Overview of AFC Women's Champions League Preliminary Round Group A
The AFC Women's Champions League Preliminary Round Group A is gearing up for an exciting set of matches tomorrow. Fans and enthusiasts are eagerly anticipating the showdowns, which promise to deliver thrilling football action. This stage is crucial as teams battle it out to secure a spot in the next round of this prestigious tournament. With a blend of tactical prowess and raw talent, each match holds the potential to surprise and captivate audiences worldwide.
Teams in Focus
Group A comprises several formidable teams, each bringing unique strengths and strategies to the pitch. The group features clubs from diverse regions, showcasing the growing competitiveness and talent pool in women's football across Asia.
Key Teams
- Team A: Known for their solid defense and strategic gameplay, Team A has consistently been a strong contender in previous tournaments.
- Team B: With a dynamic attacking lineup, Team B is expected to put on an offensive spectacle, aiming to dominate possession and create numerous scoring opportunities.
- Team C: Renowned for their resilience and teamwork, Team C often thrives under pressure, making them a tough opponent in knockout scenarios.
- Team D: Emerging as dark horses, Team D has shown remarkable progress in recent seasons, with young talents leading the charge.
Match Predictions and Analysis
As the matches draw near, expert analysts have provided insights into potential outcomes based on team form, player performances, and historical data. These predictions offer a glimpse into what might unfold on the field.
Match 1: Team A vs. Team B
This clash is anticipated to be a tactical battle. Team A's defensive solidity will be tested against Team B's aggressive forward play. Analysts predict a low-scoring affair with both teams wary of conceding early goals.
Match 2: Team C vs. Team D
Team C's experience could be pivotal in this encounter. However, Team D's youthful energy and recent form suggest they could pull off an upset. Expect an evenly matched contest with both teams looking to exploit any weaknesses.
Betting Predictions
Betting enthusiasts are keenly watching these matches for potential opportunities. Here are some expert predictions based on current odds and team analyses.
Betting Tips for Match 1: Team A vs. Team B
- Under 2.5 Goals: Given both teams' cautious approach, betting on fewer than three goals could be a safe bet.
- Draw No Bet: With both teams having strong defenses, a draw is a plausible outcome.
- Total Corners Over/Under: Expect a high number of corners due to the attacking strategies employed by both sides.
Betting Tips for Match 2: Team C vs. Team D
- Team D to Score: With their attacking flair, backing Team D to score at least one goal could be rewarding.
- Both Teams to Score (BTTS): Given the open nature of this match, there's a good chance both teams will find the back of the net.
- Correct Score Prediction: A close match could end with a narrow victory for either side; consider exploring correct score bets.
Tactical Insights
Understanding team tactics can provide deeper insights into potential match outcomes. Here’s a breakdown of key tactical elements for each team.
Team A's Defensive Strategy
Team A is likely to employ a compact defensive formation, focusing on intercepting passes and minimizing space for opponents. Their full-backs may adopt a conservative approach, prioritizing defensive duties over overlapping runs.
Team B's Offensive Play
Expect Team B to utilize quick transitions from defense to attack, exploiting spaces left by opponents. Their wingers will play a crucial role in stretching the defense and delivering crosses into the box.
Team C's Midfield Dominance
Controlling the midfield will be vital for Team C. They aim to dictate the tempo of the game through possession-based play, using their midfielders' vision to create goal-scoring opportunities.
Team D's Youthful Energy
Team D's young squad brings enthusiasm and unpredictability. They are likely to press high up the pitch, aiming to disrupt their opponents' rhythm and capitalize on counter-attacks.
Potential Game-Changers
Several players could emerge as key influencers in these matches. Their performances might tip the scales in favor of their respective teams.
Influential Players in Match 1: Team A vs. Team B
- Sarah Lee (Team A): As captain and defensive anchor, her leadership will be crucial in organizing the backline.
- Mia Tan (Team B): Known for her pace and dribbling skills, she could break down defenses with her skillful runs.
Influential Players in Match 2: Team C vs. Team D
- Jessica Wong (Team C): Her playmaking abilities will be vital in linking defense and attack.
- Aisha Khan (Team D): As an emerging star striker, her finishing prowess could be decisive in securing goals.
Past Performance Analysis
Examining past performances provides context for predicting future outcomes. Historical data highlights patterns that may influence tomorrow’s matches.
Past Encounters: Team A vs. Team B
In previous meetings, these teams have displayed contrasting styles but balanced results. Matches often hinge on which team can impose their game plan effectively.
Past Encounters: Team C vs. Team D
Historically, matches between these teams have been closely contested affairs, with neither side able to establish consistent dominance over the other.
