Glossary
LP (cEDH League)
League Points (cEDH League)
Definition
League Points is the ultimate composite score used to rank players within the league. It provides the most holistic evaluation of a player's skill by integrating not only their raw success rate but also crucial contextual factors like the difficulty of their opponents, the seating advantage, and their total experience in the league. It is the definitive measure of overall league performance.
How It's Calculated
The score is calculated by multiplying five major components together, with each component carrying a specific weight in the final calculation. The resulting value is then multiplied by a large constant to generate a whole-number score suitable for ranking:
Individual Performance Component: This factor is derived from a weighted combination of the player's Average Points Per Game (ØPPG) and their Win Percentage (WP). The ØPPG is weighted more heavily than the WP, emphasizing consistency in point accumulation.
Pod Size Factor (PSF) Component: The PSF is included to adjust for the varying difficulty of winning in different-sized groups.
Seat Factor (SF) Component: The SF is included to adjust for any statistical advantage or disadvantage inherent in the player's average seating position.
Opponent Strength Component: The Opponent Performance Score (OPS) is included to reward players who maintain high performance against difficult opponents.
Experience Component: The Match Count Factor (MCF) is applied as the final multiplier to ensure that performance only receives its full weight once the player reaches the required experience threshold (15 matches).
Example
Imagine two players with identical Personal Performance Scores (PPS).
Player X has a high OPS, an average PSF, and an unfavorable SF (a slight bonus).
Player Y has a low OPS, a high PSF, and a favorable SF (a slight penalty).
The final League Points will reflect that Player X excelled against tougher opponents, while Player Y gained ground primarily through favorable pod sizes. The score balances all these elements to determine the player's final ranking.
LP (Casual League)
League Points (Casual League)
Definition
League Points Casual is a streamlined performance metric designed for rankings in a casual league environment where complex factors like opponent strength and seating bias are excluded. This score focuses solely on a player's raw success rate and the pod sizes they compete in, making it a simpler, more approachable measure of competence.
How It's Calculated
The score is calculated by multiplying three key components together, and the result is scaled up by a large constant to generate a high-precision score:
Pod Size Factor (PSF) Component: This uses the Pod Size Factor to adjust the score based on the relative difficulty of the pod sizes (3, 4, or 5 players) the player has encountered.
Individual Performance Component: This uses the player's Average Points Per Game (ØPPG), which is derived from their Match Points (5 points for a win, 1 point for a draw). This is the core measure of the player's efficacy in securing points.
Experience Component: The Match Count Factor (MCF) is applied as the final multiplier to ensure that the score only receives its full weight once the player reaches the required experience threshold (15 matches).
Example
A player with a high ØPPG but only 4 matches played will have their score severely reduced by a very low Match Count Factor. Conversely, a veteran player with a solid ØPPG will have their score adjusted only by the Pod Size Factor, leading to a high score that accurately reflects their consistent performance in the average group sizes they face.
MP
Match Points
Definition
The Match Points metric represents a player's total raw points earned in a league based purely on the match outcomes (Win, Loss, Draw). It is the foundational score used as a basis for other calculated performance metrics.
How It's Calculated
The calculation assigns a specific point value to each match result and sums them up:
- Wins: Each match won contributes 5 points.
- Draws (Ties): Each match ending in a draw contributes 1 point.
- Losses: Losses contribute 0 points to this metric.
The total is the sum of (Wins multiplied by 5) plus (Draws multiplied by 1).
Example
If a player has 10 Wins, 3 Draws, and 5 Losses: (10 Wins×5)+(3 Draws×1)=50+3=53 Match Points
ØPPG
Average Points Per Game
Definition
The Ø Points Per Game (APPG) metric measures a player's average point accrual across all matches played. It normalizes the player's total Match Points by the number of matches they've participated in, providing a standardized measure of their consistent performance and efficacy.
How It's Calculated
ØPPG is calculated by dividing the player's total Match Points (where a win is 5 points and a draw is 1 point) by the total number of matches played. If a player has played no matches, the ØPPG is 0.
Example
If a player has a total of 53 Match Points from 18 total Matches: ØPPG=53/18≈2.94
Win%
Win Percentage
Definition
The Win Percentage (Win%) is a fundamental statistic that expresses the frequency of a player's victories as a proportion of their total matches played. It provides a straightforward and essential view of a player's ability to secure a win in their games.
How It's Calculated
Win% is calculated by dividing the total number of Wins by the total number of matches played and then multiplying the result by 100 to present it as a percentage. If a player has played no matches, the Win% is 0.
Example
If a player has 10 Wins in 18 total Matches: Win%=(10/18)×100≈55.56%
PSF
Pot Size Factor
Definition
The Pod Size Factor (PSF) is a weighting multiplier that adjusts a player's performance based on the size of the pods they compete in. This factor accounts for the fact that the probability of winning varies in different sized groups.
- Participation in 4-player pods is considered the baseline (Factor ≈1.0).
- Participation in 3-player pods receives a slightly reduced factor.
- Participation in 5-player pods receives a slightly increased factor.
The PSF is thus the weighted average of the individual factors for the pod sizes in which the player has competed.
How It's Calculated
The PSF is calculated by multiplying the count of matches in each pod size with a specific Pod Size Factor (weight). The sum of these weighted matches is then divided by the total number of matches played. If a player has played no matches, the PSF is 0.
Example
A player has played more often in 5-player pods than in 3-player pods in recent matches. Since 5-player pods receive a higher factor, the resulting PSF of the player will be higher than 1.0, which slightly corrects their average performance upwards.
