Dictionary of pitch types and their corresponding colors and names
-        pitch_colours = {
-            'FF': {'colour': '#FF007D', 'name': '4-Seam Fastball'},
-            'FA': {'colour': '#FF007D', 'name': 'Fastball'},
-            'SI': {'colour': '#98165D', 'name': 'Sinker'},
-            'FC': {'colour': '#BE5FA0', 'name': 'Cutter'},
-            'CH': {'colour': '#F79E70', 'name': 'Changeup'},
-            'FS': {'colour': '#FE6100', 'name': 'Splitter'},
-            'SC': {'colour': '#F08223', 'name': 'Screwball'},
-            'FO': {'colour': '#FFB000', 'name': 'Forkball'},
-            'SL': {'colour': '#67E18D', 'name': 'Slider'},
-            'ST': {'colour': '#1BB999', 'name': 'Sweeper'},
-            'SV': {'colour': '#376748', 'name': 'Slurve'},
-            'KC': {'colour': '#311D8B', 'name': 'Knuckle Curve'},
-            'CU': {'colour': '#3025CE', 'name': 'Curveball'},
-            'CS': {'colour': '#274BFC', 'name': 'Slow Curve'},
-            'EP': {'colour': '#648FFF', 'name': 'Eephus'},
-            'KN': {'colour': '#867A08', 'name': 'Knuckleball'},
-            'PO': {'colour': '#472C30', 'name': 'Pitch Out'},
-            'UN': {'colour': '#9C8975', 'name': 'Unknown'},
-        }
-
-        # Create dictionaries mapping pitch types to their colors and names
-        dict_colour = dict(zip(pitch_colours.keys(), [pitch_colours[key]['colour'] for key in pitch_colours]))
-        dict_pitch = dict(zip(pitch_colours.keys(), [pitch_colours[key]['name'] for key in pitch_colours]))
-
-        return dict_colour, dict_pitch
-
-    # Define the sns_custom_theme method
-    def sns_custom_theme(self):
-        # Custom theme for seaborn plots
-        custom_theme = {
-            "axes.facecolor": "white",
-            "axes.edgecolor": ".8",
-            "axes.grid": True,
-            "axes.axisbelow": True,
-            "axes.labelcolor": ".15",
-            "figure.facecolor": "#f9f9f9",
-            "grid.color": ".8",
-            "grid.linestyle": "-",
-            "text.color": ".15",
-            "xtick.color": ".15",
-            "ytick.color": ".15",
-            "xtick.direction": "out",
-            "ytick.direction": "out",
-            "lines.solid_capstyle": "round",
-            "patch.edgecolor": "w",
-            "patch.force_edgecolor": True,
-            "image.cmap": "rocket",
-            "font.family": ["sans-serif"],
-            "font.sans-serif": ["Arial", "DejaVu Sans", "Liberation Sans", "Bitstream Vera Sans", "sans-serif"],
-            "xtick.bottom": False,
-            "xtick.top": False,
-            "ytick.left": False,
-            "ytick.right": False,
-            "axes.spines.left": True,
-            "axes.spines.bottom": True,
-            "axes.spines.right": True,
-            "axes.spines.top": True
-        }
-
-        # Color palette for the plots
-        colour_palette = ['#FFB000', '#648FFF', '#785EF0', '#DC267F', '#FE6100', '#3D1EB2', '#894D80', '#16AA02', '#B5592B', '#A3C1ED']
-
-        return custom_theme, colour_palette
-
-    # Define the sport_id_dict method
-    def sport_id_dict(self):
-        # Dictionary mapping sport IDs to their names
-        dict = {1: 'MLB', 11: 'AAA'}
-        return dict
-
-    # Define the team_logos method
-    def team_logos(self):
-        # List of MLB teams and their corresponding ESPN logo URLs
-        mlb_teams = [
-            {"team": "AZ", "logo_url": "https://a.espncdn.com/combiner/i?img=/i/teamlogos/mlb/500/scoreboard/ari.png&h=500&w=500"},
-            {"team": "ATL", "logo_url": "https://a.espncdn.com/combiner/i?img=/i/teamlogos/mlb/500/scoreboard/atl.png&h=500&w=500"},
-            {"team": "BAL", "logo_url": "https://a.espncdn.com/combiner/i?img=/i/teamlogos/mlb/500/scoreboard/bal.png&h=500&w=500"},
-            {"team": "BOS", "logo_url": "https://a.espncdn.com/combiner/i?img=/i/teamlogos/mlb/500/scoreboard/bos.png&h=500&w=500"},
-            {"team": "CHC", "logo_url": "https://a.espncdn.com/combiner/i?img=/i/teamlogos/mlb/500/scoreboard/chc.png&h=500&w=500"},
-            {"team": "CWS", "logo_url": "https://a.espncdn.com/combiner/i?img=/i/teamlogos/mlb/500/scoreboard/chw.png&h=500&w=500"},
-            {"team": "CIN", "logo_url": "https://a.espncdn.com/combiner/i?img=/i/teamlogos/mlb/500/scoreboard/cin.png&h=500&w=500"},
-            {"team": "CLE", "logo_url": "https://a.espncdn.com/combiner/i?img=/i/teamlogos/mlb/500/scoreboard/cle.png&h=500&w=500"},
-            {"team": "COL", "logo_url": "https://a.espncdn.com/combiner/i?img=/i/teamlogos/mlb/500/scoreboard/col.png&h=500&w=500"},
-            {"team": "DET", "logo_url": "https://a.espncdn.com/combiner/i?img=/i/teamlogos/mlb/500/scoreboard/det.png&h=500&w=500"},
-            {"team": "HOU", "logo_url": "https://a.espncdn.com/combiner/i?img=/i/teamlogos/mlb/500/scoreboard/hou.png&h=500&w=500"},
-            {"team": "KC", "logo_url": "https://a.espncdn.com/combiner/i?img=/i/teamlogos/mlb/500/scoreboard/kc.png&h=500&w=500"},
-            {"team": "LAA", "logo_url": "https://a.espncdn.com/combiner/i?img=/i/teamlogos/mlb/500/scoreboard/laa.png&h=500&w=500"},
-            {"team": "LAD", "logo_url": "https://a.espncdn.com/combiner/i?img=/i/teamlogos/mlb/500/scoreboard/lad.png&h=500&w=500"},
-            {"team": "MIA", "logo_url": "https://a.espncdn.com/combiner/i?img=/i/teamlogos/mlb/500/scoreboard/mia.png&h=500&w=500"},
-            {"team": "MIL", "logo_url": "https://a.espncdn.com/combiner/i?img=/i/teamlogos/mlb/500/scoreboard/mil.png&h=500&w=500"},
-            {"team": "MIN", "logo_url": "https://a.espncdn.com/combiner/i?img=/i/teamlogos/mlb/500/scoreboard/min.png&h=500&w=500"},
-            {"team": "NYM", "logo_url": "https://a.espncdn.com/combiner/i?img=/i/teamlogos/mlb/500/scoreboard/nym.png&h=500&w=500"},
-            {"team": "NYY", "logo_url": "https://a.espncdn.com/combiner/i?img=/i/teamlogos/mlb/500/scoreboard/nyy.png&h=500&w=500"},
-            {"team": "OAK", "logo_url": "https://a.espncdn.com/combiner/i?img=/i/teamlogos/mlb/500/scoreboard/oak.png&h=500&w=500"},
-            {"team": "PHI", "logo_url": "https://a.espncdn.com/combiner/i?img=/i/teamlogos/mlb/500/scoreboard/phi.png&h=500&w=500"},
-            {"team": "PIT", "logo_url": "https://a.espncdn.com/combiner/i?img=/i/teamlogos/mlb/500/scoreboard/pit.png&h=500&w=500"},
-            {"team": "SD", "logo_url": "https://a.espncdn.com/combiner/i?img=/i/teamlogos/mlb/500/scoreboard/sd.png&h=500&w=500"},
-            {"team": "SF", "logo_url": "https://a.espncdn.com/combiner/i?img=/i/teamlogos/mlb/500/scoreboard/sf.png&h=500&w=500"},
-            {"team": "SEA", "logo_url": "https://a.espncdn.com/combiner/i?img=/i/teamlogos/mlb/500/scoreboard/sea.png&h=500&w=500"},
-            {"team": "STL", "logo_url": "https://a.espncdn.com/combiner/i?img=/i/teamlogos/mlb/500/scoreboard/stl.png&h=500&w=500"},
-            {"team": "TB", "logo_url": "https://a.espncdn.com/combiner/i?img=/i/teamlogos/mlb/500/scoreboard/tb.png&h=500&w=500"},
-            {"team": "TEX", "logo_url": "https://a.espncdn.com/combiner/i?img=/i/teamlogos/mlb/500/scoreboard/tex.png&h=500&w=500"},
-            {"team": "TOR", "logo_url": "https://a.espncdn.com/combiner/i?img=/i/teamlogos/mlb/500/scoreboard/tor.png&h=500&w=500"},
-            {"team": "WSH", "logo_url": "https://a.espncdn.com/combiner/i?img=/i/teamlogos/mlb/500/scoreboard/wsh.png&h=500&w=500"}
-        ]
-
-        # Create a DataFrame from the list of dictionaries
-        df_image = pl.DataFrame(mlb_teams)
-        # Set the index to 'team' and convert 'logo_url' to a dictionary
-        image_dict = df_image.select(['team', 'logo_url']).to_dict(as_series=False)['logo_url']
-
-        # Convert to the desired dictionary format
-        image_dict = {row['team']: row['logo_url'] for row in df_image.select(['team', 'logo_url']).to_dicts()}
-
-        return image_dict
-
-    # Function to get an image from a URL and display it on the given axis
-    def player_headshot(self, pitcher_id: str, ax: plt.Axes, sport_id: int):
-        """
-        Fetches and displays the player's headshot image on the given axis.