Injury Updates and Squad Changes
<|file_sep|># -*- coding: utf-8 -*-
"""
Created on Tue Jan
@author: Christian Kehl
"""
import os
import time
import pandas as pd
from matplotlib import pyplot as plt
from matplotlib import rcParams
from datetime import datetime
import matplotlib.dates as mdates
#Set global parameters
rcParams['font.family'] = 'sans-serif'
rcParams['font.sans-serif'] = ['Arial']
rcParams['font.size'] = '16'
rcParams['lines.linewidth'] = '0.8'
rcParams['legend.fontsize'] = '14'
rcParams['axes.linewidth'] = '0.8'
def plot_filelist(filelist):
#Go through all files
for file in filelist:
print('Processing file '+file)
#Read CSV File
df=pd.read_csv(file)
#Remove unwanted columns
df=df.drop(['Unnamed:0','Unnamed:0_x','Unnamed:0_y'], axis=1)
#Convert time column
df['Time']=df['Time'].apply(lambda x: datetime.strptime(x,'%Y-%m-%d %H:%M:%S'))
#Sort by Time
df.sort_values(by=['Time'], inplace=True)
#Get information about input file
filename=os.path.basename(file)
print('Filename:'+filename)
#Extract country name from filename
country=filename.split('_')[0]
#Extract state name from filename if available
try:
state=filename.split('_')[1]
print('State:'+state)
#Create path name if state not equal 'Global'
path='Country/'+country+'/'+state
#If state equal Global create path name without state
if state=='Global':
path='Country/'+country+'/Global'
#Replace state by country name
country=state.replace('Global',country)
#If country Germany replace by DEU
if country=='Germany':
country='DEU'
print('Country:'+country)
except:
path='Country/'+country
#Create directory if not existent
try:
os.makedirs(path)
except OSError:
pass
#Plot line graph
plt.figure(figsize=(10.,5.),dpi=150)
#Select data points from dataframe
x=df['Time']
y=df['Confirmed']
#Plot data points with label
plt.plot(x,y,label=country,c='black')
#Add legend
plt.legend()
#Set x-axis label
plt.xlabel('Date')
#Set y-axis label
plt.ylabel('Cases')
#Set title
plt.title(country+' '+state)
#Set date format on x-axis
plt.gca().xaxis.set_major_formatter(mdates.DateFormatter('%d.%m.%y'))
#Rotate date labels
plt.gcf().autofmt_xdate()
#Set limits for y-axis based on max value of y-values +10%
plt.ylim(top=max(y)+max(y)*0.1)
#Save figure as PNG file
figname=path+'/'+filename.replace('.csv','.png')
plt.savefig(figname,dpi=150,bbox_inches='tight')
print('Saved figure as '+figname)
#Get list of all CSV files from directory
filelist=[os.path.join(dp,f) for dp,dn,f in os.walk(os.getcwd()) for f in dn if f.endswith('.csv')]
#Call plot function with filelist as argument
plot_filelist(filelist)<|repo_name|>c-kehl/covid19<|file_sep|>/README.md
# COVID19
Data sources:
https://github.com/CSSEGISandData/COVID-19/blob/master/csse_covid_19_data/csse_covid_19_time_series/time_series_covid19_confirmed_global.csv
https://github.com/CSSEGISandData/COVID-19/blob/master/csse_covid_19_data/csse_covid_19_time_series/time_series_covid19_deaths_global.csv
https://github.com/CSSEGISandData/COVID-19/blob/master/csse_covid_19_data/csse_covid_19_time_series/time_series_covid19_recovered_global.csv
Source code:
https://github.com/c-kehl/covid19/blob/master/extract_daily_data.py
https://github.com/c-kehl/covid19/blob/master/plot_time_series.py
<|repo_name|>c-kehl/covid19<|file_sep|>/extract_daily_data.py
# -*- coding: utf-8 -*-
"""
Created on Mon Jan
@author: Christian Kehl
"""
import pandas as pd
import os
#Read CSV File confirmed cases
df=pd.read_csv('https://raw.githubusercontent.com/CSSEGISandData/COVID-19/master/csse_covid_19_data/csse_covid_19_time_series/time_series_covid19_confirmed_global.csv')
#Extract data columns from dataframe (all columns except first three columns)
data=df.iloc[:,4:]
#Add new column Time with values from column Date - fill empty cells with zero value (NaN ->0)
data.insert(0,'Time',df['Date'].fillna(0))
#Remove first column Province/State (not needed anymore)
data=data.drop(['Province/State'],axis=1)
#Reset index starting at zero (default after drop operation is index starting at one)
data.reset_index(drop=True,inplace=True)
#Group rows by Country/Region summing up all values (if several entries exist e.g.: US State wise entries + Federal States entries)
data=data.groupby(['Country/Region']).sum()
