The above two charts are very similar to the first chart, with the difference that we removed 1% of the high data (moments with a price of more than a thousand dollars) from it to make it clearer.

This chart shows well at what price most moments were sold.

Since more than 99% of moments are sold under $1000, I will only consider them to arrive at an answer that makes more sense to me.

==The reason for ignoring it is that a losing moment sale at a price of $230,000 will spoil the result.==

If the player's team won the game, does that correlate to higher sales for that individual moment vs. a play where the team lost?

We want to know a team's moments sold more if they win the game. Can we say that the moments that are related to losing the game are not sold?

It doesn't seem to be.

Based on the chart, In some teams, the total volume of selling moments in the time of loss is even higher than in the time of victory.

So I think I can say definitively that the moments have value in themselves and are not affected by the outcome of the game.

There are some jumps in the chart of the average and median moment’s prices sold for each team (related to the games they lost).

How much more valuable, on average, are touchdown rushes than a rush that did not result in a touchdown?

We want to know touchdown or non touchdown moments impacts on sales volume of each plat type. Can we say that the touchdown moments have more volume in different play type or not.

In my opinion, I have to say again, it does not seem so. but you can see Rush - touchdown has more volume than non touchdown. same for pass.

Based on the chart, In some play types, the total volume of selling moments with non touchdown even higher than with touchdown. For example in sack and interception types.

So I think there is some relation between play type and touchdown or non touchdown moment and their sales volume. but only on some positions not all.

The average sales price in pressure type - non touchdown unexpectedly is more than others. This is while its median is as expected.

Rush (play type) - touchdown and non touchdown

Following chart shows above things separately in touchdown and non touchdown:

• Daily sales volume
• Daily average sales price
• Daily median sales price
• Share of sales volume
• Share of number of sales
• Total average and median

Observation:

• Although the sales volume and the number of sales are more in Rush - touchdown, but the average and median sales price is more in Rush - non touchdown. The reason for this is that we have more sales at low prices in Rush - touchdown, which causes the average and median to decrease, but on the other hand, because the number of sales is high, the volume is also high.
• In particular, in case Rush, we must say that although the desire to buy moments of non touchdown is less than touchdown, they usually have a higher price.

What about for quarterbacks, or wide receivers?

I tried to find pattern from core.dim_allday_metadata table for winner team.

According to my observation when some words like win, victory, lead, prevail exist in moment_description column means home team is winner and also when words like loss, lose, defeat, fall, fell, beat exist in this column means away team is winner.

Based on these findings, we first divided the moments into three categories: win, loss and tie. Now, in the first chart of this dashboard, we want to see how much the sales volume of all moments is at a certain price for each of the results (win, loss and tie).

We want to know touchdown or non touchdown moments impacts on sales volume of each player position. Can we say that the touchdown moments have more volume in different player position or not.

Based on the chart, In some player position, the total volume of selling moments with non touchdown even higher than with touchdown. For example in line backer and defensive line.

But I think there is some relation. For example if you look at Quarterback you can see most of it volume is related to touchdown moments. same for Running back.

Quarterback (player position) - touchdown and non touchdown

Following chart shows above things separately in touchdown and non touchdown:

• Daily sales volume
• Daily average sales price
• Daily median sales price
• Share of sales volume
• Share of number of sales
• Total average and median

Observation:

• Although the sales volume and the number of sales are more in quarterback - touchdown, but the average and median sales price is more in quarterback - non touchdown. The reason for this is that we have more sales at low prices in quarterback - touchdown, which causes the average and median to decrease, but on the other hand, because the number of sales is high, the volume is also high.
• In particular, in case quarterback, we must say that although the desire to buy moments of non touchdown is less than touchdown, they usually have a higher price.

Observation:

• Although the sales volume and the number of sales are more in wide receiver - touchdown, but the average and median sales price is more in wide receiver - non touchdown. The reason for this is that we have more sales at low prices in wide receiver - touchdown, which causes the average and median to decrease, but on the other hand, because the number of sales is high, the volume is also high.
• In case wide receiver, we must say that although the desire to buy moments of non touchdown is less than touchdown, they usually have a higher price.
• In wide receiver, unlike quarterback there is more balance between touchdown and non touchdown moment sales volume.

Defense vs. Offense analysis, looking at how well sales of OL plays that result in the team scoring vs. defensive linemen highlights like a sack.

Observation:

• In both positions, we can say that the volume of sales was higher in the moments that were associated with the team's win.
• Totally, the sales volume in position defensive line was more than position offensive linemen.

blue shows low sales volume and orange shows high sales volume.

observation:

• It can be clearly seen that the volume of sales in moments with winning results (orange color) is more than moments with losing results
• On the other hand, it is undeniable that moments with the result of loss also sell well. For example, the most expensive moment belongs to the team's loss, which was sold at a price of more than 230 thousand dollars.
• Also, the majority of moments are related to low prices. Large circles are close to the y-axis.