-
-        Parameters:
-        pitcher_id (str): The ID of the pitcher.
-        ax (plt.Axes): The matplotlib axis to display the image on.
-        sport_id (int): The sport ID to determine the URL format.
-        """
-        # Construct the URL for the player's headshot image
-        if sport_id == 1:
-            url = f'https://img.mlbstatic.com/mlb-photos/image/'\
-                  f'upload/d_people:generic:headshot:67:current.png'\
-                  f'/w_640,q_auto:best/v1/people/{pitcher_id}/headshot/silo/current.png'
-        else:
-            url = f'https://img.mlbstatic.com/mlb-photos/image/upload/c_fill,g_auto/w_640/v1/people/{pitcher_id}/headshot/milb/current.png'
-        
-        # Send a GET request to the URL
-        response = requests.get(url)
-        # Open the image from the response content
-        img = Image.open(BytesIO(response.content))
-        # Display the image on the axis
-        ax.set_xlim(0, 2)
-        ax.set_ylim(0, 1)
-        ax.imshow(img, extent=[0.0, 1, 0, 1], origin='upper')
-        # Turn off the axis
-        ax.axis('off')
-
-    # Function to display player bio information on the given axis
-    def player_bio(self, pitcher_id: str, ax: plt.Axes, start_date: str, end_date: str, batter_hand: list):
-        """
-        Fetches and displays the player's bio information on the given axis.
-
-        Parameters:
-        pitcher_id (str): The ID of the pitcher.
-        ax (plt.Axes): The matplotlib axis to display the bio information on.
-        start_date (str): The start date for the bio information.
-        end_date (str): The end date for the bio information.
-        batter_hand (list): The list of batter hands (e.g., ['R'] or ['L']).
-        """
-        # Construct the URL to fetch player data
-        url = f"https://statsapi.mlb.com/api/v1/people?personIds={pitcher_id}&hydrate=currentTeam"
-        # Send a GET request to the URL and parse the JSON response
-        data = requests.get(url).json()
-        # Extract player information from the JSON data
-        player_name = data['people'][0]['fullName']
-        pitcher_hand = data['people'][0]['pitchHand']['code']
-        age = data['people'][0]['currentAge']
-        height = data['people'][0]['height']
-        weight = data['people'][0]['weight']
-        # Display the player's name, handedness, age, height, and weight on the axis
-        ax.text(0.5, 1, f'{player_name}', va='top', ha='center', fontsize=48)
-        ax.text(0.5, 0.6, f'{pitcher_hand}HP, Age: {age}, {height}/{weight}', va='top', ha='center', fontsize=22)
-        # Determine the batter hand text
-        if batter_hand == ['R']:
-            batter_hand_text = ', vs RHH'
-        elif batter_hand == ['L']:
-            batter_hand_text = ', vs LHH'
-        else:
-            batter_hand_text = ''
-        ax.text(0.5, 0.35, f'{start_date} to {end_date}{batter_hand_text}', va='top', ha='center', fontsize=22, fontstyle='italic')
-        # Turn off the axis
-        ax.axis('off')
-
-    # Function to display the team logo on the given axis
-    def plot_logo(self, pitcher_id: str, ax: plt.Axes):
-        """
-        Fetches and displays the team logo on the given axis.
-
-        Parameters:
-        pitcher_id (str): The ID of the pitcher.
-        ax (plt.Axes): The matplotlib axis to display the logo on.
-        """
-        # Construct the URL to fetch player data
-        url = f"https://statsapi.mlb.com/api/v1/people?personIds={pitcher_id}&hydrate=currentTeam"
-        # Send a GET request to the URL and parse the JSON response
-        data = requests.get(url).json()
-        # Construct the URL to fetch team data
-        url_team = 'https://statsapi.mlb.com/' + data['people'][0]['currentTeam']['link']
-        # Send a GET request to the team URL and parse the JSON response
-        data_team = requests.get(url_team).json()
-        # Get the logo URL from the image dictionary using the team abbreviation
-        try:
-            if data_team['teams'][0]['sport']['id'] == 1:
-                team_abb = data_team['teams'][0]['abbreviation']
-                logo_url = self.team_logos()[team_abb]
-            else:
-                team_abb = data_team['teams'][0]['parentOrgId']
-                logo_url = self.team_logos()[dict(scraper.get_teams().select(['team_id', 'parent_org_abbreviation']).iter_rows())[team_abb]]
-        except KeyError:
-            logo_url = "https://a.espncdn.com/combiner/i?img=/i/teamlogos/leagues/500/mlb.png?w=500&h=500&transparent=true"
-        # Send a GET request to the logo URL
-        response = requests.get(logo_url)
-        # Open the image from the response content
-        img = Image.open(BytesIO(response.content))
-        # Display the image on the axis
-        ax.set_xlim(0, 2)
-        ax.set_ylim(0, 1)
-        ax.imshow(img, extent=[1, 2, 0, 1], origin='upper')
-        # Turn off the axis
-        ax.axis('off')
-
-    ### PITCH ELLIPSE ###
-    def confidence_ellipse( self,
-                            x:np.array,
-                            y:np.array, 
-                            ax:plt.Axes, 
-                            n_std:float=3.0,
-                            facecolor:str='none',
-                            **kwargs):
-        """
-        Create a plot of the covariance confidence ellipse of *x* and *y*.
-        Parameters
-        ----------
-        x, y : array-like, shape (n, )
-            Input data.
-        ax : matplotlib.axes.Axes
-            The axes object to draw the ellipse into.
-        n_std : float
-            The number of standard deviations to determine the ellipse's radiuses.
-        **kwargs
-            Forwarded to `~matplotlib.patches.Ellipse`
-        Returns
-        -------
-        matplotlib.patches.Ellipse
-        """
-        
-        if x.shape != y.shape:
-            raise ValueError("x and y must be the same size")
-        try:
-            cov = np.cov(x, y)
-            pearson = cov[0, 1]/np.sqrt(cov[0, 0] * cov[1, 1])
-            # Using a special case to obtain the eigenvalues of this
-            # two-dimensional dataset.
-            ell_radius_x = np.sqrt(1 + pearson)
-            ell_radius_y = np.sqrt(1 - pearson)
-            ellipse = Ellipse((0, 0), width=ell_radius_x * 2, height=ell_radius_y * 2,
-                            facecolor=facecolor,linewidth=2,linestyle='--', **kwargs)
-            
-
-            # Calculating the standard deviation of x from
-            # the squareroot of the variance and multiplying
-            # with the given number of standard deviations.
-            scale_x = np.sqrt(cov[0, 0]) * n_std
-            mean_x = x.mean()
-            
-
-            # calculating the standard deviation of y ...
-            scale_y = np.sqrt(cov[1, 1]) * n_std
-            mean_y = y.mean()
-            
-
-            transf = transforms.Affine2D() \
-                .rotate_deg(45) \
-                .scale(scale_x, scale_y) \
-                .translate(mean_x, mean_y)
-            
-            
-
-            ellipse.set_transform(transf + ax.transData)
-        except ValueError:
-            return    
-            
-        return ax.add_patch(ellipse)
-
-    
-    def break_plot_big(self, df: pl.DataFrame, ax: plt.Axes, sport_id: int):
-        """
-        Plots a big break plot for the given DataFrame on the provided axis.
-
-        Parameters:
-        df (pl.DataFrame): The DataFrame containing pitch data.
-        ax (plt.Axes): The matplotlib axis to plot on.
-        sport_id (int): The sport ID to determine the plot title.
