RaghuDMT

select season_year,
Fours,
Sixes,
sum(fours*4+Sixes*6) as total_runs_in_boundries 
from (SELECT season.season_year, 
       Sum (CASE 
              WHEN batsman_scored.runs_scored = 4 THEN 1 
              ELSE 0 
            END) AS 'Fours', 
       Sum (CASE 

RaghuDMT

select season_year,
Fours,
Sixes,
[Country_Name],
sum(fours*4+Sixes*6) as total_runs_in_boundries 
from (SELECT season.season_year,country.Country_Name,
       Sum (CASE 
              WHEN batsman_scored.runs_scored = 4 THEN 1 
              ELSE 0 
            END) AS 'Fours', 

RaghuDMT

select  a.Match_Id,c.Player_Name,e.Season_Year,sum([Runs_Scored]) as  [Runs Scored]
from [dbo].[Ball_by_Ball] a 
inner join [dbo].[Batsman_Scored] b 
on concat(a.Match_Id,a.Over_Id,a.Ball_Id,a.Innings_No)=
concat(b.[Match_Id],b.Over_Id,b.Ball_Id,b.Innings_No)
inner join Player c on a.Striker=c.Player_Id 
inner join Match d on a.Match_Id=d.Match_Id 
inner join Season  e on d.Season_Id=e.Season_Id
group by a.Match_Id,c.Player_Name,e.Season_Year
order by 4 desc

RaghuDMT

select  f.Country_Name ,e.Season_Year,sum([Runs_Scored]) as  [Runs Scored]

from [dbo].[Ball_by_Ball] a 
inner join [dbo].[Batsman_Scored] b 
on concat(a.Match_Id,a.Over_Id,a.Ball_Id,a.Innings_No)=
concat(b.[Match_Id],b.Over_Id,b.Ball_Id,b.Innings_No)
inner join Player c on a.Striker=c.Player_Id 
inner join Match d on a.Match_Id=d.Match_Id 
inner join Season  e on d.Season_Id=e.Season_Id
inner join Country f on f.Country_Id=c.Country_Name

RaghuDMT

select v.Venue_Name,  sum(case when([Runs_Scored]=6) then 1 else 0 end) Sixes,count(distinct m.Match_Id) Matches,sum(case when([Runs_Scored]=6) then 1 else 0 end)/count(distinct m.Match_Id) Sixes_Per_Match
from [dbo].[Batsman_Scored]  b 
inner join Match m on b.Match_Id=m.Match_Id
inner join Venue v on v.Venue_Id=m.Venue_Id
group by v.Venue_Name
order by 2 desc

RaghuDMT

select v.Venue_Name,  
sum(case when([Runs_Scored]=4) then 1 else 0 end) Fours,
count(distinct m.Match_Id) Matches,
sum(case when([Runs_Scored]=4) then 1 else 0 end)/count(distinct m.Match_Id) Fours_Per_Match
from [dbo].[Batsman_Scored]  b 
inner join Match m on b.Match_Id=m.Match_Id
inner join Venue v on v.Venue_Id=m.Venue_Id
group by v.Venue_Name
order by 2 desc

RaghuDMT

/****** Script for Top Players with Highest Stike Rates in the middle Overs(7-16) ******/
SELECT 
	  c.Player_Name as Batsman,
	  sum([Runs_Scored]) [Runs Scored],
	  count(concat(a.Over_Id,a.Ball_Id)) [Balls faced],
	  case when (sum([Runs_Scored])<>0) then cast (sum([Runs_Scored])/cast(count(concat(a.Over_Id,a.Ball_Id))as float)as float)*100 else 0 end as Strike_rate
  FROM [IPL].[dbo].[Ball_by_Ball] a 
  inner join [dbo].[Batsman_Scored] b on concat(a.Match_Id,a.Over_Id,a.Ball_Id,a.Innings_No)= 
  concat(b.Match_Id,b.Over_Id,b.Ball_Id,b.Innings_No)

RaghuDMT

https://stackoverflow.com/questions/41065214/reading-a-yaml-file-in-python-and-accessing-the-data-by-matching-key-value-pair
https://gist.github.com/benhosmer/3697171

RaghuDMT

Here is URL of My Tableau Public Profile-->>>> https://public.tableau.com/profile/raghunath1816#!/
I have developed some Reports on IPL Data using Tableau