NEITHER TEAM HAS UNITS EDGE Baltimore OriolesĪCCUSCORE ADVISOR: AccuScore simulates every game thousands of times one play at a time. PAST 30 DAYS: We advise incorporating these trends along with the current Season after the first 6 to 8 weeks. UNITS EDGE FAVORS: Baltimore Orioles Baltimore Orioles He has a 41% chance of having a big game with 3+ Hits, Walks, RBI and if he has a big game the Orioles have a 58% chance of winning.ĬURRENT SEASON: We advise relying on these trends after the first 6 to 8 weeks of the season. The most productive batter for the Baltimore Orioles is Austin Hays who averaged 2.35 hits+walks+RBI. He has a 53% chance of having a big game with 3+ Hits, Walks, RBI and if he has a big game the White Sox have a 65% chance of winning.
The most productive batter for the Chicago White Sox is Tim Anderson who averaged 2.83 hits+walks+RBI. In simulations we tracked the batter for each team that was most productive based his average hits, walks and RBI per simulation.
He has a 10% chance of having a 5 to 1 K/BB ratio and if he does his team wins 67% of simulations. In Spenser Watkins quality starts the Orioles win 67%. When he has a 5/1 ratio the White Sox win 64%. His simulated strikeout to walk ratio is 2.7 and he has a 15% chance of having a 5 to 1 K/BB ratio. If Lance Lynn (p) has a quality start the White Sox has a 80% chance of winning. Lance Lynn (p) has a 46% chance of having a Quality Start (QS) while Spenser Watkins has a 32% chance of a QS. White Sox\' starter Lance Lynn (p) is forecasted to have a better game than Orioles\' starter Spenser Watkins. The White Sox have a better than 55% chance of winning based on 10,000 game simulations generated one play at a time by the AccuScore Simulation Supercomputer. All images are property the copyright holder and are displayed here for informational purposes only.The Chicago White Sox are 15-17 at home this season and are solid favorites to beat the Baltimore Orioles who are 13-22 on the road this season. Many historical player head shots courtesy of David Davis. Some high school data is courtesy David McWater.
Some defensive statistics Copyright © Baseball Info Solutions, 2010-2022. Total Zone Rating and initial framework for Wins above Replacement calculations provided by Sean Smith.įull-year historical Major League statistics provided by Pete Palmer and Gary Gillette of Hidden Game Sports. Win Expectancy, Run Expectancy, and Leverage Index calculations provided by Tom Tango of, and co-author of The Book: Playing the Percentages in Baseball.
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