-        """
-        # Set font properties for different elements of the plot
-        font_properties = {'size': 20}
-        font_properties_titles = {'size': 32}
-        font_properties_axes = {'size': 24}
-        
-        # Get unique pitch types sorted by 'prop' and 'pitch_type'
-        label_labels = df.sort(by=['prop', 'pitch_type'], descending=[False, True])['pitch_type'].unique()
-        j = 0
-        dict_colour, dict_pitch = self.pitch_colours()
-        custom_theme, colour_palette = self.sns_custom_theme()
-        
-        # Loop through each pitch type and plot confidence ellipses
-        for label in label_labels:
-            subset = df.filter(pl.col('pitch_type') == label)
-            if len(subset) > 4:
-                try:
-                    if df['pitcher_hand'][0] == 'R':
-                        self.confidence_ellipse(subset['hb'], subset['ivb'], ax=ax, edgecolor=dict_colour[label], n_std=2, facecolor=dict_colour[label], alpha=0.2)
-                    if df['pitcher_hand'][0] == 'L':
-                        self.confidence_ellipse(subset['hb'] * -1, subset['ivb'], ax=ax, edgecolor=dict_colour[label], n_std=2, facecolor=dict_colour[label], alpha=0.2)
-                except ValueError:
-                    return
-                j += 1
-            else:
-                j += 1
-        
-        # Plot scatter plot of pitch data
-        if df['pitcher_hand'][0] == 'R':
-            sns.scatterplot(ax=ax, x=df['hb'] * 1, y=df['ivb'] * 1, hue=df['pitch_type'], palette=dict_colour, ec='black', alpha=1, zorder=2, s=50)
-        if df['pitcher_hand'][0] == 'L':
-            sns.scatterplot(ax=ax, x=df['hb'] * -1, y=df['ivb'] * 1, hue=df['pitch_type'], palette=dict_colour, ec='black', alpha=1, zorder=2, s=50)
-        
-        # Set plot limits and labels
-        ax.set_xlim((-25, 25))
-        ax.set_ylim((-25, 25))
-        ax.hlines(y=0, xmin=-50, xmax=50, color=colour_palette[8], alpha=0.5, linestyles='--', zorder=1)
-        ax.vlines(x=0, ymin=-50, ymax=50, color=colour_palette[8], alpha=0.5, linestyles='--', zorder=1)
-        ax.set_xlabel('Horizontal Break (in)', fontdict=font_properties_axes)
-        ax.set_ylabel('Induced Vertical Break (in)', fontdict=font_properties_axes)
-        ax.set_title(f"{self.sport_id_dict()[sport_id]} - Short Form Pitch Movement Plot", fontdict=font_properties_titles)
-        
-        # Remove legend and set tick labels
-        ax.get_legend().remove()
-        ax.set_xticklabels(ax.get_xticks(), fontdict=font_properties)
-        ax.set_yticklabels(ax.get_yticks(), fontdict=font_properties)
-        
-        # Add text annotations based on pitcher hand
-        if df['pitcher_hand'][0] == 'R':
-            ax.text(-24.5, -24.5, s='← Glove Side', fontstyle='italic', ha='left', va='bottom', bbox=dict(facecolor='white', edgecolor='black'), fontsize=16, zorder=3)
-            ax.text(24.5, -24.5, s='Arm Side →', fontstyle='italic', ha='right', va='bottom', bbox=dict(facecolor='white', edgecolor='black'), fontsize=16, zorder=3)
-        if df['pitcher_hand'][0] == 'L':
-            ax.invert_xaxis()
-            ax.text(24.5, -24.5, s='← Arm Side', fontstyle='italic', ha='left', va='bottom', bbox=dict(facecolor='white', edgecolor='black'), fontsize=16, zorder=3)
-            ax.text(-24.5, -24.5, s='Glove Side →', fontstyle='italic', ha='right', va='bottom', bbox=dict(facecolor='white', edgecolor='black'), fontsize=16, zorder=3)
-        
-        # Set aspect ratio and format tick labels
-        ax.set_aspect('equal', adjustable='box')
-        ax.xaxis.set_major_formatter(FuncFormatter(lambda x, _: int(x)))
-        ax.yaxis.set_major_formatter(FuncFormatter(lambda x, _: int(x)))
-
-    ### BREAK PLOT ###
-    def break_plot_big_long(self, df: pl.DataFrame, ax: plt.Axes, sport_id: int):
-        """
-        Plots a long break plot for the given DataFrame on the provided axis.
-
-        Parameters:
-        df (pl.DataFrame): The DataFrame containing pitch data.
-        ax (plt.Axes): The matplotlib axis to plot on.
-        sport_id (int): The sport ID to determine the plot title.
-        """
-        # Set font properties for different elements of the plot
-        font_properties = {'size': 20}
-        font_properties_titles = {'size': 32}
-        font_properties_axes = {'size': 24}
-        
-        # Get unique pitch types sorted by 'prop' and 'pitch_type'
-        label_labels = df.sort(by=['prop', 'pitch_type'], descending=[False, True])['pitch_type'].unique()
-        dict_colour, dict_pitch = self.pitch_colours()
-        custom_theme, colour_palette = self.sns_custom_theme()
-        j = 0
-        
-        # Loop through each pitch type and plot confidence ellipses
-        for label in label_labels:
-            subset = df.filter(pl.col('pitch_type') == label)
-            print(label)
-            if len(subset) > 4:
-                try:
-                    if df['pitcher_hand'][0] == 'R':
-                        self.confidence_ellipse(subset['hb'], subset['vb'], ax=ax, edgecolor=dict_colour[label], n_std=2, facecolor=dict_colour[label], alpha=0.2)
-                    if df['pitcher_hand'][0] == 'L':
-                        self.confidence_ellipse(subset['hb'] * -1, subset['vb'], ax=ax, edgecolor=dict_colour[label], n_std=2, facecolor=dict_colour[label], alpha=0.2)
-                except ValueError:
-                    return
-                j += 1
-            else:
-                j += 1
-        
-        # Plot scatter plot of pitch data
-        if df['pitcher_hand'][0] == 'R':
-            sns.scatterplot(ax=ax, x=df['hb'] * 1, y=df['vb'] * 1, hue=df['pitch_type'], palette=dict_colour, ec='black', alpha=1, zorder=2, s=50)
-        if df['pitcher_hand'][0] == 'L':
-            sns.scatterplot(ax=ax, x=df['hb'] * -1, y=df['vb'] * 1, hue=df['pitch_type'], palette=dict_colour, ec='black', alpha=1, zorder=2, s=50)
-        
-        # Set plot limits and labels
-        ax.set_xlim((-40, 40))
-        ax.set_ylim((-80, 0))
-        ax.axhline(y=0, color=colour_palette[8], alpha=0.5, linestyle='--', zorder=1)
-        ax.axvline(x=0, color=colour_palette[8], alpha=0.5, linestyle='--', zorder=1)
-        ax.set_xlabel('Horizontal Break (in)', fontdict=font_properties_axes)
-        ax.set_ylabel('Vertical Break (in)', fontdict=font_properties_axes)
-        ax.set_title(f"{self.sport_id_dict()[sport_id]} - Long Form Pitch Movement Plot", fontdict=font_properties_titles)
-        
-        # Remove legend and set tick labels
-        ax.get_legend().remove()
-        ax.set_xticklabels(ax.get_xticks(), fontdict=font_properties)
-        ax.set_yticklabels(ax.get_yticks(), fontdict=font_properties)
-        
-        # Add text annotations based on pitcher hand
-        if df['pitcher_hand'][0] == 'R':
-            ax.text(-39.5, -79.5, s='← Glove Side', fontstyle='italic', ha='left', va='bottom', bbox=dict(facecolor='white', edgecolor='black'), fontsize=16, zorder=3)
-            ax.text(39.5, -79.5, s='Arm Side →', fontstyle='italic', ha='right', va='bottom', bbox=dict(facecolor='white', edgecolor='black'), fontsize=16, zorder=3)
-        if df['pitcher_hand'][0] == 'L':
-            ax.invert_xaxis()
-            ax.text(39.5, -79.5, s='← Arm Side', fontstyle='italic', ha='left', va='bottom', bbox=dict(facecolor='white', edgecolor='black'), fontsize=16, zorder=3)
-            ax.text(-39.5, -79.5, s='Glove Side →', fontstyle='italic', ha='right', va='bottom', bbox=dict(facecolor='white', edgecolor='black'), fontsize=16, zorder=3)
-        
-        # Set aspect ratio and format tick labels
-        ax.set_aspect('equal', adjustable='box')
-        ax.xaxis.set_major_formatter(FuncFormatter(lambda x, _: int(x)))
-        ax.yaxis.set_major_formatter(FuncFormatter(lambda x, _: int(x)))
-
-    ### BREAK PLOT ###
-    def release_point_plot(self, df: pl.DataFrame, ax: plt.Axes, sport_id: int):
-        """
-        Plots the release points for the given DataFrame on the provided axis.
-
-        Parameters:
-        df (pl.DataFrame): The DataFrame containing pitch data.
-        ax (plt.Axes): The matplotlib axis to plot on.
-        sport_id (int): The sport ID to determine the plot title.
