The National Football League (NFL):

The National Football League (NFL) is a professional American football league that consists of 32 teams, divided equally between the American Football Conference (AFC) and the National Football Conference (NFC).

The NFL is one of the major North American professional sports leagues and the highest professional level of American football in the world. The NFL, the NFL Players Association (NFLPA), and Dapper Labs Inc. Aug 18th announced that NFL ALL DAY -- the exclusive digital video highlight NFT platform -- is officially open and available to fans worldwide, just ahead of the 2022 NFL season.

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Goal:

The goal of this dashboard is to determine which parameter, player or play type, is more important and has more impact on NFT sales volume.

let start with 10 Tops

at first step I want to show distribution of top ten based on Sale Volume both Play Top and NFT Top. one information that can get from this charts is “is there any centrality in each group”. it means if with select a few of slices in donut we get most of the donut. and shows

Not homogeneously distributed. And there are parts that are much bigger than others. These larger sections indicate their greater influence.

as we see in Charts, in Play Type based on Sale Volume Top Three

Play Type Contain about 80% of Volume while we need more than 7 people to get 80% of top ten. The result of this discussion is that Play Type Sale Volume relies on a certain few Types while in Player Name has evenly distributed.so this metric shows Specific Play Type maybe has more effect than Player Name in Sale Volume

this chart is a bit more specific than others. but first let me say how this chart drawn.

picked of top 10% of player with most Sale Volume.
find NFTs of them.
find most repeated type in each player and show how many percateage of this player NFTs has this type. ( for example in second bar we have b>= 90% ,21. this means we have 21 player in top 10% that more than 90 of theier NFTs are in one type. )

now we know how this chart work and what information we get from chart.there is 15 player that just have one type NFT.from this chart we can get two type of result.

Type is More Impactable than player
Player are more stronger in one type than others

we have another chart like this in previous part. but there have different. in this chart we just have top 10% of player instead of all.

but result has about same and has a bit diffrent. The only easily recognizable change is change of Pass percentage. seems pass is more popular among top players.other big Type have about same ratio

this chart separate between sale volume of each player. but has one extra data. show Play Type of NFTs .as color and chart shows must of Sale volume came from top three Play Top.

this statics information of top 10% player has some information that help us in finding result.

but what is this information. in static Median and Average usually represent information of whole group. but Min and Max shows single item. in this chart some of items has big gap between Median (or Average) between Min and Max. it can be concluded in two ways

we are now in bear market and NFT price drop so median and average and min value are close and far of Max
player maybe sometimes has popular and unpopular Group Type NFT and make new Mix or Max. for example in Aaron Rogers we clearly see Max Value has big gap with other and so this maybe because has one NFT with some specialty (like play Type).

Methodology:

In this dashboard, I used:

core.ez_nft_sales table. All sales data are available in this table.
core.dim_allday_metadata table. All information about games, players, and overall NFTs are available in it.

To find out which one, player or play type has more impact on the sales volume, I performed the analysis in three separate parts.

First, only between the top 10 players and also the top 10 play types in terms of sales volume.
Second between top 10% of players and top 10% of play types in terms of sales volume.
Third among all players and all play types.

The following topics are shown in this dashboard:

Top 10 players/play types whose NFTs have the highest volume of sales.
The top 10 combinations of players and the play type whose NFTs have the highest volume of sales.
The top 10 combinations of players and the type of game whose NFTs have the highest number of sales.
In the top 10% of players, How many have a certain percentage of their NFTs belonging to one play type?
In the top 10% of players, what is sales volume of each play type?
Average, median, max, and min of NFTs sales for each player.
In the top 10% of play types, what is sales volume of each player?
Average, median, max, and min of NFTs sales for each play type.
Overview information.
Player Name Vs Play Type.
Total sales volume/sales count of each player.
Total sales volume/sales count of each play type.
Top 3 player based on volume on each week.
Top 3 play type based on volume on each week.
The number of NFTs of each player/ play type.

while in top 10% of players each player has limited number of group. but in. top 10% of players type there is large number of players and all of this belong to two group. so we can result this as The thing that increases the probability of sales to a great extent is Group Type. Because most of the best sellers are from a certain group.

in top 10% play type we don't have Single Player that share large part of donut while in Player Name top three Type fill 80% of donut so this is another sign that Type of player has more effect than Name of Player.

