The ultimate Fabric, Power BI, SQL, and AI community-led learning event. Save €200 with code FABCOMM.
Get registeredEnhance your career with this limited time 50% discount on Fabric and Power BI exams. Ends August 31st. Request your voucher.
I've below data set and need to identify the ranking of "Player" based on their "Score" average.
PlayersMaster
Player | Team | Type |
Player1 | Team1 | Local |
Player2 | Team1 | Overseas |
Player3 | Team2 | Local |
Player4 | Team2 | Local |
Player5 | Team2 | Overseas |
MatchScores
Match | Player | Score |
Match1 | Player1 | 25 |
Match1 | Player2 | 40 |
Match1 | Player3 | 84 |
Match1 | Player4 | 19 |
Match1 | Player5 | 43 |
Match2 | Player1 | 56 |
Match2 | Player2 | 36 |
Match2 | Player3 | 61 |
Match2 | Player4 | 58 |
Match2 | Player5 | 90 |
Match3 | Player1 | 26 |
Match2 | Player2 | 34 |
Match2 | Player3 | 31 |
Match2 | Player4 | 31 |
Match2 | Player5 | 56 |
Please support me in developing below measures.
1. Dynamic Ranking of Players (Top3) based on Average score. (Filtered upon slicer values)
I was able to identify the ranking using below measure. In visual, I just filtered the Top 3 players using a filter. Is there any other better way to achieve this?
2. Overall Ranking of Player, irrespective of slicer values.
Expected Result
Player | Rank | Type | Total |
Player5 | 1 | Overseas | 63 |
Player3 | 2 | Local | 58.67 |
Player2 | 3 | Overseas | 36.67 |
Player4 | 4 | Local | 36 |
Player1 | 5 | Local | 35.67 |
3. Overall Ranking of Player based on Type, irrespective of slicer values
Expected Result
Player | Rank | Type | Total |
Player5 | 1 | Overseas | 63 |
Player3 | 1 | Local | 58.67 |
Player2 | 2 | Overseas | 36.67 |
Player4 | 2 | Local | 36 |
Player1 | 3 | Local | 35.67 |
Thanks in advance
Solved! Go to Solution.
RANK_Type = RANKX( ALLSELECTED( PlayersMaster[Player] ), [Total],,, DENSE )
Rank_Overall =
RANKX(
ALL( PlayersMaster[Player] ),
CALCULATE( [Total], ALLEXCEPT( PlayersMaster, PlayersMaster[Player] ) ),
,
,
DENSE
)
Thanks to the great efforts by MS engineers to simplify syntax of DAX! Most beginners are SUCCESSFULLY MISLED to think that they could easily master DAX; but it turns out that the intricacy of the most frequently used RANKX() is still way beyond their comprehension! |
DAX is simple, but NOT EASY! |
RANK_Type = RANKX( ALLSELECTED( PlayersMaster[Player] ), [Total],,, DENSE )
Rank_Overall =
RANKX(
ALL( PlayersMaster[Player] ),
CALCULATE( [Total], ALLEXCEPT( PlayersMaster, PlayersMaster[Player] ) ),
,
,
DENSE
)
Thanks to the great efforts by MS engineers to simplify syntax of DAX! Most beginners are SUCCESSFULLY MISLED to think that they could easily master DAX; but it turns out that the intricacy of the most frequently used RANKX() is still way beyond their comprehension! |
DAX is simple, but NOT EASY! |
Thanks a lot @CNENFRNL for your reply. However, I'm not clear about the [Total] field that you've used for both measures.
In my expected results I've considered the Average Score for each player as the Total.
Please explain.
Thanks
Total = AVERAGE('MatchScores'[Score])
Thanks to the great efforts by MS engineers to simplify syntax of DAX! Most beginners are SUCCESSFULLY MISLED to think that they could easily master DAX; but it turns out that the intricacy of the most frequently used RANKX() is still way beyond their comprehension! |
DAX is simple, but NOT EASY! |
User | Count |
---|---|
77 | |
77 | |
36 | |
30 | |
28 |
User | Count |
---|---|
106 | |
97 | |
55 | |
49 | |
46 |