Data was sketchy at best and definitley would not hold up even in class let alone a paper, but like I said it took three minutes.
Y is number of wins right as of 1Am eastern today (June 15) (and yes I know some teams have played more games), X1 is payroll as reported by USA Today, X2 is number of players CURRENTLY on the disabled list.
Wins= 26.85 + (4.75E-08)Payroll
Payroll is significant at the 4% level (t=2.23)
Which is expected, pay more for talent get more wins.
What is interesting is to see how well this simple simple simple model predicts wins. (spreadsheet below). The best? The Red Sox. The Worst? The Nationals. The Mets? about 2 fewer ganes than would be expected (given they have one extra game to play than many teams AND won at least 8/9ths of the Friday game, I found this a good sign). LOL.
Then using a very noisy variable for injuries (Hey I am a Met fan, I get to use injuries as an excuse):
Y is number of wins right as of 1Am eastern today (June 15) (and yes I know some teams have played more games), X1 is payroll as reported by USA Today, X2 is number of players CURRENTLY on the disabled list.
Wins= 29.93 + (4.11E-08)(Payroll) + (-0.51627)(number of players CURRENTLY on DL)
t-stat for payroll 1.93, t stat for players on DL= -1.45
So point estimates are in the expected direction but not significant using normal levels. Tjis might be because of the failure to differentiate injury severity (15 vs 60 day DL), importance of player (a mop up player has the same weight as a Jose Reyes or Carlos Delgado), or the total number of games lost (literally this is just the number of players reported by Yahoo that are CURRENTLY) on the DL.
| Team | payroll | Injuries | wins | expected wins based off of payroll | Wins - expected wins |
| Yankees | 201449189 | 5 | 36 | 36.414706 | -0.41471 |
| Mets | 148373987 | 8 | 32 | 33.896147 | -1.89615 |
| cubs | 134809000 | 3 | 30 | 33.252453 | -3.25245 |
| red sox | 121745999 | 3 | 38 | 32.632579 | 5.367421 |
| tigers | 115085145 | 3 | 34 | 32.316504 | 1.683496 |
| angels | 113709000 | 3 | 32 | 32.251202 | -0.2512 |
| phillies | 113004046 | 3 | 36 | 32.21775 | 3.78225 |
| astros | 102996414 | 4 | 29 | 31.742861 | -2.74286 |
| mariers | 98904166 | 6 | 30 | 31.548673 | -1.54867 |
| braves | 96726166 | 7 | 30 | 31.445322 | -1.44532 |
| white sox | 96068500 | 2 | 30 | 31.414114 | -1.41411 |
| Giants | 82616450 | 2 | 34 | 30.775778 | 3.224222 |
| indians | 81579166 | 7 | 29 | 30.726556 | -1.72656 |
| blue jays | 80538300 | 5 | 34 | 30.677165 | 3.322835 |
| brewers | 80182502 | 2 | 34 | 30.660281 | 3.339719 |
| cardianals | 77605109 | 4 | 34 | 30.537977 | 3.462023 |
| rockies | 75201000 | 4 | 31 | 30.423895 | 0.576105 |
| reds | 73558500 | 3 | 31 | 30.345955 | 0.654045 |
| diamondbacks | 73516666 | 6 | 27 | 30.343969 | -3.34397 |
| royals | 70519333 | 7 | 28 | 30.201738 | -2.20174 |
| rangers | 68178798 | 8 | 35 | 30.090673 | 4.909327 |
| orioles | 67101666 | 4 | 27 | 30.039561 | -3.03956 |
| twins | 65299266 | 3 | 32 | 29.954032 | 2.045968 |
| rays | 63313034 | 9 | 34 | 29.85978 | 4.14022 |
| As | 62310000 | 7 | 27 | 29.812183 | -2.81218 |
| nationals | 60328000 | 7 | 16 | 29.718132 | -13.7181 |
| pirates | 48693000 | 5 | 30 | 29.166021 | 0.833979 |
| padres | 43734200 | 7 | 28 | 28.930713 | -0.93071 |
| marlins | 36834000 | 5 | 32 | 28.60328 | 3.39672 |
Posts
1 comments:
You should try to re-run it with the payroll of the players on the injured reserve (if the data is available). I would expect that a player with a higher salary who is on the injured list has a greater negative effect on the record than a no-name player.
Post a Comment