From Wikipedia:
Pythagorean expectation is a formula invented by Bill James to estimate how many games a baseball team “should” have won based on the number of runs they scored and allowed. Comparing a team’s actual and Pythagorean winning percentage can be used to evaluate how lucky (or alternatively how “clutch”) that team was (by examining the variation between the two winning percentages). The term is derived from the formula’s resemblance to the Pythagorean theorem.
The basic formula is:
where Win% is the winning percentage generated by the formula. The expected number of wins would be the expected winning percentage multiplied by the number of games played.
Applied to hockey, the formula looks like this:
EAST | |||||||||
ATLANTIC | GP | W | L | OTL | PTS | GF | GA | EXP WIN % | PROJ PTS |
New Jersey | 32 | 23 | 8 | 1 | 47 | 93 | 69 | 0.645 | 111 |
Pittsburgh | 35 | 24 | 10 | 1 | 49 | 114 | 90 | 0.616 | 107 |
Philadelphia | 33 | 15 | 16 | 2 | 32 | 93 | 97 | 0.479 | 79 |
NY Rangers | 34 | 15 | 16 | 3 | 33 | 94 | 100 | 0.469 | 78 |
NY Islanders | 35 | 13 | 15 | 7 | 33 | 88 | 113 | 0.378 | 68 |
NORTHEAST | GP | W | L | OTL | PTS | GF | GA | EXP WIN % | PROJ PTS |
Buffalo | 32 | 20 | 10 | 2 | 42 | 85 | 70 | 0.596 | 102 |
Boston | 32 | 16 | 10 | 6 | 38 | 84 | 80 | 0.524 | 90 |
Ottawa | 33 | 17 | 12 | 4 | 38 | 94 | 96 | 0.489 | 86 |
Montreal | 36 | 15 | 18 | 3 | 33 | 90 | 104 | 0.428 | 72 |
Toronto | 34 | 12 | 15 | 7 | 31 | 100 | 122 | 0.402 | 70 |
SOUTHEAST | GP | W | L | OTL | PTS | GF | GA | EXP WIN % | PROJ PTS |
Washington | 34 | 21 | 7 | 6 | 48 | 124 | 95 | 0.630 | 108 |
Atlanta | 33 | 18 | 12 | 3 | 39 | 108 | 99 | 0.543 | 92 |
Florida | 35 | 14 | 14 | 7 | 35 | 99 | 115 | 0.426 | 75 |
Tampa Bay | 34 | 11 | 14 | 9 | 31 | 81 | 104 | 0.378 | 67 |
Carolina | 33 | 8 | 19 | 6 | 22 | 82 | 120 | 0.318 | 53 |
WEST | |||||||||
CENTRAL | GP | W | L | OTL | PTS | GF | GA | EXP WIN % | PROJ PTS |
Chicago | 32 | 21 | 8 | 3 | 45 | 95 | 67 | 0.668 | 112 |
Nashville | 35 | 21 | 11 | 3 | 45 | 101 | 98 | 0.515 | 93 |
Detroit | 34 | 18 | 11 | 5 | 41 | 95 | 89 | 0.533 | 92 |
St. Louis | 32 | 14 | 13 | 5 | 33 | 78 | 88 | 0.440 | 77 |
Columbus | 35 | 14 | 14 | 7 | 35 | 101 | 121 | 0.411 | 74 |
NORTHWEST | GP | W | L | OTL | PTS | GF | GA | EXP WIN % | PROJ PTS |
Calgary | 34 | 20 | 10 | 4 | 44 | 98 | 82 | 0.588 | 100 |
Vancouver | 34 | 19 | 15 | 0 | 38 | 106 | 88 | 0.592 | 95 |
Colorado | 36 | 19 | 11 | 6 | 44 | 104 | 105 | 0.495 | 90 |
Minnesota | 34 | 17 | 14 | 3 | 37 | 89 | 95 | 0.467 | 82 |
Edmonton | 34 | 15 | 15 | 4 | 34 | 103 | 109 | 0.472 | 79 |
PACIFIC | GP | W | L | OTL | PTS | GF | GA | EXP WIN % | PROJ PTS |
San Jose | 35 | 20 | 8 | 7 | 47 | 115 | 93 | 0.605 | 104 |
Phoenix | 35 | 21 | 12 | 2 | 44 | 89 | 79 | 0.559 | 97 |
Los Angeles | 37 | 22 | 12 | 3 | 47 | 111 | 108 | 0.514 | 93 |
Dallas | 34 | 14 | 9 | 11 | 39 | 101 | 105 | 0.481 | 85 |
Anaheim | 34 | 13 | 14 | 7 | 33 | 95 | 109 | 0.432 | 74 |
*Note actual points should be higher because the formula does not factor in overtime losses.
Any surprises? Comments? There are certainly flaws with a) the theorem itself (that has been refined numerous times), and b) its application to hockey (doesn’t factor in the overtime loss). But I am not a statistician and this was done for fun not to make any worthwhile predictions. Please feel free to criticize/correct my work. Also, the formula only applies to a team’s remaining games.
Dedicated to Michael Remis
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