This page hosts the standings for the leaders of each award given by LIBO. The awards listed in BOLD are the 'official' formulas we'll be using; the alternate ones are the ones that may replace the 'official' ones, at some point in the future.
There are 'attendance' requirements and/or victory requirements for all plaques.
Gamer Points -- this is an absolute measure -- if you finish 1st, you get 10 points, 2nd, you get 6, 3rd you get 3, 4th you get 1 (with some variations for 3 player, 2 player and wargames). This measure does not consider how `close' a game is. In the above examples, game 1 A would get 10 pts, B: 6, C: 3 and D: 1, even though C and D are separated by 1 point. In game 2 C would get 10, B: 6, A: 3 and D: 1. This measure is absolute.
Total Gamer Rank -- this measure's how far above or below average each player's score is, overall. This is a RELATIVE score so it's based on the average score of the game. In game 1, the average score is 9, so, A is .67 above average (6 points above the 9), B is .33, C is -.44 (4 below average) and D is -.55; In game 2, the average is 8, so A is .13, B is .25, C is 1.20, D is -.75 and E is -.88 in other words, the scores reflect how close the positions are.
W-M-L Percentage -- This is a winning percentage computing the times the player Wins (W), finishes in the Middle (M), or finishes Last (L) -- it factors in the average number of players (so a record of 5-2-1 in 3-player games isn't as impressive as the same record in 10-player games). Still, just another metric measuring the ability to finish first, along with the ability to NOT finish last (but, the metric DOES consider 2nd, 3rd and 4th place finishes to all be equal, in a 5-player game).
Average Finish -- This simply measures the average "place" of finish in each game the player plays. Not a very meaningful stat, but necessary to compute the next one.
% of Players Defeated -- This juxtaposes the average finish with the average number of players per game, to determine the % of players each player has defeated. This formula ALSO measures which players, even when they cannot finish 1st, continue to play hard (i.e., it measures the total number of players you defeat in all your games, by checking your average finish with the number of players in each game).
Metrics That Measure Just Winning
Winning Percentage -- pure measurement of wins as a percentage of games played. Useful, but I think the Win % above expected is far, far more meaningful.
Wins above expected -- Since we're now tracking the number of players per game, the 'expected' win is one chance per number of players (i.e., in a 4-player game, each player has a .25 chance of winning; in a 3-player game, each player has a .33 chance). When those are added up, and compared to the number of actual wins, you get this measurement (some players have won more, some have won less than expected). This is a good stat, but it's a quantitative stat, so it favors people who play more games, and play them well the percentage stat is more valuable, since it makes everything even.
Win% above expected -- The expected winning percentage (using above computations) is compared to actual winning percentage, to determine how far above/below the expected win percentage, each player actually is. I think this is the best stat using winning % and wins above expected. It truly shows how well each player is performing AND takes into consideration the number of players at his game. For example, in game 1, each player has a 25% chance to win, while in game 2, each player has a 20% chance to win. Obviously, a winning percentage looks BETTER with more players, because it means your `odds' of winning were longer. Therefore, a 30% win percentage is good if you only play 5-player games, and poor if you only play 2-player games.
Metrics Measuring Good Overall Performance
Total 1st and 2nd Percentage -- This is the actual percentage of times the player finishes first OR second. This is also not bad, as there is some shakeup between the two lists (only 1st or 1st & 2nd), but the metric is essentially the same as above, just allowing 2nd place finishes (which only matters in 3-player+ games finishing second in a 2-player game is NOT second; it's last). Again, though, far more meaningful when compared to the expected percentage (the next metric).
1st and 2nd% above expected -- Measures the expected percentage to finish 1st or 2nd vs. the actual percentage of time the player actually finishes 1st or 2nd.
Metrics Measuring Not Finishing Last
Total last percentage -- The percentage of time the player finishes DEAD last (including 2-player games). Tries to measure the amount of time people avoid the cellar. Again, though, far more meaningful when compared to the expected percentage (the next metric).
Last% below expected -- The expected LAST percentage is compared to the actual last percentage. A positive number is better, as that is how much ABOVE expected last percentage the player actually finishes. Again, the expected last % is the same as the expected win % (since only 1 chance in x to finish 1st or last)
now, you're essentially checking to see how often the player avoids finishing last (remember, all these `total' percentages are FAR more meaningful when compared to the `expected' percentage).
The dominance metrics are very different, and therefore, need to be explained. Once again, remember that there are two tables. At Table 1, a 4-player game, the scores for players A, B, C and D are 15, 12, 5, 4. At Table 2, a 5-player game, the scores for players A, B,C, D and E are 9, 10, 18, 2, 1.
Metrics Measuring How Dominating the Winner Was
Pct Domination -- this measures the percentage of the total table's score the winning score represented (only tracked for the winning score). This means, overall for table 1, there were 36 points scored. The winning score was 15, so the `dominance pct' was .42. In game 2, there were 40 points scored, so the dominance pct was .45. (i.e., the dominance pct. suffers when the games are larger if you had a 3 player game, using only the top 3 scores in game 1, the dominance pct is .47, but even adding the last place 4, drops the overall dominance pct to .42, because there are now MORE total points scored (which diminishes the pct the winning score can represent).
Dominance average -- This measures the number of times over the average score (minus the winning score) in the game the winning score represents. So, a 2.2 means the winning score was 2.2 times the average score in the game (not including the winning score). In game 1, for instance, the average score NOT including the winning score was 7, therefore, the 15 represents a dominance of 2.14, while in game 2, the average score NOT including the winning score was 4.5, so the dominance is 3.86 looking at the range of scores (high to low), in game 1: 15, 12, 5, 4; in game 2: 18, 10, 9, 2, 1 it DOES follow that game 2 was the more dominant game. This stat measures that, effectively.
Dominance vs. Close Play -- this measures the Dominance average (listed above) multiplied by the close play average (which is the inverse). In other words, it aims to see what percentage of Dominance average remains when multiplied by the close play average (which is how close to the leader, each player scored). The closer to the leader, the greater the multiplier, which means more of the Dominance Average remains.
Other statistics are tracked, including the average amount of time it takes a player to play a game, and the average amount of time it takes that same player to get through a game, including the rules -- again, until MANY games are tracked, these statistics mean very little. A cumulative total of gaming time is also tracked.