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Leaderboarded Relative Weighted Ranking Algorithm A prim er fo r le aderboar d playe rs

Leaderboarded uses an advanced ranking formula when calculating your

leaderboard score.

 This advanced formula brings benefits by reducing the bias of simpler

leaderboards. It makes the overall leaderboard fairer by discounting player

scores which are outliers. It also means the winners of the leaderboard are those

who are a “rounded player”, doing well in many areas, rather than over-focusingon just one way to score to points.

Players are ranked according to how well they do against peers in each points

category (“metric”). Then this is weighted with other metrics to create a total

score out of 100.

One way to think of it is as there being a “pie” of 100 possible points. Each metric

is worth a number of points. Being top in that metric gives you all the possible

points, while being second gives you 95% of them.

So if a metric is worth 20 points and there are 10 people on the leaderboard, the

top ranked player will get all 20 points, the second will get 18 points, the third 16

and so on.

 The leaderboard manager decides how points are allocated for each metric - the

‘weighting’. If one metric has 50% of the weighting then that will account for

50% of the points. Managers may choose to keep this secret from the players to

reduce ‘gaming’ of the system.

 Worked ExampleIn a cooking competition, for example, we might seek to measure three metrics:

-  Cleanliness - how clean the kitchen is at the end

-  Cost - how cost effective were the ingredients were used

-   Taste - how good the food tastes

 The manager would allocate weighting according to the agreed priorities. Most

would agree that how good the food tastes is of most important so in our

example above, the manager allocates weighting as follows:

-  Cleanliness – 15-  Cost – 30

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-   Taste – 55-   Total = 100 

Now, let us imagine we have two chefs, each competing for the award:

Let’s say the first chef beats the second chef at Cleanliness and Cost but loses on

 Taste as follows.

Chef Cleanliness Cost Taste

Chef 1 1st 1st 2nd 

Chef 2 2nd 2nd 1st 

Each player gets a percentage of the number of points depending on their rank

for that specific variable.

With two players, the top player gets 100% of the points, the second playerscores 50% of the points. The table below shows how this changes when you

have more players.

Player / Number

of players

2 players 3 players 100 players

 Top player 100% 100% 100%Second player 50% 66% 99% Third player n/a 33% 98%

Last player n/a n/a 1%

So, when we apply this to our Chefs we get an outcome on the leaderboard as

follows:

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Chef 2 beats player 1 because his combined composite index (77.5) is higher

than Chef 2’s (72.5).

 What does this mean for you as a player?1.  Your score is never zero – you get something for just taking part.

2.  Even if another player appears to be far and away at the top, in one metric,

 you can still reach them by beating them in other metrics. Especially if the

other metrics are weighted more heavily.

3.  It’s better to do reasonably well in all metrics rather than focus on just

one.

4.  It’s better to focus on doing the right things, rather than trying to figure

out how to beat the system and game the leaderboard.