-        """
-        # Set font properties for different elements of the plot
-        font_properties = {'size': 20}
-        font_properties_titles = {'size': 32}
-        font_properties_axes = {'size': 24}
-        dict_colour, dict_pitch = self.pitch_colours()
-        custom_theme, colour_palette = self.sns_custom_theme()
-        
-        # Plot scatter plot of release points based on pitcher hand
-        if df['pitcher_hand'][0] == 'R':
-            sns.scatterplot(ax=ax, x=df['x0'] * -1, y=df['z0'] * 1, hue=df['pitch_type'], palette=dict_colour, ec='black', alpha=1, zorder=2, s=50)
-        if df['pitcher_hand'][0] == 'L':
-            sns.scatterplot(ax=ax, x=df['x0'] * 1, y=df['z0'] * 1, hue=df['pitch_type'], palette=dict_colour, ec='black', alpha=1, zorder=2, s=50)
-        
-        # Add patches to the plot
-        ax.add_patch(plt.Circle((0, 10 / 12 - 18), radius=18, edgecolor='black', facecolor='#a63b17'))
-        ax.add_patch(plt.Rectangle((-0.5, 9 / 12), 1, 1 / 6, edgecolor='black', facecolor='white'))
-        
-        # Set plot limits and labels
-        ax.set_xlim((-4, 4))
-        ax.set_ylim((0, 8))
-        ax.axhline(y=0, color=colour_palette[8], alpha=0.5, linestyle='--', zorder=1)
-        ax.axvline(x=0, color=colour_palette[8], alpha=0.5, linestyle='--', zorder=1)
-        ax.set_ylabel('Vertical Release (ft)', fontdict=font_properties_axes)
-        ax.set_xlabel('Horizontal Release (ft)', fontdict=font_properties_axes)
-        ax.set_title(f"{self.sport_id_dict()[sport_id]} - Release Points Catcher Perspective", fontdict=font_properties_titles)
-        
-        # Remove legend and set tick labels
-        ax.get_legend().remove()
-        ax.set_xticklabels(ax.get_xticks(), fontdict=font_properties)
-        ax.set_yticklabels(ax.get_yticks(), fontdict=font_properties)
-        
-        # Add text annotations based on pitcher hand
-        if df['pitcher_hand'][0] == 'L':
-            ax.text(-3.95, 0.05, s='← Glove Side', fontstyle='italic', ha='left', va='bottom', bbox=dict(facecolor='white', edgecolor='black'), fontsize=16, zorder=3)
-            ax.text(3.95, 0.05, s='Arm Side →', fontstyle='italic', ha='right', va='bottom', bbox=dict(facecolor='white', edgecolor='black'), fontsize=16, zorder=3)
-        if df['pitcher_hand'][0] == 'R':
-            ax.invert_xaxis()
-            ax.text(3.95, 0.05, s='← Arm Side', fontstyle='italic', ha='left', va='bottom', bbox=dict(facecolor='white', edgecolor='black'), fontsize=16, zorder=3)
-            ax.text(-3.95, 0.05, s='Glove Side →', fontstyle='italic', ha='right', va='bottom', bbox=dict(facecolor='white', edgecolor='black'), fontsize=16, zorder=3)
-        
-        # Set aspect ratio and format tick labels
-        ax.set_aspect('equal', adjustable='box')
-        ax.xaxis.set_major_formatter(FuncFormatter(lambda x, _: int(x)))
-        ax.yaxis.set_major_formatter(FuncFormatter(lambda x, _: int(x)))
-
-    def df_to_polars(self, df_original: pl.DataFrame, pitcher_id: str, start_date: str, end_date: str, batter_hand: list):
-        """
-        Filters and processes the original DataFrame to a Polars DataFrame.
-
-        Parameters:
-        df_original (pl.DataFrame): The original DataFrame containing pitch data.
-        pitcher_id (str): The ID of the pitcher.
-        start_date (str): The start date for filtering the data.
-        end_date (str): The end date for filtering the data.
-        batter_hand (list): The list of batter hands (e.g., ['R'] or ['L']).
-
-        Returns:
-        pl.DataFrame: The filtered and processed Polars DataFrame.
-        """
-        df = df_original.clone()
-        df = df.filter((pl.col('pitcher_id') == pitcher_id) & 
-                       (pl.col('is_pitch')) & (pl.col('pitch_type').is_not_null()) &
-                       (pl.col('pitch_type') != 'NaN') &
-                       (pl.col('game_date') >= start_date) &
-                       (pl.col('game_date') <= end_date) &
-                       (pl.col('batter_hand').is_in(batter_hand)))
-        df = df.with_columns(
-            prop_percent=(pl.col('is_pitch') / pl.col('is_pitch').sum()).over("pitch_type"),
-            prop=pl.col('is_pitch').sum().over("pitch_type")
-        )
-        return df
-    
-    def final_plot(self, df: pl.DataFrame, pitcher_id: str, plot_picker: str, sport_id: int):
-        """
-        Creates a final plot with player headshot, bio, logo, and pitch movement plots.
-
-        Parameters:
-        df (pl.DataFrame): The DataFrame containing pitch data.
-        pitcher_id (str): The ID of the pitcher.
-        plot_picker (str): The type of plot to create ('short_form_movement', 'long_form_movement', 'release_point').
-        sport_id (int): The sport ID to determine the plot title.
-        """
-        # Set the theme for seaborn plots
-        sns.set_theme(style="whitegrid", rc=self.sns_custom_theme()[0])
-        
-        # Create a figure and a gridspec with 6 rows and 5 columns
-        fig = plt.figure(figsize=(16, 16), dpi=400)
-        gs = gridspec.GridSpec(6, 5, figure=fig, height_ratios=[0.00000000005, 5, 30, 5, 2, 0.00000000005], width_ratios=[1, 10, 10, 10, 1])
-
-        # Create subplots for player headshot, bio, and logo
-        ax_headshot = fig.add_subplot(gs[1, 1])
-        ax_bio = fig.add_subplot(gs[1, 2])
-        ax_logo = fig.add_subplot(gs[1, 3])
-
-        # Get the start and end dates and unique batter hands from the DataFrame
-        start_date = df['game_date'].min()
-        end_date = df['game_date'].max()
-        batter_hand = list(df['batter_hand'].unique())
-
-        # Plot player headshot, bio, and logo
-        self.player_headshot(pitcher_id=pitcher_id, ax=ax_headshot, sport_id=sport_id)
-        self.player_bio(pitcher_id=pitcher_id, ax=ax_bio, start_date=start_date, end_date=end_date, batter_hand=batter_hand)
-        self.plot_logo(pitcher_id=pitcher_id, ax=ax_logo)
-
-        # Create subplot for the main plot
-        ax_main_plot = fig.add_subplot(gs[2, :])
-
-        # Create subplot for the legend
-        ax_legend = fig.add_subplot(gs[3, :])
-        ax_legend.axis('off')
-
-        # Create subplot for the footer
-        ax_footer = fig.add_subplot(gs[-2, :])
-
-        # Plot the selected pitch movement plot
-        if plot_picker == 'short_form_movement':
-            self.break_plot_big(df, ax_main_plot, sport_id=sport_id)
-        elif plot_picker == 'long_form_movement':
-            self.break_plot_big_long(df, ax_main_plot, sport_id=sport_id)
-        elif plot_picker == 'release_point':
-            self.release_point_plot(df, ax_main_plot, sport_id=sport_id)
-
-        # Sort the DataFrame and get unique pitch types
-        items_in_order = list(df.sort(by=['prop', 'pitch_type'], descending=[True, True])['pitch_type'].unique(maintain_order=True))
-
-        # Get pitch colors and names
-        dict_colour, dict_pitch = self.pitch_colours()
-        ordered_colors = [dict_colour[x] for x in items_in_order]
-        items_in_order = [dict_pitch[x] for x in items_in_order]
-
-        # Create custom legend handles with circles
-        legend_handles = [mlines.Line2D([], [], color=color, marker='o', linestyle='None', markersize=8, label=label) for color, label in zip(ordered_colors, items_in_order)]
-
-        # Add legend to ax_legend
-        ax_legend.legend(handles=legend_handles, bbox_to_anchor=(0.1, 0, 0.8, 0.5), ncol=5, fancybox=True, loc='lower center', fontsize=8, framealpha=1.0, markerscale=2, prop={'size': 16})
-
-        # Add footer text
-        ax_footer.text(x=0.075, y=1, s='By: Thomas Nestico\n      @TJStats', fontname='Calibri', ha='left', fontsize=24, va='top')
-        ax_footer.text(x=1-0.075, y=1, s='Data: MLB', ha='right', fontname='Calibri', fontsize=24, va='top')
-        ax_footer.axis('off')
-
-        # Create subplots for the borders
-        ax_top_border = fig.add_subplot(gs[0, :])
-        ax_left_border = fig.add_subplot(gs[:, 0])
-        ax_right_border = fig.add_subplot(gs[:, -1])
-        ax_bottom_border = fig.add_subplot(gs[-1, :])
-
-        # Turn off the axes for the border subplots
-        ax_top_border.axis('off')
-        ax_left_border.axis('off')
-        ax_right_border.axis('off')
-        ax_bottom_border.axis('off')
-
-        # Adjust layout and show the figure
-        fig.tight_layout()
-        fig.subplots_adjust(hspace=0.1, wspace=0.1)
-        st.pyplot(fig)
-
-
-
-
-    
-
+import polars as pl
+import numpy as np
+import matplotlib.pyplot as plt
+import seaborn as sns
+from PIL import Image
+import requests
+from io import BytesIO
