Manager game: How to calculate market values?

Answer 1

One thing that you could do is look at recent transfers of similar(1) players. Say all transfers within 2-5 game weeks of similar players and then take the average (or median or some other calculated value) of their sale price.

(1) You will have to define similiar in some way, i.e a defender with +-10 in defence, +-3 in passing and +-2 years of age. More factors give more precise results.

Answer 2

My suggestion: define a distance function that takes two players stats and return a distance value. Now that you have a distance between the two (that corresponds to the similarity between them) you can use the K-means algorithm to find clusters of similar players.

For each cluster you can take a number of values that can help you calculate the so called 'market price' (like the average or median value).

Here's a very simple example of how you could compute the distance function between two players:

float distance(Player player1, Player player2){
    float distance = 0.0;

    distance += abs(player1.strength - player2.strength) / strengthRange;
    distance += abs(player1.maxStrength - player2.maxStrength) / maxStrength;
    distance += abs(player1.motivation - player2.motivation) / motivationRange;
    distance += abs(player1.age - player2.age) / ageRange;

    return distance;
}

Now that you have the distance function you can apply the k-means algorithm:

1. Assign each player randomly to a cluster.

2. Now compute the centroid of each cluster. In your case the centroid coordinates will be (strength, maxStrength, motivation, age). To compute the centroid strength coordinate, for example, just average the strengths for the all players in the cluster.

3. Now assign each player to the nearest centroid. Note that in this step some players may have its cluster changed.

4. Repeat steps 2 and 3 until you have convergence or, in other words, until no player have its cluster changed in step 3.

Now that you have the clusters, you can calculate the average price fore similar players.

Answer 3

Or you could use a little Economics 101 and try to define the supply and demand for that specific player based on:

• Number of players in the league with similar capabilities (you could use the clustering method mentioned before) and number of those players "available" for transfer
• Number of teams that own the players with similar capabilities and number of teams that are in need for such players

Now with these number you could calculate the supply (available players for transfer) and demand (teams in need for those players) and use that to modify your base price (which can be your last transfer price or a base price for a player) up or down (ie more demand than supply will tend to push the prices up and vice versa)

After that it becomes negotiation game where you can take a look at some of the Game Theory literature to solve the actual exchange price.

Hope this at least give you a different look into it.