#Create directory if not existent
try:
os.makedirs('Country')
except OSError:
pass
#Go through all rows (Countries)
for row_index,row_value in data.iterrows():
country=row_value.name
#Print Country name
print(country)
#Extract series values from dataframe row
series=row_value.to_list()
#Create dataframe with two columns - Time & Cases
df=pd.DataFrame(list(zip(series[:],series[1:])),columns=['Time','Confirmed'])
#Add Country column with constant value
df['Country']=country
try:
state=row_value.name.split(',')[1].strip()
print(state)
df['State']=state
path='Country/'+row_value.name.replace(',','_')+'_DailyConfirmed.csv'
print(path)
except:
path='Country/'+row_value.name+'_DailyConfirmed.csv'
print(path)
df.to_csv(path,index=False)
<|file_sep|>#include "stdafx.h"
#include "Turret.h"
CTurret::CTurret(CPlayer* player) :CGameObject(player->GetWorld())
{
//m_TurretMesh = SMgr.GetMesh("Models/TankTurret.X");
m_TurretMesh = SMgr.GetMesh("Models/TankTurretTest.X");
m_MaxRotationSpeed = Vector3(180.f / dt);
m_MaxRotationSpeed *= dt;
//m_RotationSpeed = m_MaxRotationSpeed;
m_RotationSpeed = Vector3(100.f / dt);
m_RotationSpeed *= dt;
m_CurrentRotationSpeed = Vector3::Zero;
}
CTurret::~CTurret(void)
{
}
void CTurret::Update(const float& dt)
{
CGameObject::Update(dt);
if (!m_Player->IsDead())
{
Vector3 lookDirection = m_Player->GetPosition() - GetPosition();
lookDirection.Normalize();
Vector3 turretForward = GetForward();
turretForward.Normalize();
float dot = turretForward.Dot(lookDirection);
if (dot > -0.f && dot <= -0.999f)
{
turretForward *= -1.f;
dot *= -1.f;
}
float angleToLookAt = acos(dot);
Vector3 crossProductVector = turretForward.Cross(lookDirection);
float crossProductZValue = crossProductVector.z;
if(crossProductZValue >= -0.f && crossProductZValue <= +0.f) // up or down -> rotate around x axis
m_CurrentRotationSpeed.x = m_RotationSpeed.x * sign(angleToLookAt);
else if(crossProductZValue > +0.f && crossProductZValue <= +1.f) // right side -> rotate around z axis clockwise
m_CurrentRotationSpeed.z = m_RotationSpeed.z * sign(angleToLookAt);
else if(crossProductZValue > -1.f && crossProductZValue <= -0.f) // left side -> rotate around z axis counter clockwise
m_CurrentRotationSpeed.z = m_RotationSpeed.z * sign(-angleToLookAt);
else // only happens when vectors are parallel -> do nothing because there is no need to rotate around y axis
m_CurrentRotationSpeed.y = Vector3::Zero.y;
if (abs(angleToLookAt) > abs(m_CurrentRotationSpeed.Length()))
m_CurrentRotationSpeed.Normalize();
SetRotation(GetRotation() + m_CurrentRotationSpeed);
// CGameObject* objectInFrontOfTurret;
// float minDistanceToObjectInFrontOfTurret;
// bool objectInFrontOfTurretExists;
// objectInFrontOfTurretExists =
// SMgr.GetPhysicsManager()->Raycast(
// GetPosition(),
// GetForward(),
// objectInFrontOfTurret,
// minDistanceToObjectInFrontOfTurret,
// this,
// false);
//
//
// if (!objectInFrontOfTurretExists || objectInFrontOfTurret == m_Player)
// return;
//
//
// Vector3 lookDirection =
// objectInFrontOfTurret->GetPosition() -
// GetPosition();
//
// Vector3 turretForward =
// GetForward();
//
// turretForward.Normalize();
//
//
// float dot =
// turretForward.Dot(lookDirection);
//
//
// if (dot > -0.f && dot <= -0.999f)
// {
// turretForward *= -1.f;
// dot *= -1.f;
// }
//
//
// float angleToLookAt =
// acos(dot);
//
//
// Vector3 crossProductVector =
// turretForward.Cross(lookDirection);
//
//
// float crossProductZValue =
// crossProductVector.z;
//
//
//
////UP OR DOWN -> ROTATE AROUND X AXIS
//
//
//
////RIGHT SIDE -> ROTATE AROUND Z AXIS CLOCKWISE
//
////LEFT SIDE -> ROTATE AROUND Z AXIS COUNTER CLOCKWISE
//
////ONLY HAPPENS WHEN VECTORS ARE PARALLEL -> DO NOTHING BECAUSE THERE IS NO NEED TO ROTATE AROUND Y AXIS
//
////if (abs(angleToLookAt) > abs(m_CurrentRotationSpeed.Length()))
//// m_CurrentRotationSpeed.Normalize();
////
////
////SetRotation(GetRotation() + m_CurrentRotationSpeed);
}
}
void CTurret::Render(const Vector4& colorOverride /*= Vector4::White*/)
{
CGameObject::Render(colorOverride);
Matrix worldMatrix;
worldMatrix.SetTranslation(GetPosition());
worldMatrix.Rotate(GetEulerAngles());
worldMatrix.Scale(Vector3(20.f));
SMgr.GetDevice()->SetTransform(D3DTS_WORLD,&worldMatrix);
SMgr.Get