Excel - Super League 

Immerse yourself in the exhilarating world of Super League  analytics using Microsoft Excel.

This micro course is tailored for enthusiasts who want to master data manipulation and visualization with real-time datasets from the Super League.
Learn to clean, analyze, and visualize player statistics, team performance, and match trends.
Gain the skills to create dynamic dashboards that offer valuable insights.

Excel Bootcamp


Super League Data Lab  

The Intro course is free

  • Video Introduction
  • Paid Section Preview
  • Theory
  • Case Study Preview
  • Practice

#1 Excel Bootcamp

Sections included :

  • Working with tables
  • CountA() Function
  • CountIFS() Function
  • Exploring Excel
  • CountIF() Function
  • SumIF() Function
  • IF() Function
  • Data Validation & CountIF()
  • SumIFS() Function
  • Average() Function
  • AverageIF() Function
  • AverageIFS() Function
  • Pivot Tables

#2 Advanced Excel 

Sections included :

  • VLOOKUP() Function
  • MATCH() Function
  • LEFT() Function
  • HLOOKUP() Function
  • TRIM() Function
  • RIGHT() Function
  • INDEX() Function
  • CLEAN() Function
  • MID() Function
  • SUBSTITUTE() Function
  • Data Cleaning

#3 Playground

Sections included :

  • Case Study 1: The Home Ground Advantage
  • Case Study 2: Clash of the Titans
  • Case Study 3: Win - Loss Ration
  • Case Study 4: Analyzing Data based on Performance Ranking

#4 Practice Section

Sections included :

  • IF() Function Exercises
  • SUM(), SUMIF() & SUMIFS() Functions

Data Labs

#5 Case Studies

A Data Lab is essentially a dynamic learning environment where we put into practice the latest skills we've acquired in Excel through the League of your choosing.

In this section, our focus shifts to the realm of Super League data.

Data Lab serves as a practical course where we immerse ourselves in hands-on Case Studies, applying our knowledge to gain insights and make data-driven decisions.

With each Case Study, we explore new dimensions of data analysis, allowing us to delve into the latest trends and uncover hidden patterns within the world of Super League data.

Sections included :

Case Study #1 : Performance statistics of Ionikos

In conclusion, Ionikos' performance during the 2022/23 Super League shows a team that struggled offensively and defensively, despite some strong individual performances. Improvement in goal conversion, better utilization of ball possession, and enhancement in defensive tactics could be crucial for the team's future success.

Case Study #2 : Performance statistics of Ofi

From this analysis, the team shows potential in both offensive and defensive play ⚽, with evidence of strong ball control 🎛️ and defensive activity 🛡️. However, there's a need to improve efficiency in creating significant goal opportunities 🎯 from their possession and on-target attempts 🥅, and in converting defensive activity into successful prevention of goals 🚫. The 3412 formation 📐 seems to yield the best performance in terms of scoring ⚽ and conceding goals ❌. These insights 💡 could guide their future strategic and tactical decisions 🤔.

Case Study #3 : Performance statistics of Olympiakos

Based on the data from the 2022/23 Super League, Olympiakos demonstrated an effective combination of strong offensive prowess and solid defensive stability. They scored more than 2 goals in 10 games ⚽️, kept clean sheets in 12 games ✅ where they had over 55% possession, and were efficient in converting scoring opportunities when they had more than 5 on-target scoring attempts 🎯. The defensive performance was also impressive, with 136 interceptions 🔍 in games where they had more than 50% possession and conceded no goals. They employed a strategy of aggressive offense paired with strong goalkeeping, as indicated by an average of 8.3 saves 🥅 in games where they scored more than 2 goals.

Case Study #4 : Performance statistics of Panathinaikos

In the 2022/23 Super League season, Panathinaikos exhibited a balanced and defensively strong style of play, often maintaining control of the ball ⚽. Their defensive efforts were more successful when they controlled more than 50% of the possession. The team's ability to score more than 2 goals in a match was limited, possibly indicating a need to improve their attacking efficiency 📈. Their formations 433 and 4231 yielded the best results in terms of average goals and possession. The correlation between big chances created and successful offensive actions shows the significance of creating high-quality chances in their games 🎯.

Case Study #5 : Performance statistics of Panaitolikos

Panaitolikos showed some strong offensive performances in the 2022/23 season, especially when playing in a 451 formation ⚽. However, finishing abilities could be improved given the number of on-target scoring attempts resulting in goals 🥅. Defensively, there were solid performances characterized by high numbers of interceptions and ball recoveries 💪, although this did not always correlate with clean sheets 🚫. The team demonstrated a good ability to control the game, reflected in the number of games with over 55% possession 🏆.

Case Study #6 : Performance statistics of Paok

Overall, the 2022/23 Super League season for PAOK suggests a well-rounded performance both offensively and defensively ⚽. Key strategies for success include maintaining high possession 🙌, accuracy in scoring attempts 🎯, and effective use of the 4231 formation 🏆. PAOK's defensive strategy seems to involve a high number of tackles 💪, interceptions 🏃, and ball recoveries ♻️, particularly in games without clean sheets 🚫. Future strategies may benefit from focusing on enhancing ball control 🎛️ and accurate shot attempts 🥅.