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Sports Club Stats calculates each team’s odds of making the playoffs, how each upcoming game will impact those odds, and how well they have to finish out to have a shot. It knows the season schedule and scores for past games. Each night it grabs any new scores from the internet and simulates the rest of the season by randomly picking scores for each remaining game. The weighted method takes the opponents record and home field advantage into account when randomly picking scores, so the better team is more likely to win. The 50/50 method gives each opponent an equal chance of winning each game. Both methods let an appropriate percent of games end in a tie or go into overtime in leagues where that matters. When it’s finished "playing" all the remaining games it applies the league’s tie breaking rules to see where everyone finished. It repeats this random playing out of the season million of times (try it yourself), keeping track of how many "seasons" each team finishes where. Finally it updates this page with the new results for you to read with your morning coffee.

To help flush out each team’s highest and lowest possible seeds, I force them to win or lose all their remaining games for a small percentage of the simulation runs. All the change columns are since the end of the last day that had games. The biggest movers up and down are in bold. The teams are ordered by their odds of making the playoffs (more interesting than their record) except on the league wide page of leagues that have conferences. Those are sorted by winning percentage. Click on a team to see its big games and what if scenarios.

P G W-L-OL GD: Current points, games in hand, wins, losses, overtime losses, and goals delta (points for - points against). A team gets 2 points for a win, 1 for an overtime loss, and 0 for a loss.

Chance will make playoffs: This is what we care about. Out of the millions of simulated seasons they made the playoffs this percentage of the time. Sums the chances at positions 1-8 (3 division winners and 5 wildcards).

Chance team will finish the regular season at position: The numbers are rounded percentages, so a 0 means a very small number that rounded to 0. You can hover your mouse above a number to see the "full" percentage and what the team did to get there. If there is a blank space for a position the team never finished there after any of the millions of simulated seasons, although it still might be mathematically possible.

Avg: Average finishing position at the end of the regular season, more interesting once you have locked a playoff spot and are fighting for a better seed. It is the arithmetic mean, so if they come in 1st half the time and 5th the other half the average would be 3 (even though they never actually finish 3rd). The sign of the average change is flipped so negative is bad.

RPI: Ratings Percentage Index rank among all team in the league. Listed here for kicks, it does factor into the simulation. Hover over the rank to see the RPI value and how many spots the rank changed.

Strength: (weighted method only) Pythagorean or Pythagenpat expected winning percentage, uses the team’s goals (runs, points, whatever they are called) scored and goals allowed to model how they "should" be playing. On average this is a more accurate predictor of a team’s true strength then their actual winning percentage. Green is good because you can expect them to do better down the road, (again, on average). Although you could view it as bad because they probably have lost more than their fair share of close games. Hover over to see the difference between the actual winning percentage and to see the weight. Weight is the actual number the weighted method uses for team strength. It is just the pythag value regressed towards the mean, a fancy way of saying nudged back towards .500, a lot early in the season and less and less as the season progresses.