PUBG Players

By shrijeetverma13 · April 3, 2026

PUBG Players Sample Dataset ek gaming analytics dataset hai jo PlayerUnknown’s Battlegrounds matches me players ki performance ko represent karta hai. Is…

Out of 11 players with zero kills, only 2 (18.2%) managed to achieve a win placement percentage above 0.5. This means the vast majority of players who don't get any kills tend to finish in the lower half of the rankings.

The analysis identified the top 15 most competitive matches based on a combined score of average kills and average damage dealt per player. Two visualizations were generated to explore this: a grouped bar chart showing the top 15 matches with their average kills and damage side by side, and a scatter plot comparing average kills vs. average damage across all matches to reveal overall competitiveness patterns.

Yes! There is an optimal number of weapons acquired. Players who acquired exactly 5 weapons had the highest average win placement percentage at 0.607 (60.7%). A bar chart and data table have been generated showing the full breakdown across all weapon counts from 0 to 10.

Players who travel farther do tend to place slightly higher, but the difference is surprisingly small. The correlation between total distance and win placement is just 0.037, indicating a very weak relationship. Two charts were generated — a box plot showing win placement across distance quartiles and a scatter plot with a trendline — both visually confirming the minimal effect.

Top 25% players use noticeably more heals (4.80 avg) compared to bottom 25% players (3.62 avg), a difference of +1.18. Interestingly, bottom 25% players actually use slightly more boosts (4.28 avg) than top players (3.92 avg). A grouped bar chart has been generated to visually compare these usage rates side by side.

Top 10% players (those with winPlacePerc ≥ 0.85) show moderately higher stats across all three metrics compared to the bottom 90%. On average, they walk 2,807 units (vs 2,658), ride 4,963 units (vs 4,108), and secure 8.0 kills (vs 7.2). Two visualizations were generated: a grouped bar chart comparing average stats between the two groups, and a scatter plot showing walk vs. ride distance with kill count represented by bubble size.

No, players with the highest kills do NOT consistently achieve better win placement outcomes. The data reveals a surprisingly weak correlation of just 0.028 between kills and win placement percentage, meaning kills alone are a very poor predictor of where a player finishes. Two charts and a data table were generated to visualize this relationship.

The analysis examined which players have the highest damage dealt per kill ratio and how this metric relates to win placement. Two visualizations were generated: a scatter plot showing damage per kill ratio vs. win placement percentage, and a bar chart highlighting the top 10 players by this ratio. Out of 200 players analyzed, 189 had at least one kill. The correlation between damage per kill ratio and win placement is nearly zero (-0.023), meaning how much damage a player deals per kill has almost no impact on whether they win or lose.

The analysis examined how kills, damage, distance, heals, boosts, and other metrics correlate with winning placement. A bar chart was generated showing the Pearson correlation coefficients for each metric against win placement percentage. The results reveal that movement-related metrics (walk distance, ride distance) and survival behaviors (boosts, heals) tend to be the strongest predictors of winning, while combat metrics like kills and damage dealt also contribute meaningfully.

The analysis identified the top-performing groups by average win placement percentage (winPlacePerc), with Group 6 emerging as the highest-ranked group. Two visualizations were generated: a bar chart showing the Top 10 Groups by Average Win Place % and a comparison chart contrasting key metrics between top and bottom groups. The charts reveal clear differences in combat and survival behaviors between high and low performers.

The bar chart and data table show the average heals, boosts, and weapons acquired broken down by win placement quartile (Q1 = bottom 25%, Q4 = top 25%). Interestingly, Q2 (25–50th percentile) players show the highest averages for both heals (5.32) and weapons acquired (6.14), while Q1 (bottom performers) have the lowest heals (3.62) and weapons (4.86). Boosts remain relatively consistent across all quartiles, ranging from 3.92 to 4.28.

There is virtually no meaningful relationship between total distance traveled and damage dealt per player. The correlation coefficient is just 0.021, indicating an extremely weak positive link — essentially, how far a player travels has almost no bearing on how much damage they deal.

The analysis produced two visualizations comparing how players' preference for riding versus walking affects their win placement percentage (winPlacePerc). A bar chart shows the average win placement broken down into three movement groups — Walk-focused, Mixed, and Ride-focused — and a scatter plot illustrates the relationship between ride distance ratio and win placement across all players.

The bar chart visualizes how average winPlacePerc varies across different group sizes (number of players per group). Each bar represents a group size, with the height showing the average win placement percentile and labels indicating how many groups exist at that size. This lets you directly compare whether larger squads tend to place better or worse than solo/duo players.

A data table was generated comparing win placement percentages across different playstyles — Aggressive (high kills + high damage), Passive (low kills + low damage), and Mixed players. The table breaks down average and median win placement percentages along with player counts and average stats for each group, giving a clear picture of how combat style relates to finishing position in matches.

The analysis identified the top 20 matches with the widest spread in winPlacePerc, which indicates the most unbalanced player skill levels. A bar chart was generated showing each match's spread (calculated as max minus min winPlacePerc), colored by standard deviation to highlight variability. Matches with a spread close to 1.0 contain the most diverse mix of skill levels — from very weak to very strong players in the same game.