For the second straight game, McCall-Donnelly will face off against Weiser. The Vandals will welcome the Wolverines at 4:00 p.m. on Wednesday. McCall-Donnelly has a tough task ahead: they'll enter the contest with seven straight losses, while Weiser will come in with nine straight victories.
McCall-Donnelly fell victim to Weiser and their airtight pitching crew on Monday. They lost 10-0 to the Wolverines. The game marked the first time this season in which the Vandals were not able to get on the board.
For Weiser's part, Madi Janicek was a major factor while hitting and pitching. On the mound, she didn't allow a single earned run and allowed only two hits while striking out eight over five innings pitched. Janicek was also stellar in the batter's box, going a perfect 3-for-3 with two runs, one stolen base, and one double.
In other batting news, Ellie Shirts and Sophia Shirts did most of the damage at the plate: Ellie went 2-for-4 with two runs, one triple, and two RBI, while Sophia went a perfect 3-for-3 with one stolen base, two RBI, and one run. That's the most hits Sophia has posted since back in March. Another player making a difference was Natalya Hoobery, who went 2-for-3 with two runs and one RBI.
Weiser kept the outfield on their toes and finished the game with 11 hits. That strong performance was nothing new for the team: they've now got at least eight hits in nine consecutive matchups.
Weiser's win bumped their record up to 10-1. As for McCall-Donnelly, their defeat dropped their record down to 3-10.
The pitchers for both teams better look sharp on Wednesday as neither team is afraid to steal. McCall-Donnelly has been swiping bases left and right this season, having averaged 3 stolen bases per game. However, it's not like Weiser struggles in that department as they've been averaging an even more impressive 3.3 stolen bases. The only question left is which team can snag more. Check MaxPreps after the match for a full breakdown of the game, commentary, and other softball content.
Article generated by infoSentience based on data entered on MaxPreps