+from matplotlib.offsetbox import OffsetImage, AnnotationBbox
+from matplotlib.ticker import FuncFormatter
+import matplotlib.transforms as transforms
+from matplotlib.patches import Ellipse
+import matplotlib.gridspec as gridspec
+import matplotlib.patches as mpatches
+import matplotlib.lines as mlines
+from matplotlib.figure import Figure
+import streamlit as st
+import api_scraper
+
+# Initialize the scraper
+scraper = api_scraper.MLB_Scrape()
+
+class PitchPlotFunctions:
+    # Define the pitch_colours method
+    def pitch_colours(self):
+        # Dictionary of pitch types and their corresponding colors and names
+        pitch_colours = {
+            'FF': {'colour': '#FF007D', 'name': '4-Seam Fastball'},
+            'FA': {'colour': '#FF007D', 'name': 'Fastball'},
+            'SI': {'colour': '#98165D', 'name': 'Sinker'},
+            'FC': {'colour': '#BE5FA0', 'name': 'Cutter'},
+            'CH': {'colour': '#F79E70', 'name': 'Changeup'},
+            'FS': {'colour': '#FE6100', 'name': 'Splitter'},
+            'SC': {'colour': '#F08223', 'name': 'Screwball'},
+            'FO': {'colour': '#FFB000', 'name': 'Forkball'},
+            'SL': {'colour': '#67E18D', 'name': 'Slider'},
+            'ST': {'colour': '#1BB999', 'name': 'Sweeper'},
+            'SV': {'colour': '#376748', 'name': 'Slurve'},
+            'KC': {'colour': '#311D8B', 'name': 'Knuckle Curve'},
+            'CU': {'colour': '#3025CE', 'name': 'Curveball'},
+            'CS': {'colour': '#274BFC', 'name': 'Slow Curve'},
+            'EP': {'colour': '#648FFF', 'name': 'Eephus'},
+            'KN': {'colour': '#867A08', 'name': 'Knuckleball'},
+            'PO': {'colour': '#472C30', 'name': 'Pitch Out'},
+            'UN': {'colour': '#9C8975', 'name': 'Unknown'},
+        }
+
+        # Create dictionaries mapping pitch types to their colors and names
+        dict_colour = dict(zip(pitch_colours.keys(), [pitch_colours[key]['colour'] for key in pitch_colours]))
+        dict_pitch = dict(zip(pitch_colours.keys(), [pitch_colours[key]['name'] for key in pitch_colours]))
+
+        return dict_colour, dict_pitch
+
+    # Define the sns_custom_theme method
+    def sns_custom_theme(self):
+        # Custom theme for seaborn plots
+        custom_theme = {
+            "axes.facecolor": "white",
+            "axes.edgecolor": ".8",
+            "axes.grid": True,
+            "axes.axisbelow": True,
+            "axes.labelcolor": ".15",
+            "figure.facecolor": "#f9f9f9",
+            "grid.color": ".8",
+            "grid.linestyle": "-",
+            "text.color": ".15",
+            "xtick.color": ".15",
+            "ytick.color": ".15",
+            "xtick.direction": "out",
+            "ytick.direction": "out",
+            "lines.solid_capstyle": "round",
+            "patch.edgecolor": "w",
+            "patch.force_edgecolor": True,
+            "image.cmap": "rocket",
+            "font.family": ["sans-serif"],
+            "font.sans-serif": ["Arial", "DejaVu Sans", "Liberation Sans", "Bitstream Vera Sans", "sans-serif"],
+            "xtick.bottom": False,
+            "xtick.top": False,
+            "ytick.left": False,
+            "ytick.right": False,
+            "axes.spines.left": True,
+            "axes.spines.bottom": True,
+            "axes.spines.right": True,
+            "axes.spines.top": True
+        }
+
+        # Color palette for the plots
+        colour_palette = ['#FFB000', '#648FFF', '#785EF0', '#DC267F', '#FE6100', '#3D1EB2', '#894D80', '#16AA02', '#B5592B', '#A3C1ED']
+
+        return custom_theme, colour_palette
+
+    # Define the sport_id_dict method
+    def sport_id_dict(self):
+        # Dictionary mapping sport IDs to their names
+        dict = {1: 'MLB', 11: 'AAA'}
+        return dict
+
+    # Define the team_logos method
+    def team_logos(self):
+        # List of MLB teams and their corresponding ESPN logo URLs
+        mlb_teams = [
+            {"team": "AZ", "logo_url": "https://a.espncdn.com/combiner/i?img=/i/teamlogos/mlb/500/scoreboard/ari.png&h=500&w=500"},
+            {"team": "ATL", "logo_url": "https://a.espncdn.com/combiner/i?img=/i/teamlogos/mlb/500/scoreboard/atl.png&h=500&w=500"},
+            {"team": "BAL", "logo_url": "https://a.espncdn.com/combiner/i?img=/i/teamlogos/mlb/500/scoreboard/bal.png&h=500&w=500"},
+            {"team": "BOS", "logo_url": "https://a.espncdn.com/combiner/i?img=/i/teamlogos/mlb/500/scoreboard/bos.png&h=500&w=500"},
+            {"team": "CHC", "logo_url": "https://a.espncdn.com/combiner/i?img=/i/teamlogos/mlb/500/scoreboard/chc.png&h=500&w=500"},
+            {"team": "CWS", "logo_url": "https://a.espncdn.com/combiner/i?img=/i/teamlogos/mlb/500/scoreboard/chw.png&h=500&w=500"},
+            {"team": "CIN", "logo_url": "https://a.espncdn.com/combiner/i?img=/i/teamlogos/mlb/500/scoreboard/cin.png&h=500&w=500"},
+            {"team": "CLE", "logo_url": "https://a.espncdn.com/combiner/i?img=/i/teamlogos/mlb/500/scoreboard/cle.png&h=500&w=500"},
+            {"team": "COL", "logo_url": "https://a.espncdn.com/combiner/i?img=/i/teamlogos/mlb/500/scoreboard/col.png&h=500&w=500"},
+            {"team": "DET", "logo_url": "https://a.espncdn.com/combiner/i?img=/i/teamlogos/mlb/500/scoreboard/det.png&h=500&w=500"},
+            {"team": "HOU", "logo_url": "https://a.espncdn.com/combiner/i?img=/i/teamlogos/mlb/500/scoreboard/hou.png&h=500&w=500"},
+            {"team": "KC", "logo_url": "https://a.espncdn.com/combiner/i?img=/i/teamlogos/mlb/500/scoreboard/kc.png&h=500&w=500"},
+            {"team": "LAA", "logo_url": "https://a.espncdn.com/combiner/i?img=/i/teamlogos/mlb/500/scoreboard/laa.png&h=500&w=500"},
+            {"team": "LAD", "logo_url": "https://a.espncdn.com/combiner/i?img=/i/teamlogos/mlb/500/scoreboard/lad.png&h=500&w=500"},
+            {"team": "MIA", "logo_url": "https://a.espncdn.com/combiner/i?img=/i/teamlogos/mlb/500/scoreboard/mia.png&h=500&w=500"},
+            {"team": "MIL", "logo_url": "https://a.espncdn.com/combiner/i?img=/i/teamlogos/mlb/500/scoreboard/mil.png&h=500&w=500"},
+            {"team": "MIN", "logo_url": "https://a.espncdn.com/combiner/i?img=/i/teamlogos/mlb/500/scoreboard/min.png&h=500&w=500"},
+            {"team": "NYM", "logo_url": "https://a.espncdn.com/combiner/i?img=/i/teamlogos/mlb/500/scoreboard/nym.png&h=500&w=500"},
+            {"team": "NYY", "logo_url": "https://a.espncdn.com/combiner/i?img=/i/teamlogos/mlb/500/scoreboard/nyy.png&h=500&w=500"},
+            {"team": "OAK", "logo_url": "https://a.espncdn.com/combiner/i?img=/i/teamlogos/mlb/500/scoreboard/oak.png&h=500&w=500"},
+            {"team": "PHI", "logo_url": "https://a.espncdn.com/combiner/i?img=/i/teamlogos/mlb/500/scoreboard/phi.png&h=500&w=500"},
+            {"team": "PIT", "logo_url": "https://a.espncdn.com/combiner/i?img=/i/teamlogos/mlb/500/scoreboard/pit.png&h=500&w=500"},
+            {"team": "SD", "logo_url": "https://a.espncdn.com/combiner/i?img=/i/teamlogos/mlb/500/scoreboard/sd.png&h=500&w=500"},
+            {"team": "SF", "logo_url": "https://a.espncdn.com/combiner/i?img=/i/teamlogos/mlb/500/scoreboard/sf.png&h=500&w=500"},
+            {"team": "SEA", "logo_url": "https://a.espncdn.com/combiner/i?img=/i/teamlogos/mlb/500/scoreboard/sea.png&h=500&w=500"},
+            {"team": "STL", "logo_url": "https://a.espncdn.com/combiner/i?img=/i/teamlogos/mlb/500/scoreboard/stl.png&h=500&w=500"},
+            {"team": "TB", "logo_url": "https://a.espncdn.com/combiner/i?img=/i/teamlogos/mlb/500/scoreboard/tb.png&h=500&w=500"},
+            {"team": "TEX", "logo_url": "https://a.espncdn.com/combiner/i?img=/i/teamlogos/mlb/500/scoreboard/tex.png&h=500&w=500"},
+            {"team": "TOR", "logo_url": "https://a.espncdn.com/combiner/i?img=/i/teamlogos/mlb/500/scoreboard/tor.png&h=500&w=500"},
+            {"team": "WSH", "logo_url": "https://a.espncdn.com/combiner/i?img=/i/teamlogos/mlb/500/scoreboard/wsh.png&h=500&w=500"}
+        ]
+
+        # Create a DataFrame from the list of dictionaries
+        df_image = pl.DataFrame(mlb_teams)
+        # Set the index to 'team' and convert 'logo_url' to a dictionary
+        image_dict = df_image.select(['team', 'logo_url']).to_dict(as_series=False)['logo_url']
+
+        # Convert to the desired dictionary format
+        image_dict = {row['team']: row['logo_url'] for row in df_image.select(['team', 'logo_url']).to_dicts()}
+
+        return image_dict
+
+    # Function to get an image from a URL and display it on the given axis
+    def player_headshot(self, pitcher_id: str, ax: plt.Axes, sport_id: int):
+        """
+        Fetches and displays the player's headshot image on the given axis.
