Modern Cricket Analytics: Bowling Efficiency & Match Influence

By abhishek.verma75000 · May 14, 2026

This Datastam analysis presents a data-driven evaluation of bowling performance in modern T20 cricket using advanced metrics such as wickets, bowling…

The analysis identified the top 5 bowlers by total wickets taken. A bar chart has been generated showing each bowler's wicket tally, color-coded by team, making it easy to compare performance across players and teams.

The bowlers with the lowest bowling averages (indicating the best performance) have been identified from the dataset. Mohsin Khan of LSG tops the list with an impressive bowling average of just 11.33, followed by Bhuvneshwar Kumar (RCB) at 16.85 and Anshul Kamboj (CSK) at 16.92. A bar chart and data table have been generated showing the top 10 bowlers with the lowest averages.

The bowlers creating the most pressure through dot balls are led by Mohsin Khan (LSG) with an impressive 51.04% dot ball rate, meaning over half his deliveries are scoreless. A horizontal bar chart and data table have been generated showing the top 10 pressure bowlers ranked by dot ball percentage.

The analysis identified 6 bowlers who recorded match-winning performances through 4-wicket or 5-wicket hauls. Mohsin Khan (LSG) stands out as the only bowler with a 5-wicket haul, while Eshan Malinga (SRH), Prasidh Krishna (GT), Ravi Bishnoi (RR), Jamie Overton (CSK), and Josh Hazlewood (RCB) each recorded one 4-wicket haul. A grouped bar chart has been generated comparing 4WH and 5WH counts for each bowler.

There is a moderate negative relationship between bowling economy rate and impact score across bowlers. This means that bowlers who concede fewer runs per over tend to have higher impact scores — being economical is a meaningful contributor to overall bowling impact. Two visualizations were generated to explore this relationship in detail.

The analysis compared all teams across average wickets per bowler and economy rate. SRH has the strongest wicket-taking ability with 14.0 average wickets per bowler, while LSG boasts the best economy rate at just 7.22. Two scatter plots and a grouped bar chart were generated to visualize these comparisons, along with a full data table.

The IQR-based outlier detection was run across four key bowling metrics: economy, avg, impact, and dot balls. A summary table was generated listing bowlers flagged as outliers and their performance categories. For economy, the IQR bounds were calculated as [5.58, 11.98] (Q1=7.98, Q3=9.58), and no outliers were detected in this metric — meaning all bowlers fall within a normal range for economy. The summary table artifact provides a consolidated view of which bowlers stand out as exceptional or poor performers across the other metrics.

The Pearson correlation matrix for all 8 bowling metrics has been computed and visualized as a color-coded heatmap. The heatmap uses a red-blue scale where deep blue indicates strong positive correlations and deep red indicates strong negative correlations. The strongest positive correlation is between overs and balls (r = 1.000), which makes perfect sense since balls bowled directly determines overs. Runs also correlate strongly with both overs (0.847) and balls (0.846), confirming that workload metrics move together. On the negative side, wickets and avg show the strongest inverse relationship (r = -0.470), meaning bowlers who take more wickets tend to have lower (better) bowling averages. Impact and avg (-0.411) as well as economy and impact (-0.400) also show meaningful negative correlations, revealing that higher-impact bowlers tend to be more economical and have better averages.

A grouped bar chart has been generated comparing bowlers side-by-side across three key performance dimensions: bowling average, economy rate, and impact score — all normalized to a 0–100 scale where higher values indicate better performance. Bowlers are ranked by their composite score, making it easy to spot who excels consistently versus who specializes in one area.

Comprehensive summary statistics were calculated for all 10 numeric bowling columns, and two bar charts were generated showing how each bowler compares to the mean in economy rate and bowling average. The mean economy is 8.78 (range: 6.37–10.34) and the mean bowling average is 21.44 (range: 11.33–32.00). Wickets ranged from 8 to 14 with a mean of 11. Seven bowlers perform better than the mean economy rate (lower is better), led by Bhuvneshwar Kumar, Anshul Kamboj, Jofra Archer, Prince Yadav, and Mohsin Khan. Nine bowlers beat the mean bowling average, including Bhuvneshwar Kumar, Anshul Kamboj, Eshan Malinga, Jofra Archer, and Prince Yadav. The charts color-code each bowler green (better than average) or red (worse than average) for quick comparison.