You are now a sqlite data analyst, and you are given a database schema as follows:

    【Schema】
    【DB_ID】 regional_sales
【Schema】
# Table: Customers
[
(CustomerID:INTEGER, Primary Key, Examples: [1, 2, 3]),
(Customer Names:TEXT, Examples: [Avon Corp, WakeFern , Elorac, Corp])
]
# Table: Sales Team
[
(SalesTeamID:INTEGER, Primary Key, Examples: [1, 2, 3]),
(Sales Team:TEXT, Examples: [Adam Hernandez, Keith Griffin, Jerry Green]),
(Region:TEXT, Examples: [Northeast, West, South])
]
# Table: Sales Orders
[
(OrderNumber:TEXT, Primary Key, Examples: [SO - 0001000, SO - 0001001, SO - 0001002]),
(Sales Channel:TEXT, Examples: [In-Store, Online, Distributor]),
(WarehouseCode:TEXT, Examples: [WARE-UHY1004, WARE-NMK1003, WARE-PUJ1005]),
(ProcuredDate:TEXT, Examples: [12/31/17, 4/10/18, 7/19/18]),
(OrderDate:TEXT, Examples: [5/31/18, 6/1/18, 6/2/18]),
(ShipDate:TEXT, Examples: [6/14/18, 6/22/18, 6/21/18]),
(DeliveryDate:TEXT, Examples: [6/19/18, 7/2/18, 7/1/18]),
(CurrencyCode:TEXT, Examples: [USD]),
(_SalesTeamID:INTEGER, Examples: [6, 14, 21]),
(_CustomerID:INTEGER, Examples: [15, 20, 16]),
(_StoreID:INTEGER, Examples: [259, 196, 213]),
(_ProductID:INTEGER, Examples: [12, 27, 16]),
(Order Quantity:INTEGER, Examples: [5, 3, 1]),
(Discount Applied:REAL, Examples: [0.075, 0.05, 0.1]),
(Unit Price:TEXT, Examples: [1,963.10, 3,939.60, 1,775.50]),
(Unit Cost:TEXT, Examples: [1,001.18, 3,348.66, 781.22])
]
# Table: Products
[
(ProductID:INTEGER, Primary Key, Examples: [1, 2, 3]),
(Product Name:TEXT, Examples: [Cookware, Photo Frames, Table Lamps])
]
# Table: Regions
[
(StateCode:TEXT, Primary Key, Examples: [AL, AR, AZ]),
(State:TEXT, Examples: [Alabama, Arkansas, Arizona]),
(Region:TEXT, Examples: [South, West, Northeast])
]
# Table: Store Locations
[
(StoreID:INTEGER, Primary Key, Examples: [1, 2, 3]),
(City Name:TEXT, Examples: [Birmingham, Huntsville, Mobile]),
(County:TEXT, Examples: [Shelby County/Jefferson County]),
(StateCode:TEXT, Examples: [AL, AR, AZ]),
(State:TEXT, Examples: [Alabama, Arkansas, Arizona]),
(Type:TEXT, Examples: [City, Town, CDP]),
(Latitude:REAL, Examples: [33.52744, 34.69901, 30.69436]),
(Longitude:REAL, Examples: [-86.79905, -86.67298, -88.04305]),
(AreaCode:INTEGER, Examples: [205, 256, 251]),
(Population:INTEGER, Examples: [212461, 190582, 194288]),
(Household Income:INTEGER, Examples: [89972, 78554, 76170]),
(Median Income:INTEGER, Examples: [31061, 48775, 38776]),
(Land Area:INTEGER, Examples: [378353942, 552604579, 361044263]),
(Water Area:INTEGER, Examples: [6591013, 3452021, 105325210]),
(Time Zone:TEXT, Examples: [America/Chicago, America/Phoenix, America/Los Angeles])
]
【Foreign keys】
Sales Orders._ProductID=Products.ProductID
Sales Orders._StoreID=Store Locations.StoreID
Sales Orders._CustomerID=Customers.CustomerID
Sales Orders._SalesTeamID=Sales Team.SalesTeamID
Store Locations.StateCode=Regions.StateCode

    【Question】
    How many orders were shipped by the sales team with the highest amount of shipped orders in 2020? Give the name of the said sales team. shipped refers to ShipDate; in 2020 refers to SUBSTR(ShipDate, -2) = '20'; highest amount of shipped orders refers to Max(Count(OrderNumber))

    【Evidence】
    shipped refers to ShipDate; in 2020 refers to SUBSTR(ShipDate, -2) = '20'; highest amount of shipped orders refers to Max(Count(OrderNumber))

    Please read and understand the database schema carefully, and generate an executable SQL based on the user's question and evidence. 

SQL: SELECT COUNT(T1.OrderNumber), T2.`Sales Team` FROM `Sales Orders` AS T1 INNER JOIN `Sales Team` AS T2 ON T2.SalesTeamID = T1._SalesTeamID WHERE T1.ShipDate LIKE '%/%/20' GROUP BY T2.`Sales Team` ORDER BY COUNT(T1.OrderNumber) DESC LIMIT 1