+
+        Parameters:
+        pitcher_id (str): The ID of the pitcher.
+        ax (plt.Axes): The matplotlib axis to display the image on.
+        sport_id (int): The sport ID to determine the URL format.
+        """
+        # Construct the URL for the player's headshot image
+        if sport_id == 1:
+            url = f'https://img.mlbstatic.com/mlb-photos/image/'\
+                  f'upload/d_people:generic:headshot:67:current.png'\
+                  f'/w_640,q_auto:best/v1/people/{pitcher_id}/headshot/silo/current.png'
+        else:
+            url = f'https://img.mlbstatic.com/mlb-photos/image/upload/c_fill,g_auto/w_640/v1/people/{pitcher_id}/headshot/milb/current.png'
+        
+        # Send a GET request to the URL
+        response = requests.get(url)
+        # Open the image from the response content
+        img = Image.open(BytesIO(response.content))
+        # Display the image on the axis
+        ax.set_xlim(0, 2)
+        ax.set_ylim(0, 1)
+        ax.imshow(img, extent=[0.0, 1, 0, 1], origin='upper')
+        # Turn off the axis
+        ax.axis('off')
+
+    # Function to display player bio information on the given axis
+    def player_bio(self, pitcher_id: str, ax: plt.Axes, start_date: str, end_date: str, batter_hand: list):
+        """
+        Fetches and displays the player's bio information on the given axis.
+
+        Parameters:
+        pitcher_id (str): The ID of the pitcher.
+        ax (plt.Axes): The matplotlib axis to display the bio information on.
+        start_date (str): The start date for the bio information.
+        end_date (str): The end date for the bio information.
+        batter_hand (list): The list of batter hands (e.g., ['R'] or ['L']).
+        """
+        # Construct the URL to fetch player data
+        url = f"https://statsapi.mlb.com/api/v1/people?personIds={pitcher_id}&hydrate=currentTeam"
+        # Send a GET request to the URL and parse the JSON response
+        data = requests.get(url).json()
+        # Extract player information from the JSON data
+        player_name = data['people'][0]['fullName']
+        pitcher_hand = data['people'][0]['pitchHand']['code']
+        age = data['people'][0]['currentAge']
+        height = data['people'][0]['height']
+        weight = data['people'][0]['weight']
+        # Display the player's name, handedness, age, height, and weight on the axis
+        ax.text(0.5, 1, f'{player_name}', va='top', ha='center', fontsize=48)
+        ax.text(0.5, 0.6, f'{pitcher_hand}HP, Age: {age}, {height}/{weight}', va='top', ha='center', fontsize=22)
+        # Determine the batter hand text
+        if batter_hand == ['R']:
+            batter_hand_text = ', vs RHH'
+        elif batter_hand == ['L']:
+            batter_hand_text = ', vs LHH'
+        else:
+            batter_hand_text = ''
+        ax.text(0.5, 0.35, f'{start_date} to {end_date}{batter_hand_text}', va='top', ha='center', fontsize=22, fontstyle='italic')
+        # Turn off the axis
+        ax.axis('off')
+
+    # Function to display the team logo on the given axis
+    def plot_logo(self, pitcher_id: str, ax: plt.Axes):
+        """
+        Fetches and displays the team logo on the given axis.
+
+        Parameters:
+        pitcher_id (str): The ID of the pitcher.
+        ax (plt.Axes): The matplotlib axis to display the logo on.
+        """
+        # Construct the URL to fetch player data
+        url = f"https://statsapi.mlb.com/api/v1/people?personIds={pitcher_id}&hydrate=currentTeam"
+        # Send a GET request to the URL and parse the JSON response
+        data = requests.get(url).json()
+        # Construct the URL to fetch team data
+        try:
+            url_team = 'https://statsapi.mlb.com/' + data['people'][0]['currentTeam']['link']
+            # Send a GET request to the team URL and parse the JSON response
+            data_team = requests.get(url_team).json()
+            # Get the logo URL from the image dictionary using the team abbreviation
+            
+            if data_team['teams'][0]['sport']['id'] == 1:
+                team_abb = data_team['teams'][0]['abbreviation']
+                logo_url = self.team_logos()[team_abb]
+            else:
+                team_abb = data_team['teams'][0]['parentOrgId']
+                logo_url = self.team_logos()[dict(scraper.get_teams().select(['team_id', 'parent_org_abbreviation']).iter_rows())[team_abb]]
+        except KeyError:
+            logo_url = "https://a.espncdn.com/combiner/i?img=/i/teamlogos/leagues/500/mlb.png?w=500&h=500&transparent=true"
+        # Send a GET request to the logo URL
+        response = requests.get(logo_url)
+        # Open the image from the response content
+        img = Image.open(BytesIO(response.content))
+        # Display the image on the axis
+        ax.set_xlim(0, 2)
+        ax.set_ylim(0, 1)
+        ax.imshow(img, extent=[1, 2, 0, 1], origin='upper')
+        # Turn off the axis
+        ax.axis('off')
+
+    ### PITCH ELLIPSE ###
+    def confidence_ellipse( self,
+                            x:np.array,
+                            y:np.array, 
+                            ax:plt.Axes, 
+                            n_std:float=3.0,
+                            facecolor:str='none',
+                            **kwargs):
+        """
+        Create a plot of the covariance confidence ellipse of *x* and *y*.
+        Parameters
+        ----------
+        x, y : array-like, shape (n, )
+            Input data.
+        ax : matplotlib.axes.Axes
+            The axes object to draw the ellipse into.
+        n_std : float
+            The number of standard deviations to determine the ellipse's radiuses.
+        **kwargs
+            Forwarded to `~matplotlib.patches.Ellipse`
+        Returns
+        -------
+        matplotlib.patches.Ellipse
+        """
+        
+        if x.shape != y.shape:
+            raise ValueError("x and y must be the same size")
+        try:
+            cov = np.cov(x, y)
+            pearson = cov[0, 1]/np.sqrt(cov[0, 0] * cov[1, 1])
+            # Using a special case to obtain the eigenvalues of this
+            # two-dimensional dataset.
+            ell_radius_x = np.sqrt(1 + pearson)
+            ell_radius_y = np.sqrt(1 - pearson)
+            ellipse = Ellipse((0, 0), width=ell_radius_x * 2, height=ell_radius_y * 2,
+                            facecolor=facecolor,linewidth=2,linestyle='--', **kwargs)
+            
+
+            # Calculating the standard deviation of x from
+            # the squareroot of the variance and multiplying
+            # with the given number of standard deviations.
+            scale_x = np.sqrt(cov[0, 0]) * n_std
+            mean_x = x.mean()
+            
+
+            # calculating the standard deviation of y ...
+            scale_y = np.sqrt(cov[1, 1]) * n_std
+            mean_y = y.mean()
+            
+
+            transf = transforms.Affine2D() \
+                .rotate_deg(45) \
+                .scale(scale_x, scale_y) \
+                .translate(mean_x, mean_y)
+            
+            
+
+            ellipse.set_transform(transf + ax.transData)
+        except ValueError:
+            return    
+            
+        return ax.add_patch(ellipse)
+
+    
+    def break_plot_big(self, df: pl.DataFrame, ax: plt.Axes, sport_id: int):
+        """
+        Plots a big break plot for the given DataFrame on the provided axis.
+
+        Parameters:
+        df (pl.DataFrame): The DataFrame containing pitch data.
+        ax (plt.Axes): The matplotlib axis to plot on.
+        sport_id (int): The sport ID to determine the plot title.
