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No. | Pos | First Name | Last Name | Avg | AB | R | 1B | 2B | 3B | HR | XBH | RBI | S | BB | FC | K | E | OFA | SLG | OBP | OPS | RC | TAv |
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8 | UTIL | Gwen | Robinson | 0.000 | 1 | 2 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 2 | 0 | 1 | 0 | 0 | 0.000 | 0.667 | 0.667 | 0.000 | 1.000 |
1 | UTIL | Addison | Culver | 0.000 | 1 | 2 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 2 | 0 | 1 | 0 | 0 | 0.000 | 0.667 | 0.667 | 0.000 | 1.000 |
10 | UTIL | Alexis | Contreraz | 0.000 | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 2 | 0 | 1 | 0 | 0 | 0.000 | 0.667 | 0.667 | 0.000 | 1.000 |
9 | UTIL | Alivia | Cook | 0.500 | 2 | 1 | 1 | 0 | 0 | 0 | 0 | 1 | 0 | 1 | 0 | 1 | 0 | 0 | 0.500 | 0.667 | 1.167 | 0.667 | 1.167 |
5 | UTIL | Allison | Ray | 0.000 | 2 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 1 | 0 | 1 | 0 | 0 | 0.000 | 0.333 | 0.333 | 0.000 | 0.500 |
12 | UTIL | Elyse | Miller | 1.000 | 3 | 1 | 3 | 0 | 0 | 0 | 0 | 4 | 0 | 0 | 0 | 0 | 0 | 0 | 1.000 | 1.000 | 2.000 | 3.000 | 2.000 |
3 | UTIL | Hunter | Addy | 0.000 | 3 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 3 | 0 | 0 | 0.000 | 0.000 | 0.000 | 0.000 | 0.000 |
4 | UTIL | Libby | Blackmer | 0.000 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 2 | 0 | 1 | 0 | 0 | 0.000 | 0.667 | 0.667 | 0.000 | 1.000 |
11 | UTIL | Lucy | Goss | 0.500 | 4 | 1 | 2 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 1 | 0 | 0 | 0.500 | 0.500 | 1.000 | 1.000 | 1.000 |
7 | UTIL | Olivia | Landers | 1.000 | 2 | 1 | 1 | 1 | 0 | 0 | 1 | 2 | 0 | 1 | 0 | 0 | 0 | 0 | 1.500 | 1.000 | 2.500 | 3.000 | 2.167 |
2 | UTIL | Sarah | Stone | 1.000 | 2 | 2 | 2 | 0 | 0 | 0 | 0 | 1 | 0 | 1 | 0 | 0 | 0 | 0 | 1.000 | 1.000 | 2.000 | 2.000 | 1.833 |
6 | P | Sienna | Nicol | 0.000 | 1 | 2 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 2 | 0 | 1 | 0 | 0 | 0.000 | 0.667 | 0.667 | 0.000 | 1.000 |
Confused by what some of these abbreviations mean? Check out our Stats Glossary