Green Little Statistician

COLLABORATION ALERT! 🤝🏼 🚨 🤝🏼

We're thrilled to announce our collaboration with 'Aladeen Ka Chiragh', a delivery platform operating at LUMS. In this partnership, we take on the responsibility of managing all their data.

Aladeen Ka Chiragh operates as a student-driven delivery platform, bridging customers with individuals available for delivery services. Their unique supply-demand price bargaining model aims to address delivery challenges efficiently. The standout thing is the opportunity for students to earn more than a university graduate while working much fewer hours. Unlike other platforms, they do not draw commissions from our genies (delivery personnel).

To kick things off, we've attached some fascinating insights from their pilot run, spanning the past five weeks.

For more such content, keep following us!

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EPL - Result Predictor 1.0

How many times have you heard students saying why are we even studying Mathematics & what exactly is the practical application of Mathematical Concepts? A lot, right? Credit goes to our education system, which focuses only on the theoretical part of the knowledge & doesn't teach students to translate theory to practicality for solving real-world problems.

With the English Premier League (EPL) around the corner, we thought we should come up with something interesting to inspire people & show them the power of Data, Statistics, & Mathematics. Therefore, we are releasing our work, 'English Premier League (EPL) - Result Predictor 1.0'.

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| 𝗜𝗡𝗧𝗥𝗢𝗗𝗨𝗖𝗧𝗜𝗢𝗡 𝗧𝗢 𝗧𝗛𝗘 𝗗𝗔𝗧𝗔𝗦𝗘𝗧 |

We collected multiple datasets from different resources which then underwent rigorous merging and cleaning. Majority of our time and energy were spent on data collection, data merging, and data cleaning.

The dataset had around 11,184 observations and 12 variables. Following are the details about the variables:

01) "𝗚𝗼𝗮𝗹 𝗗𝗶𝗳𝗳𝗲𝗿𝗲𝗻𝗰𝗲 𝘄.𝗿.𝘁 𝗛𝗼𝗺𝗲 𝗧𝗲𝗮𝗺" is the difference between the goals scored by home team and away team, with respect to the home team. Goal difference would be positive if home team wins, negative if home team loses, and zero in case of a draw. It's a numerical discrete variable (integer). Examples: 2, -3, 0, etc.

02) "𝗠𝗮𝘁𝗰𝗵𝗲𝘀 𝗣𝗹𝗮𝘆𝗲𝗱 (𝗛𝗼𝗺𝗲 𝗧𝗲𝗮𝗺)" is the total number of matches played by the home team at the home venues across all the seasons. It's a numerical discrete variable (integer). Examples: 38, 342, 534, etc.

03) "𝗠𝗮𝘁𝗰𝗵𝗲𝘀 𝗣𝗹𝗮𝘆𝗲𝗱 (𝗔𝘄𝗮𝘆 𝗧𝗲𝗮𝗺)" is the total number of matches played by the away team at the away venues across all the seasons. It's a numerical discrete variable (integer). Examples: 38, 342, 534, etc.

04) "𝗟𝗮𝘀𝘁 𝗬𝗲𝗮𝗿'𝘀 𝗣𝗼𝗶𝗻𝘁𝘀/𝗠𝗮𝘁𝗰𝗵𝗲𝘀_𝗣𝗹𝗮𝘆𝗲𝗱 (𝗛𝗼𝗺𝗲 𝗧𝗲𝗮𝗺)" is the ratio of points scored and matches played in last season by the home team at home venues. It's a numerical continuous variable (real numbers). Examples: 2.41, 1.95, 1.62, etc.

05) "𝗟𝗮𝘀𝘁 𝗬𝗲𝗮𝗿’𝘀 𝗣𝗼𝗶𝗻𝘁𝘀/𝗠𝗮𝘁𝗰𝗵𝗲𝘀_𝗣𝗹𝗮𝘆𝗲𝗱 (𝗔𝘄𝗮𝘆 𝗧𝗲𝗮𝗺)" is the ratio of points scored and matches played in last season by the away team at away venues. It's a numerical continuous variable (real numbers). Examples: 2.41, 1.95, 1.62, etc.

06) "𝗧𝗶𝘁𝗹𝗲𝘀 𝗪𝗼𝗻 (𝗛𝗼𝗺𝗲 𝗧𝗲𝗮𝗺)" is the number of titles won by the home team. It's a numerical discrete variable (integer). Examples: 13, 2, 0, etc.

07) "𝗧𝗶𝘁𝗹𝗲𝘀 𝗪𝗼𝗻 (𝗔𝘄𝗮𝘆 𝗧𝗲𝗮𝗺)" is the number of titles won by the away team. It's a numerical discrete variable (Integer). Examples: 13, 2, 0, etc.

08) "𝗟𝗮𝘀𝘁 𝗬𝗲𝗮𝗿'𝘀 𝗦𝗮𝘃𝗲𝘀 𝗣𝗲𝗿𝗰𝗲𝗻𝘁𝗮𝗴𝗲 (𝗛𝗼𝗺𝗲 𝗧𝗲𝗮𝗺)" is the saves percentage of home team for the last season. It's a numerical continuous variable (real numbers). Examples: 81.1, 69.2, 72.4, etc.

