#WBBL: Scoring and Strike Rates

Two recent games (43 and 44) in this season’s #WBBL (link) raised for me some interesting issues about game management. My data for the tournament indicate that the median winning score is 147 runs and a losing median is 136.

Game 43

In Game 43, the Perth Scorchers played the Sydney Sixers at Lilac Hill, Perth (link). The Sixers won the toss and elected to field. The Scorchers won the game by 52 runs. When the Scorchers batted they scored 152 runs for the loss of 5 wickets. The Sixers were 100 for 9 at the end of their innings. With a score of 152, I estimated that Perth would have to apply enough pressure that took wickets every 15 per balls. The Sixers would have to resist this pressure to score and above median score to win. At that point, only two games had been won batting second and scoring more than 152 runs.

My ggplot of the data:

Game 44

In Game 44, the Melbourne Stars played the Melbourne Renegades at Ballatrat (link). The Stars won the toss and elected to field. The Stars won the game by 7 wickets. When the Renegades batted they scored 165 runs for the loss of 3 wickets. The Stars were 169 for 3 at the end of their innings. With a score of 165, I estimated that the Renegades would have to apply enough pressure that took wickets every 17 per balls. The Sixers would have to resist this pressure to score and above median score to win. At that point, no game had been won by the team batting second and scoring that may runs.

My ggplot of the data:

Discussion

The two games raise interesting issues. One team chased down a higher than medium score and in doing so became the first team to bat second to score that many runs. A second team managed 100 runs batting second. I hope the ggplots in this post illustrate these differences. I do think they raise questions about how we prepare for games and how players (and coaches) respond within games.

Photo Credit

Adelaide Strikers (Twitter)

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