+        """
+        # Set font properties for different elements of the plot
+        font_properties = {'size': 20}
+        font_properties_titles = {'size': 32}
+        font_properties_axes = {'size': 24}
+        
+        # Get unique pitch types sorted by 'prop' and 'pitch_type'
+        label_labels = df.sort(by=['prop', 'pitch_type'], descending=[False, True])['pitch_type'].unique()
+        j = 0
+        dict_colour, dict_pitch = self.pitch_colours()
+        custom_theme, colour_palette = self.sns_custom_theme()
+        
+        # Loop through each pitch type and plot confidence ellipses
+        for label in label_labels:
+            subset = df.filter(pl.col('pitch_type') == label)
+            if len(subset) > 4:
+                try:
+                    if df['pitcher_hand'][0] == 'R':
+                        self.confidence_ellipse(subset['hb'], subset['ivb'], ax=ax, edgecolor=dict_colour[label], n_std=2, facecolor=dict_colour[label], alpha=0.2)
+                    if df['pitcher_hand'][0] == 'L':
+                        self.confidence_ellipse(subset['hb'] * -1, subset['ivb'], ax=ax, edgecolor=dict_colour[label], n_std=2, facecolor=dict_colour[label], alpha=0.2)
+                except ValueError:
+                    return
+                j += 1
+            else:
+                j += 1
+        
+        # Plot scatter plot of pitch data
+        if df['pitcher_hand'][0] == 'R':
+            sns.scatterplot(ax=ax, x=df['hb'] * 1, y=df['ivb'] * 1, hue=df['pitch_type'], palette=dict_colour, ec='black', alpha=1, zorder=2, s=50)
+        if df['pitcher_hand'][0] == 'L':
+            sns.scatterplot(ax=ax, x=df['hb'] * -1, y=df['ivb'] * 1, hue=df['pitch_type'], palette=dict_colour, ec='black', alpha=1, zorder=2, s=50)
+        
+        # Set plot limits and labels
+        ax.set_xlim((-25, 25))
+        ax.set_ylim((-25, 25))
+        ax.hlines(y=0, xmin=-50, xmax=50, color=colour_palette[8], alpha=0.5, linestyles='--', zorder=1)
+        ax.vlines(x=0, ymin=-50, ymax=50, color=colour_palette[8], alpha=0.5, linestyles='--', zorder=1)
+        ax.set_xlabel('Horizontal Break (in)', fontdict=font_properties_axes)
+        ax.set_ylabel('Induced Vertical Break (in)', fontdict=font_properties_axes)
+        ax.set_title(f"{self.sport_id_dict()[sport_id]} - Short Form Pitch Movement Plot", fontdict=font_properties_titles)
+        
+        # Remove legend and set tick labels
+        ax.get_legend().remove()
+        ax.set_xticklabels(ax.get_xticks(), fontdict=font_properties)
+        ax.set_yticklabels(ax.get_yticks(), fontdict=font_properties)
+        
+        # Add text annotations based on pitcher hand
+        if df['pitcher_hand'][0] == 'R':
+            ax.text(-24.5, -24.5, s='← Glove Side', fontstyle='italic', ha='left', va='bottom', bbox=dict(facecolor='white', edgecolor='black'), fontsize=16, zorder=3)
+            ax.text(24.5, -24.5, s='Arm Side →', fontstyle='italic', ha='right', va='bottom', bbox=dict(facecolor='white', edgecolor='black'), fontsize=16, zorder=3)
+        if df['pitcher_hand'][0] == 'L':
+            ax.invert_xaxis()
+            ax.text(24.5, -24.5, s='← Arm Side', fontstyle='italic', ha='left', va='bottom', bbox=dict(facecolor='white', edgecolor='black'), fontsize=16, zorder=3)
+            ax.text(-24.5, -24.5, s='Glove Side →', fontstyle='italic', ha='right', va='bottom', bbox=dict(facecolor='white', edgecolor='black'), fontsize=16, zorder=3)
+        
+        # Set aspect ratio and format tick labels
+        ax.set_aspect('equal', adjustable='box')
+        ax.xaxis.set_major_formatter(FuncFormatter(lambda x, _: int(x)))
+        ax.yaxis.set_major_formatter(FuncFormatter(lambda x, _: int(x)))
+
+    ### BREAK PLOT ###
+    def break_plot_big_long(self, df: pl.DataFrame, ax: plt.Axes, sport_id: int):
+        """
+        Plots a long break plot for the given DataFrame on the provided axis.
+
+        Parameters:
+        df (pl.DataFrame): The DataFrame containing pitch data.
+        ax (plt.Axes): The matplotlib axis to plot on.
+        sport_id (int): The sport ID to determine the plot title.
+        """
+        # Set font properties for different elements of the plot
+        font_properties = {'size': 20}
+        font_properties_titles = {'size': 32}
+        font_properties_axes = {'size': 24}
+        
+        # Get unique pitch types sorted by 'prop' and 'pitch_type'
+        label_labels = df.sort(by=['prop', 'pitch_type'], descending=[False, True])['pitch_type'].unique()
+        dict_colour, dict_pitch = self.pitch_colours()
+        custom_theme, colour_palette = self.sns_custom_theme()
+        j = 0
+        
+        # Loop through each pitch type and plot confidence ellipses
+        for label in label_labels:
+            subset = df.filter(pl.col('pitch_type') == label)
+            print(label)
+            if len(subset) > 4:
+                try:
+                    if df['pitcher_hand'][0] == 'R':
+                        self.confidence_ellipse(subset['hb'], subset['vb'], ax=ax, edgecolor=dict_colour[label], n_std=2, facecolor=dict_colour[label], alpha=0.2)
+                    if df['pitcher_hand'][0] == 'L':
+                        self.confidence_ellipse(subset['hb'] * -1, subset['vb'], ax=ax, edgecolor=dict_colour[label], n_std=2, facecolor=dict_colour[label], alpha=0.2)
+                except ValueError:
+                    return
+                j += 1
+            else:
+                j += 1
+        
+        # Plot scatter plot of pitch data
+        if df['pitcher_hand'][0] == 'R':
+            sns.scatterplot(ax=ax, x=df['hb'] * 1, y=df['vb'] * 1, hue=df['pitch_type'], palette=dict_colour, ec='black', alpha=1, zorder=2, s=50)
+        if df['pitcher_hand'][0] == 'L':
+            sns.scatterplot(ax=ax, x=df['hb'] * -1, y=df['vb'] * 1, hue=df['pitch_type'], palette=dict_colour, ec='black', alpha=1, zorder=2, s=50)
+        
+        # Set plot limits and labels
+        ax.set_xlim((-40, 40))
+        ax.set_ylim((-80, 0))
+        ax.axhline(y=0, color=colour_palette[8], alpha=0.5, linestyle='--', zorder=1)
+        ax.axvline(x=0, color=colour_palette[8], alpha=0.5, linestyle='--', zorder=1)
+        ax.set_xlabel('Horizontal Break (in)', fontdict=font_properties_axes)
+        ax.set_ylabel('Vertical Break (in)', fontdict=font_properties_axes)
+        ax.set_title(f"{self.sport_id_dict()[sport_id]} - Long Form Pitch Movement Plot", fontdict=font_properties_titles)
+        
+        # Remove legend and set tick labels
+        ax.get_legend().remove()
+        ax.set_xticklabels(ax.get_xticks(), fontdict=font_properties)
+        ax.set_yticklabels(ax.get_yticks(), fontdict=font_properties)
+        
+        # Add text annotations based on pitcher hand
+        if df['pitcher_hand'][0] == 'R':
+            ax.text(-39.5, -79.5, s='← Glove Side', fontstyle='italic', ha='left', va='bottom', bbox=dict(facecolor='white', edgecolor='black'), fontsize=16, zorder=3)
+            ax.text(39.5, -79.5, s='Arm Side →', fontstyle='italic', ha='right', va='bottom', bbox=dict(facecolor='white', edgecolor='black'), fontsize=16, zorder=3)
+        if df['pitcher_hand'][0] == 'L':
+            ax.invert_xaxis()
+            ax.text(39.5, -79.5, s='← Arm Side', fontstyle='italic', ha='left', va='bottom', bbox=dict(facecolor='white', edgecolor='black'), fontsize=16, zorder=3)
+            ax.text(-39.5, -79.5, s='Glove Side →', fontstyle='italic', ha='right', va='bottom', bbox=dict(facecolor='white', edgecolor='black'), fontsize=16, zorder=3)
+        
+        # Set aspect ratio and format tick labels
+        ax.set_aspect('equal', adjustable='box')
+        ax.xaxis.set_major_formatter(FuncFormatter(lambda x, _: int(x)))
+        ax.yaxis.set_major_formatter(FuncFormatter(lambda x, _: int(x)))
+
+    ### BREAK PLOT ###
+    def release_point_plot(self, df: pl.DataFrame, ax: plt.Axes, sport_id: int):
+        """
+        Plots the release points for the given DataFrame on the provided axis.
+
+        Parameters:
+        df (pl.DataFrame): The DataFrame containing pitch data.
+        ax (plt.Axes): The matplotlib axis to plot on.
+        sport_id (int): The sport ID to determine the plot title.