09) "𝗟𝗮𝘀𝘁 𝗬𝗲𝗮𝗿'𝘀 𝗦𝗮𝘃𝗲𝘀 𝗣𝗲𝗿𝗰𝗲𝗻𝘁𝗮𝗴𝗲 (𝗔𝘄𝗮𝘆 𝗧𝗲𝗮𝗺)" is the saves percentage of away team for the last season. It's a numerical continuous variable (real numbers). Examples: 81.1, 69.2, 72.4, etc.

10) "𝗗𝗮𝘆" is the day of the week on which the match was played. It's a categorical variable.
Examples: Sunday, Friday, Monday, etc.

11) "𝗪𝗲𝗲𝗸" is the week number of the season in which the match was played. It's numerical discrete variable (integer). Examples: 14, 38, 1, etc.

12) "𝗬𝗲𝗮𝗿" is the year in which the match was played. It's a numerical discrete variable (integer). Examples: 1993, 2004, 2021, etc.

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All the match predictions & results will be shared in the comments section.

Stay Tuned!

For cooperation, special thanks to:
Ahtisham Ali Jan
Ali Haider
Hassan Mujtaba
Sajid Karim

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Let's pour some Mathematics into Premier League as we grow Bigger and Better!

Sounds Crazy, No? Stay Tuned!

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PSL - Score Predictor 1.1 (Revised Edition)

In the last few days, we have received a lot of requests regarding the Pakistan Super League (PSL) Predictions.

Due to prior commitments, we couldn't build an entirely new model. However, to feed your appetite during the PSL, we are releasing the "PSL - Score Predictor 1.1", a revised edition of our previous model.

You might find some minor flaws in the model, as it was initially built quite a while ago. However, it will do pretty well at making predictions.

| BRIEF OVERVIEW |
How often have you heard people asking what exactly is the practical application of mathematical concepts and why are we even studying mathematics? A lot, right?

With the eighth season of PSL around the corner, we have come up with something interesting to inspire you and show you the power of data, statistics, and mathematics.

Using the data from past years, we have tried to come up with a mathematical equation that can be used to predict the "First Innings Score" of PSL matches.

For matches in Lahore, the equation is:
𝗙𝗜𝗦 = 𝟭𝟲𝟯 + 𝟬.𝟲𝟬 𝗣𝗦 - 𝟭𝟭.𝟮𝟱 𝗣𝗗

For matches in Karachi, the equation is:
𝗙𝗜𝗦 = 𝟭𝟱𝟳 + 𝟬.𝟲𝟬 𝗣𝗦 - 𝟭𝟭.𝟮𝟱 𝗣𝗗

For matches in Rawalpindi, the equation is:
𝗙𝗜𝗦 = 𝟭𝟳𝟯 + 𝟬.𝟲𝟬 𝗣𝗦 - 𝟭𝟭.𝟮𝟱 𝗣𝗗

For matches in Multan, the equation is:
𝗙𝗜𝗦 = 𝟭𝟲𝟱 + 𝟬.𝟲𝟬 𝗣𝗦 - 𝟭𝟭.𝟮𝟱 𝗣𝗗

Here,
FIS = First Innings Score
PS = PowerPlay Score
PD = PowerPlay Dismissals

Feel free to test the model by simply plugging in the values for PS and PD to get the predicted FIS. All the match predictions and results will also be shared in the comments section of this post. Stay tuned!

For more details regarding the initial model, feel free to visit the following post:
https://m.facebook.com/story.php?story_fbid=104737345476893&id=104180745532553&mibextid=Nif5oz

For more such content, keep following us!



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The Eighth Season of Pakistan Super League is all set to kickoff.

Here are a few of our previous visualizations to convey some interesting stats to you regarding the league.

For more such content, keep following us! ✨

We are thrilled to share that "Miss Junglee", from the Jungles of Africa, has joined the party!

Miss Junglee has a vast experience in the field of Life Sciences, especially regarding Wild Life. She will be working very closely with Dr. Jasmine on our upcoming projects.

She is not only a great addition to our and , but she will also serve as a source of inspiration for hundreds of women out there following us.

Stay tuned for more exciting content!

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Annie seems quite happy as we are now a diverse family of more than 2.5K people with all sorts of gender, regional, & cultural representations.

Thank you very much for all your love throughout the journey, especially during the ICC T20 World Cup.

You can always support & help us by inviting your friends to follow our page. It will increase our audience & motivate us to create more such content.

We have a lot of exciting things lined up for you. Stay tuned!

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T20I CWC 2022 - Result Predictor 1.0

How many times have you heard students saying why are we even studying Mathematics & what exactly is the practical application of Mathematical Concepts? A lot, right? Credit goes to our pathetic education system, which focuses only on the theoretical part of the knowledge & doesn't teach students to translate theory to practicality for solving real-world problems.

With the ICC T20 World Cup around the corner, we thought we should come up with something interesting to inspire you & show you the power of Data, Statistics, & Mathematics. To take your cricket madness to the next level, we are making one of our projects, titled "T20I CWC 2022 - Result Predictor 1.0", public.

We'll be using variables such as 'Year', 'Round', 'Time', 'Toss Decision', & 'First Innings Score' to predict the 'Winner' of a particular match. For more details, please refer to the content attached with the post.

All the match predictions & results will be shared in the comments section.

Stay Tuned!



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