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# UFC Fighters winrate - Exploratory Data Analysis (EDA)
Author: stiven rodriguez
Course: Introduction to Data Science
Assignment: EDA & Dataset Analysis
Dataset Source: Kaggle – UFC Fighters' Statistics Dataset
Dataset Size: ~4,112 rows × 18 column
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## Project Goal
The Project Goal was answer the question : What are the defining attributes—both physiological
(physical) and strategic (fighting style)—that characterize the ultimate mixed martial arts fighter?
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## Dataset Overview
The dataset contains information about UFC Fighters winrate with the following key columns:
- **name**
- **height_cm**
- **weight_in_kg**
- **stance**
- **Age**
- **reach_in_cm** - Arm span length (cm)
- **stance**
- **Strikes/Min** - significant_strikes_landed_per_minute
- **Strike Accuracy** - significant_striking_accuracy
- **Absorb/Min** - significant_strikes_absorbed_per_minute
- **Strike Defense** - significant_strike_defence
- **Takedowns/Fight** - average_takedowns_landed_per_15_minutes
- **TD Defense** - takedown_defense
- **Submissions/Fight** - average_submissions_attempted_per_15_minutes
- **TD Accuracy** - takedown_accuracy
- **total_fights**
- **win_rate**
The final dataset is the result of systematic cleaning, validation, and filtering procedures
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## Data Cleaning Summary
- Selected 13 relevant columns from the original 18 columns for analysis, and subsequently engineered 3 new features.
- Handling Non-Informative & Duplicates
- Missing Value Handling, Removing Fighters with 3 or More Missing Columns
- Filtering 3 Fighters Due to Missing Height Data
- Filtering Fighters with Missing Date of Birth
- Filling Missing 'Reach' Values with the Mean
- Filling Missing 'Stance' Values with 'Unknown
- Column Renaming for Readability
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## Research Questions & Insights
### *Q1: "Does age influence the win rate (WINRATE) of UFC fighters, and what is the distribution of ages among the fighters in the dataset?
**Visualization : barplot**
#The graph does not include fighters over the age of 38,
![UFC fighter age distribution](https://i.postimg.cc/VLLKfB6h/Screenshot-2025-11-19-203829.png)
*Click on the image above to view it in full size*
**Insight:**
- My conclusions are that age is highly significant for successfully entering the UFC (meaning fighters need many wins on the way,
which often happens around age 30+). However, within the UFC, there is no correlation between a fighter's age and their win rate (WINRATE)
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### *Q2: Is there a correlation between a physical variable or fighting style with the Win rate?
**Visualization: Correlation Heatmap of Variables**
![Correlation Heatmap](https://i.postimg.cc/rFFfVCmQ/Screenshot-2025-11-19-203753.png)
*Click on the image above to view it in full size*
**Insight:**
- The analysis suggests that there is no strong predictive variable for success, given the consistently weak correlations found across all features.
- Despite this, the maximum correlation observed was specifically associated with measures of a fighter's 'aggressive behavior during the bout.'
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### *Q3: Given that a fighter possesses all the 'aggressive' attributes with a positive correlation to victory, are these traits sufficient,
on their own, to reliably predict or guarantee a high Win Rate?
**Visualization: Correlation Heatmap of Variables**
![Multivariate Correlation map](https://i.postimg.cc/L66x9BXw/Screenshot-2025-11-19-203857.png)
*Click on the image above to view it in full size*
**Insight:**
- The conclusion is negative. While 'aggressive' attributes demonstrated the highest (positive) correlation with victory, these traits are not sufficient on their own
- to reliably predict or guarantee a high Win Rate. This determination is based on the finding that the overall correlation remains extremely low,
- even when considering the three most highly correlated variables—a fact visually evident in the data you referenced
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## Final Conclusions
*Main Research Question:* What are the defining attributes—both physiological (physical) and strategic
- (fighting style)—that characterize the ultimate mixed martial arts fighter?
*Answer:* My analysis indicates that no single variable with a strong positive correlation can be identified or
- relied upon to define the ultimate mixed martial arts fighter. Nevertheless, the data does suggest that a
- fighter's aggressive behavior during a bout is a key strategic factor that statistically elevates the probability of achieving a victory
### Key Findings:
- Physiological Attributes: Body measurements and physical characteristics (such as Height, Reach, or Leg length) show no significant correlation with a fighter's
- probability of victory (WINRATE). This suggests that success in the UFC is not determined by inherent physical size.
- Strategic Aggression: Successful Takedowns (control metrics) and Strikes Accuracy (offensive volume metrics) were found to be the variables with the highest positive
- correlation with victory among all examined features.
- Predictive Limitation: Despite being the top-correlated factors, the relationship between these aggressive metrics and the final outcome is still relatively weak.
- Therefore, while Takedowns and Strike Accuracy are important strategic advantages, they are not sufficient on their own to reliably predict or guarantee a high Win Rate.
### Overall Insights:
- There is no single parameter that can be truly relied upon to predict victory.
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## Video (https://www.veed.io/view/7decd8ee-9454-4b39-bbf0-48876d30fc42?source=editor&panel=share)