T20 World Cup 2026 Match Dataset

By ranjeetverma3084 · January 25, 2026

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The analysis reveals how match totals and team performance metrics vary across different tournament stages. A comprehensive visualization was created showing four key dimensions: average match totals with variability, team form comparisons, technical index levels, and average rankings for both teams across each stage.

The Match Total scores during the February to March 2026 tournament period showed considerable variation, with an average of 167 runs per match across 600 matches. The visualization displays the daily fluctuations in match totals throughout this period, with a red dashed line indicating the tournament average.

The analysis successfully examined team appearances and average form ratings across the dataset. A scatter plot visualization was created showing the relationship between how frequently teams appear and their average form ratings, with teams sized by appearance count and colored by form rating (green for higher form, red for lower).

The analysis reveals that home advantage has a modest positive correlation with team form. Team A shows a stronger correlation (0.286) between having home advantage and their form compared to Team B (0.184). However, the majority of matches (532 out of 600) were played at neutral venues, with only 43 matches where Team A had home advantage and 25 where Team B had home advantage.

No, there is not a strong relationship between team form and Tech Index for predicting high-scoring matches. The analysis reveals very weak correlations for both metrics.

A visualization was created comparing higher-ranked teams against lower-ranked teams across Tech Index and Form metrics. The chart displays the average values for both groups, allowing you to see whether higher-ranked teams consistently outperform their lower-ranked opponents.

The analysis reveals distinct patterns in toss decisions across different pitch types and venues. Overall, teams chose to field first in 315 matches (52.5%) compared to batting first in 285 matches (47.5%). Two interactive visualizations show how these preferences vary significantly based on pitch conditions and venue characteristics.

Flat pitches produce the highest average Match Total scores at 180.3 runs, while Spin-Friendly pitches produce the lowest at 155.4 runs. This analysis is based on 171 matches played on Flat pitches and 251 matches on Spin-Friendly pitches.

The analysis examined match distribution across 7 different venues, showing both total matches and knockout-stage games at each location. A grouped bar chart was created to visualize the comparison between total matches and knockout matches at each venue.

The Tech Index threshold that separates top-tier teams from average performers is approximately 253 . This represents the 75th percentile, meaning teams scoring above this level are in the top 25% of all teams analyzed.

The analysis identified the most one-sided team matchups based on head-to-head records. A visualization was created showing the top 15 most dominant rivalries, ranked by the winning percentage of the dominant team in each matchup. Only matchups with at least 3 games played were included to ensure meaningful patterns.

The analysis reveals that Ahmedabad produces the highest average Match Total scores at 181.6 runs. When comparing across pitch types, Flat pitches generate the highest scoring matches with an average of 180.3 runs, while Spin-Friendly pitches produce the lowest scores at 155.4 runs on average.

The analysis identified matches with the largest ranking gaps between competing teams, which are prime candidates for potential upsets. A visualization was created showing the top 15 matches ranked by the difference in team rankings, with the data displayed in an interactive bar chart using a color scale to highlight the magnitude of each gap.

Approximately 37% of matches feature evenly-matched teams based on ranking differences under 5. Specifically, 221 out of 600 total matches have teams with ranking differences of less than 5 positions apart.

The analysis identified 57 matches that exceeded 200 total runs and examined which combinations of venue, pitch type, and team form produced these high-scoring games. A visualization was created showing the top venue-pitch combinations ranked by frequency of high-scoring matches, with color coding indicating the average team form for each combination.

The average T20 score at a venue has weak predictive accuracy for actual match totals. While there's a moderate positive correlation (0.442), the venue average only explains about 20% of the variation in actual scores. On average, predictions are off by about 18 runs, though 65% of predictions fall within ±20 runs of the actual total.

The analysis reveals which teams maintain consistent form ratings versus those with high variability. A scatter plot has been generated showing each team's average form rating on the x-axis and their form variability (standard deviation) on the y-axis, with bubble sizes representing the number of matches played.

Yes, knockout stage matches do show different scoring patterns compared to group stage matches. Knockout matches average 4.6 runs higher per match (171.2 vs 166.6), though the difference is relatively modest.