+        """
+        # Set font properties for different elements of the plot
+        font_properties = {'size': 20}
+        font_properties_titles = {'size': 32}
+        font_properties_axes = {'size': 24}
+        dict_colour, dict_pitch = self.pitch_colours()
+        custom_theme, colour_palette = self.sns_custom_theme()
+        
+        # Plot scatter plot of release points based on pitcher hand
+        if df['pitcher_hand'][0] == 'R':
+            sns.scatterplot(ax=ax, x=df['x0'] * -1, y=df['z0'] * 1, hue=df['pitch_type'], palette=dict_colour, ec='black', alpha=1, zorder=2, s=50)
+        if df['pitcher_hand'][0] == 'L':
+            sns.scatterplot(ax=ax, x=df['x0'] * 1, y=df['z0'] * 1, hue=df['pitch_type'], palette=dict_colour, ec='black', alpha=1, zorder=2, s=50)
+        
+        # Add patches to the plot
+        ax.add_patch(plt.Circle((0, 10 / 12 - 18), radius=18, edgecolor='black', facecolor='#a63b17'))
+        ax.add_patch(plt.Rectangle((-0.5, 9 / 12), 1, 1 / 6, edgecolor='black', facecolor='white'))
+        
+        # Set plot limits and labels
+        ax.set_xlim((-4, 4))
+        ax.set_ylim((0, 8))
+        ax.axhline(y=0, color=colour_palette[8], alpha=0.5, linestyle='--', zorder=1)
+        ax.axvline(x=0, color=colour_palette[8], alpha=0.5, linestyle='--', zorder=1)
+        ax.set_ylabel('Vertical Release (ft)', fontdict=font_properties_axes)
+        ax.set_xlabel('Horizontal Release (ft)', fontdict=font_properties_axes)
+        ax.set_title(f"{self.sport_id_dict()[sport_id]} - Release Points Catcher Perspective", fontdict=font_properties_titles)
+        
+        # Remove legend and set tick labels
+        ax.get_legend().remove()
+        ax.set_xticklabels(ax.get_xticks(), fontdict=font_properties)
+        ax.set_yticklabels(ax.get_yticks(), fontdict=font_properties)
+        
+        # Add text annotations based on pitcher hand
+        if df['pitcher_hand'][0] == 'L':
+            ax.text(-3.95, 0.05, s='← Glove Side', fontstyle='italic', ha='left', va='bottom', bbox=dict(facecolor='white', edgecolor='black'), fontsize=16, zorder=3)
+            ax.text(3.95, 0.05, s='Arm Side →', fontstyle='italic', ha='right', va='bottom', bbox=dict(facecolor='white', edgecolor='black'), fontsize=16, zorder=3)
+        if df['pitcher_hand'][0] == 'R':
+            ax.invert_xaxis()
+            ax.text(3.95, 0.05, s='← Arm Side', fontstyle='italic', ha='left', va='bottom', bbox=dict(facecolor='white', edgecolor='black'), fontsize=16, zorder=3)
+            ax.text(-3.95, 0.05, s='Glove Side →', fontstyle='italic', ha='right', va='bottom', bbox=dict(facecolor='white', edgecolor='black'), fontsize=16, zorder=3)
+        
+        # Set aspect ratio and format tick labels
+        ax.set_aspect('equal', adjustable='box')
+        ax.xaxis.set_major_formatter(FuncFormatter(lambda x, _: int(x)))
+        ax.yaxis.set_major_formatter(FuncFormatter(lambda x, _: int(x)))
+
+    def df_to_polars(self, df_original: pl.DataFrame, pitcher_id: str, start_date: str, end_date: str, batter_hand: list):
+        """
+        Filters and processes the original DataFrame to a Polars DataFrame.
+
+        Parameters:
+        df_original (pl.DataFrame): The original DataFrame containing pitch data.
+        pitcher_id (str): The ID of the pitcher.
+        start_date (str): The start date for filtering the data.
+        end_date (str): The end date for filtering the data.
+        batter_hand (list): The list of batter hands (e.g., ['R'] or ['L']).
+
+        Returns:
+        pl.DataFrame: The filtered and processed Polars DataFrame.
+        """
+        df = df_original.clone()
+        df = df.filter((pl.col('pitcher_id') == pitcher_id) & 
+                       (pl.col('is_pitch')) & (pl.col('pitch_type').is_not_null()) &
+                       (pl.col('pitch_type') != 'NaN') &
+                       (pl.col('game_date') >= start_date) &
+                       (pl.col('game_date') <= end_date) &
+                       (pl.col('batter_hand').is_in(batter_hand)))
+        df = df.with_columns(
+            prop_percent=(pl.col('is_pitch') / pl.col('is_pitch').sum()).over("pitch_type"),
+            prop=pl.col('is_pitch').sum().over("pitch_type")
+        )
+        return df
+    
+    def final_plot(self, df: pl.DataFrame, pitcher_id: str, plot_picker: str, sport_id: int):
+        """
+        Creates a final plot with player headshot, bio, logo, and pitch movement plots.
+
+        Parameters:
+        df (pl.DataFrame): The DataFrame containing pitch data.
+        pitcher_id (str): The ID of the pitcher.
+        plot_picker (str): The type of plot to create ('short_form_movement', 'long_form_movement', 'release_point').
+        sport_id (int): The sport ID to determine the plot title.
+        """
+        # Set the theme for seaborn plots
+        sns.set_theme(style="whitegrid", rc=self.sns_custom_theme()[0])
+        
+        # Create a figure and a gridspec with 6 rows and 5 columns
+        fig = plt.figure(figsize=(16, 16), dpi=400)
+        gs = gridspec.GridSpec(6, 5, figure=fig, height_ratios=[0.00000000005, 5, 30, 5, 2, 0.00000000005], width_ratios=[1, 10, 10, 10, 1])
+
+        # Create subplots for player headshot, bio, and logo
+        ax_headshot = fig.add_subplot(gs[1, 1])
+        ax_bio = fig.add_subplot(gs[1, 2])
+        ax_logo = fig.add_subplot(gs[1, 3])
+
+        # Get the start and end dates and unique batter hands from the DataFrame
+        start_date = df['game_date'].min()
+        end_date = df['game_date'].max()
+        batter_hand = list(df['batter_hand'].unique())
+
+        # Plot player headshot, bio, and logo
+        self.player_headshot(pitcher_id=pitcher_id, ax=ax_headshot, sport_id=sport_id)
+        self.player_bio(pitcher_id=pitcher_id, ax=ax_bio, start_date=start_date, end_date=end_date, batter_hand=batter_hand)
+        self.plot_logo(pitcher_id=pitcher_id, ax=ax_logo)
+
+        # Create subplot for the main plot
+        ax_main_plot = fig.add_subplot(gs[2, :])
+
+        # Create subplot for the legend
+        ax_legend = fig.add_subplot(gs[3, :])
+        ax_legend.axis('off')
+
+        # Create subplot for the footer
+        ax_footer = fig.add_subplot(gs[-2, :])
+
+        # Plot the selected pitch movement plot
+        if plot_picker == 'short_form_movement':
+            self.break_plot_big(df, ax_main_plot, sport_id=sport_id)
+        elif plot_picker == 'long_form_movement':
+            self.break_plot_big_long(df, ax_main_plot, sport_id=sport_id)
+        elif plot_picker == 'release_point':
+            self.release_point_plot(df, ax_main_plot, sport_id=sport_id)
+
+        # Sort the DataFrame and get unique pitch types
+        items_in_order = list(df.sort(by=['prop', 'pitch_type'], descending=[True, True])['pitch_type'].unique(maintain_order=True))
+
+        # Get pitch colors and names
+        dict_colour, dict_pitch = self.pitch_colours()
+        ordered_colors = [dict_colour[x] for x in items_in_order]
+        items_in_order = [dict_pitch[x] for x in items_in_order]
+
+        # Create custom legend handles with circles
+        legend_handles = [mlines.Line2D([], [], color=color, marker='o', linestyle='None', markersize=8, label=label) for color, label in zip(ordered_colors, items_in_order)]
+
+        # Add legend to ax_legend
+        ax_legend.legend(handles=legend_handles, bbox_to_anchor=(0.1, 0, 0.8, 0.5), ncol=5, fancybox=True, loc='lower center', fontsize=8, framealpha=1.0, markerscale=2, prop={'size': 16})
+
+        # Add footer text
+        ax_footer.text(x=0.075, y=1, s='By: Thomas Nestico\n      @TJStats', fontname='Calibri', ha='left', fontsize=24, va='top')
+        ax_footer.text(x=1-0.075, y=1, s='Data: MLB', ha='right', fontname='Calibri', fontsize=24, va='top')
+        ax_footer.axis('off')
+
+        # Create subplots for the borders
+        ax_top_border = fig.add_subplot(gs[0, :])
+        ax_left_border = fig.add_subplot(gs[:, 0])
+        ax_right_border = fig.add_subplot(gs[:, -1])
+        ax_bottom_border = fig.add_subplot(gs[-1, :])
+
+        # Turn off the axes for the border subplots
+        ax_top_border.axis('off')
+        ax_left_border.axis('off')
+        ax_right_border.axis('off')
+        ax_bottom_border.axis('off')
+
+        # Adjust layout and show the figure
+        fig.tight_layout()
+        fig.subplots_adjust(hspace=0.1, wspace=0.1)
+        st.pyplot(fig)
+
+
+
+
+    
+