Play Type seems to guarantee minimum sales for a player. While this Min is more than Max, the amount of sales of some players is higher. Also, the high and equal level of the median and the average also indicate that this price is guaranteed.

when compare two compare types that each player have and players that each play type have . we clearly see players have limited type while one Type Contain lot's of player. but one intersing thing there in in both charts.in both charts has spikes in some bar. for player clearly see types like Reseption and Pass cuase this happen. in other side we see Reseption and Pass type has much higher volume while this high volume doesn't belong to specific player. so this show play type has more effect than player name

I thing this chart tell whole story of this article. most of big circle are for top three type while this circle distributed among all player. other type just own small circle that Represent small sell volume.

These charts show one of the high volume player in week 1 is Justin Herbert. The sales volume of this player growth 30K % than previous week. I was interested to follow this player's performance in the real world.

"Herbert has steadily improved his play since taking over as QB1 in Week 2 of 2020, but he looks poised to take even bigger strides in his second season with OC Joe Lombardi. Herbert is going to be more comfortable, and the loaded Chargers defense is going to give him more chances, which will help boost Herbert's production and confidence. link“

the beutiful thing about Sale Count and Volume is both of them have about same pattern.This indicates non-dependence of Play Type becuase there no other thing than Play Type to increase Volume seprately.

while when review Play Type is say play type in non-dependence with

Looking at the charts of the count and volume of sales of players, we fully understand that factors apart from all players are effective in sales and sales prices. in some charts, the sales volume is not proportional to the price. This indicates two factors. Either the player's NFT is bought and sold at a high price, or there is a factor (such as Play Type) that affects the price.

from top 3 player each week we see some player repeated some times in list Tom Brady with 8 times is most repeated player in top player and next Patrick Mahomes II with 4 times repeatd. beside this 28 player are in this list. list of reapted name are as bellow

1 player with 8 times repeat (Tom Brady )
1 player with 4 times repeat ( Patrick Mahomes II )
3 player with 3 times repeat ( Ja'Marr Chase , Davante Adams , Justin Herbert )
2 player with 2 times repeat ( Russell Wilson , Tyreek Hill )
21 player with 1 times repeat ( others )

this shows some player has more popularity and people more like to buy their NFT than others

We see that One Two has a secure position among the top three. and usually other play type fight for third place.this clearly shows Reception and Pass has more popularity.

at least part of overall information I want to show number of NFT each Type and Player. There are some information like Tom Bradly has most Sale Volume and Most Repeated Name in Top 3 of each week just has 3 NFT while there lot’s of player that had more NFT and all of them has less Sale.in Type side also “Pass” has second most sale Volume while is in forth place of Number of NFT.

conclusion

The path was long and fascinating. Now it's time to do some review of what I did:

first review top 10 Player and Play Type : seem top player has about same Volume but in Play Type Clearly show some type more sell than other type.
- first result : seem people more focus on play type than player name
in second part I expand my data and instead top 10 . i choose top 10% based on Volume: in this part also seem results are repeated Players still has same distribution
- second result: seems to some Play Type Warranty Sale Volume because Top Play Types has much higher minimum Sale Volume
in last part i review all data to “is result from past dataset are repeated?” and see yes repeated
- most of big sale are limited to thee play type
- while player has limired set of Play Type , Play type fill from various player than each one has little share of it
- Top Bradly has most sale volume and most repeated in best seller of week while has 3 NFT ( biggest has 8)
- Reception hast most Sale Volume in types and is most repeated type of each week and has highest number of NFT
last but not least as Data Show massive increase in sale after After a successful game for players