In the following, you can see the histogram of total sales volume of each curtain price for won and loss and tie moments separately.

As I said i decided to ignore moments with higher price than $1000. (The last bar of both above charts are related to price higher than $1000).

Observation:

• It is true that 99% of the moments were bought at a price below 1000 dollars, but still purchases above 1000 dollars account for a high volume.
• In this marketplace, although the number of small buyers is more, the main power is in the hands of whales.
• In all price ranges, we can definitely say that the desire to buy the moments that were with the winning team is more (both in terms of volume and number).

I tried to find pattern from core.dim_allday_metadata table for touchdown detection.

According to my observation when some words like touchdown, -yard, score exist in moment_description column indicating touchdown and otherwise indicating non touchdown.

Based on these findings, we first divided the moments into two categories: touchdown and non touchdown. Now, in the next chart, you can see sales volume of each play type (separately touchdown and non touchdown).

As you probably know, quarterbacks and wide receivers are two position players in NFL.

In this part I want do same analysis as rush for them.

The first thing need to say is how to extract the players position from the core.dim_allday_metadata table. I used moment_stats_full:metadata:playerPosition to access to all player positions.

case
    when moment_stats_full:metadata:playerPosition = 'RB' then 'Running Back (RB)'
    when moment_stats_full:metadata:playerPosition = 'LB' then 'Linebacker (LB)'
    when moment_stats_full:metadata:playerPosition = 'WR' then 'Wide Receiver (WR)'
    when moment_stats_full:metadata:playerPosition = 'DB' then 'Defensive Backs (DB)'
    when moment_stats_full:metadata:playerPosition = 'QB' then 'Quarterback (QB)'
    when moment_stats_full:metadata:playerPosition = 'K' then 'Kicker (K)'
    when moment_stats_full:metadata:playerPosition = 'P' then 'Punter (P)'
    when moment_stats_full:metadata:playerPosition = 'TE' then 'Tight End (TE)'
    when moment_stats_full:metadata:playerPosition = 'OL' then 'Offensive Linemen (OL)'
    when moment_stats_full:metadata:playerPosition = 'DL' then 'Defensive Line (DL)'
    else 'Others'
  end as player_position

Wide Receiver (player position) - touchdown and non touchdown

Following chart shows above things separately in touchdown and non touchdown:

• Daily sales volume
• Daily average sales price
• Daily median sales price
• Share of sales volume
• Share of number of sales
• Total average and median

Defensive Line and Offensive Linemen are two other player positions. Here we want to see is there any relation between match result and sales volume of these two positions.

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.

link link

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.

The following topics are shown in this dashboard:

• Relation between game result and moment price (volume of sale).
• Relation between game result and moment price (number of sale).
• Histogram of sales price based total volume and total sale of each curtain price.
• Impact of game result on volume of sale and number of sale for each team.
• Impact of touchdown or non touchdown on volume of sale and number of sale for each play type.
• Impact of touchdown or non touchdown on volume of sale and number of sale for each player positions.
• Impact of game result on volume of sale and number of sale for each player positions.

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 answers foe questions in this dashboard we need extracting data from moment_description of core.dim_allday_metadata table. The data we are looking for is:

• winner team in each game.
• touchdown or non touchdown of a game.

I tried to get the data I wanted by filtering some words. Each is explained below.

Observation:

• Totally, NFL fans NFL fans most attract to moments with player position DL than moments with player position OL.
• It is true that the volume and number of sales of moments that were associated with wins are more than those that were associated with losses, but it is not the case that the moments of lost games are not sold.

Conclusion:

• The volume of sales in moments with winning results is more than moments with losing results but moments with the result of loss also sell well.
• The range price of sold moments is huge (~$0 to $230K) but the majority of moments are sold in low prices. For example 99% of moments are sold under $1000 and more than 90% are sold under $100. Although the volume of total moments sold in high price doesn’t low.
• In some teams, the total volume of selling moments in the time of loss is even higher than in the time of victory. So I think I can say definitively that the moments have value in themselves and are not affected by the outcome of the game.
• There is some relation between play type and touchdown or non touchdown moment and their sales volume. But we cant say which of them have more volume. For example, In Rush and Pass types touchdown moments sold more than non touchdown moments and in Sack and Forced fumble types non touchdown moments sold more than touchdown moments.
• Most of sales volume of quarterback and wide receiver are related to touchdown moments.
• Most of sales volume of defensive line and offensive linemen are related to win games.