MCF
Match Count Factor
Definition
The Match Count Factor (MCF) is a crucial weighting multiplier applied to a player's performance scores. Its primary purpose is to dampen the scores of players with a small number of matches played, ensuring that statistics only receive their full weight once a statistically representative sample size has been achieved. As a player participates in more matches, the factor continuously increases, approaching a maximum value of 1.0.
How It's Calculated
The MCF is determined by a tiered calculation that operates based on the total number of matches played (M):
1.) Low Match Count (M ≤ 5): The factor starts very low and increases linearly for each game played, providing minimal weight to early scores.
2.) Mid Match Count (6 ≤ M ≤ 10): The factor's increase accelerates over this range, allowing the player's performance to emerge more quickly.
3.) Approach to 1.0 (11 ≤ M ≤ 14): The factor then rapidly approaches the cap of 1.0, with the rate of increase gradually diminishing (diminishing returns).
4.) Full Weight (M ≥ 15): Once the threshold of 15 matches is reached, the factor hits its full value of 1.0 and is no longer applied as a dampener.
Example
A player with only 5 matches will have a significantly dampened MCF (approximately 0.05), which heavily reduces their performance scores. A veteran player who has reached or exceeded the 15-match threshold has an MCF of 1.0, meaning their calculated scores are used at their full, undampened value.
SF
Seat Factor
Definition
The Seat Factor (SF) is a performance multiplier designed to adjust a player's score based on potential statistical biases related to seating positions. Since certain seats may be inherently more or less advantageous over time, the SF aims to neutralize this by comparing a player's average normalized seating position against the league's historical average normalized winning seat position.
If a player's average seat is statistically less favorable than the league-wide winning average, they receive an upward adjustment or bonus (SF > 1.0). If a player's average seat is statistically more favorable, they receive a downward adjustment or penalty (SF < 1.0). The factor starts at a neutral baseline of 1.0 and is adjusted based on this comparison.
How It's Calculated
The calculation involves a comparison using normalized values:
1.) Normalization: The raw seat number (e.g., Seat 1, Seat 4) is converted into a normalized value between 0 and 1. This standardizes the position relative to the size of the pod, making it comparable across 3, 4, or 5-player games.
2.) Comparison: The player's Average Normalized Seat across all their matches is compared directly to the league's established Average Normalized Winning Seat.
3.) Adjustment: The difference between these two averages determines the final SF, which is centered at 1.0 and adjusted within a small, defined range to correct for the seating bias.
If the player has played no matches or if the necessary league data is unavailable, the Seat Factor defaults to 1.0 (no adjustment).
Example
Assume the league data shows that the winning seat, on average, is slightly closer to the middle of the seating order.
A player who frequently sits in the first seat (a position statistically more advantageous than the winning average) will have an SF slightly less than 1.0 (e.g., 0.97), slightly penalizing their performance score.
A player who frequently sits in the last seat (a position statistically less advantageous than the winning average) will have an SF slightly greater than 1.0 (e.g., 1.03), slightly boosting their performance score.
PPS
Personal Performance Score
Definition
The Personal Performance Score (PPS) is a comprehensive metric designed to quantify a player's raw, individual skill and effectiveness in securing wins. It serves as a single, core measure of competence by heavily weighing their success rate and points per game. Importantly, the PPS is calculated before accounting for external factors like opponent strength or seating position bias.
How It's Calculated
The PPS is derived from a player's core success rates and then adjusted for experience:
Core Performance Base: The player's Average Points Per Game (ØPPG) and Win Percentage (Win%) are combined and heavily weighted. The ØPPG is given a higher weighting in this combination than the Win%, reflecting a prioritization of consistency in points earned.
Match Count Adjustment: This combined score is then multiplied by the Match Count Factor (MCF). This ensures that the PPS of newer players is appropriately dampened until they reach the 15-match threshold.
Example
Two players have an identical raw performance score (APPG and WP combination):
Player A has played 20 matches. Their MCF is 1.0
Player B has played 5 matches. Their MCF is low (approx. 0.05)
Player A's score is used at full value, while Player B's score is heavily penalized due to their lack of experience, reflecting the low statistical confidence in their early results.
OPS
Opponents Performance Score
Definition
The Opponent Performance Score (OPS) is a crucial strength-of-schedule metric. It quantifies the collective skill and effectiveness of a player's opponents throughout the season. A high OPS indicates that the player consistently competed against a stronger field, while a low OPS suggests an easier schedule. The metric is designed to reward players who maintain high performance while facing skilled adversaries.
How It's Calculated
The OPS is calculated as a weighted average of the Personal Performance Scores (PPS) of every player encountered:
Identify Opponents: For every match played by the player, all opponents in that match are identified.
Assign Weight: Each opponent's individual PPS is factored into the calculation. The weight applied to an opponent's PPS is determined by the number of times the player has faced that specific opponent.
Calculate Weighted Average: The sum of the opponents' PPS (weighted by the frequency of play) is divided by the total number of matches played against all unique opponents. This ensures that opponents a player faced more frequently have a greater influence on the final OPS value.
Example
A player faces three opponents over 10 matches:
Opponent A (PPS = 0.9): Faced 6 times.
Opponent B (PPS = 0.4): Faced 3 times.
Opponent C (PPS = 0.7): Faced 1 time.
The OPS would be calculated based on the total of 10 opponent encounters, with Opponent A's high PPS being the primary driver of the final score due to the high frequency of play.
