Posts Tagged sports

Simple Math for Belichick’s Decision

November 22, 2009 at 9:36 pm · Filed under Random Thoughts ·Tagged , ,

All week long the sports media has refused to use simple math to analyze Bill Belichick’s decision last week to go for it on 4th down versus the Colts.  Even though the media assumes (correctly?) that the viewer is an intellectual slouch, football media machine always projects an attitude of analysis and discussion.

I did read one article that offered a proper analysis, but its tone gives the impression that it involves extreme math.  In fact, the analysis is simple conditional probability.  Using the probability from that article, this diagram shows how simple the decision is.

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Fantasy Football Pickem Strategy Results after Week 4

October 6, 2009 at 11:08 am · Filed under Random Thoughts ·Tagged , ,

After Brett Favre and the Vikings polished off the Packers last night, I found myself in 7th place out of 50 in my NFL Pickem pool.  As the following box plot shows, choosing weights using Vegas point spreads put me above the median in 3/4 weeks and in the top quartile 2/4 weeks.  In the second week, when I was below the median, I was still within the interquartile range.

weeklyperformance_boxplot

Here’s some of the data in the above box plot.

Week  |    Mean  StdDev     IQR     Min      lq  Median      uq     Max
=======================================================================
   1  |   114.5    8.22      11      95     109     115     120     133
   2  |    77.1   10.38      13      53      70      78      83     107
   3  |   104.6   15.76      14      15      99     108     113     126
   4  |    91.0    7.05       9      71      86      91      95     104

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Probability NFL Favorite Wins, Given Point Spread

September 25, 2009 at 6:33 pm · Filed under software ·Tagged , , ,

I’m continuing my investigation of what we can infer from NFL point spreads.  I wrote a little code to compute the conditional probability of the favorite team winning, given the size of the point spread.  Here are the results.

probwin_exact_spread

As you can see, the game is essentially a tossup until the point spread is at least a fieldgoal.  Once the spread exceeds a touchdown, the favorite wins nearly 4/5 times.  In the rare instance that the point spread exceeds two touchdowns, then the favorite is a lock to win.

Here’s the raw data used to generate this plot.

    spread       wins      games    probwin
============================================
      0.00         21         47      44.68
      1.00         70        138      50.72
      1.50         60        123      48.78
      2.00         87        159      54.72
      2.50        126        249      50.60
      3.00        351        587      59.80
      3.50        225        360      62.50
      4.00        101        155      65.16
      4.50         71        120      59.17
      5.00         97        133      72.93
      5.50         99        142      69.72
      6.00        108        168      64.29
      6.50        154        226      68.14
      7.00        177        238      74.37
      7.50         85        123      69.11
      8.00         75         95      78.95
      8.50         70         85      82.35
      9.00         71         91      78.02
      9.50         79         98      80.61
     10.00         66         95      69.47
     10.50         55         67      82.09
     11.00         40         48      83.33
     11.50         23         27      85.19
     12.00         20         25      80.00
     12.50         28         34      82.35
     13.00         20         24      83.33
     13.50         34         44      77.27
     14.00         26         33      78.79
     14.50         14         16      87.50
     15.00          9          9     100.00
     15.50          9          9     100.00
     16.00         14         14     100.00
     16.50          3          3     100.00
     17.00          5          5     100.00
     17.50          6          7      85.71
     18.00          2          2     100.00
     18.50          1          1     100.00
     19.00          1          1     100.00
     19.50          2          2     100.00
     20.00          1          1     100.00
     21.00          1          1     100.00
     22.00          1          1     100.00
     24.00          2          2     100.00

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Simple Backtesting of Football Pickem Strategy

September 24, 2009 at 12:07 am · Filed under software ·Tagged , , , , , ,

I was curious to see how my simple strategy for the weighted fantasy football pickem would do in previous years.  I found an archive of NFL point spreads, over under lines, and game results on goldsheet.com.  I don’t know how accurate the data are, but I wrote a little Python script to parse it.  The formatting of the data is pretty rough, so I’ve put a CSV version up on Google Docs.

Here’s a tabular summary of the results.  The key column is Percent, which shows the percentage of available points (MaxPosib) that my strategy got in each year.

    Year      Min      Max      Avg    Total   MaxPosib    Percent
==================================================================
    1993       27      103    60.94     1097       1466      74.83
    1994       46       95    64.82     1102       1500      73.47
    1995       50      114    81.18     1380       1747      78.99
    1996       51      119    82.82     1408       1748      80.55
    1997       52      114    82.24     1398       1745      80.11
    1998       56      120    86.94     1478       1734      85.24
    1999       65      115    91.06     1548       1959      79.02
    2000       62      113    90.53     1539       1959      78.56
    2001       43      117    90.29     1535       1960      78.32
    2002       62      136    95.59     1625       2088      77.83
    2003       72      134    98.53     1675       2088      80.22
    2004       67      129    95.47     1623       2088      77.73
    2005       77      127   101.47     1725       2088      82.61
    2006       65      134    89.59     1523       2091      72.84
    2007       56      136   103.41     1758       2091      84.07
------------------------------------------------------------------
 average    56.73   120.40    87.66  1494.27    1890.13      78.96
std.dev.    12.20    11.84    11.67   189.42     211.33       3.39
     min    27.00    95.00    60.94  1097.00    1466.00      72.84
     max    77.00   136.00   103.41  1758.00    2091.00      85.24

So I expect to score 79% of the total points available this year if I use my strategy of assigning weights to the favored team, ordered by point spread.

The next step is obviously to try some other strategies and see what the results are.  First I want to see how poorly a completely random strategy does.

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Automated Fantasy Pro Football Pickem Weights

September 18, 2009 at 8:27 pm · Filed under Python, software ·Tagged , , , ,

I’m participating in the Yahoo! Sports Fantasy Pro Football Pickem with some family and friends.   I don’t regularly play fantasy sports, but I was coaxed into donating money to the pool during a family trip this summer.  I blame the beer and port.

For the uninitiated, each week you must pick a winner in all 16 games, assigning a confidence weight from 1 to 16 to each game.  If your pick wins, then you are awarded points equal to the confidence weight that you assigned to that game.

Now that my money’s in, I want to make a solid showing.  My strategy is to leverage the gambling lines, mapping the point spreads and over under lines to my picks and weights.

I threw together a little Python script to parse the Yahoo odds web page.  For each game, the script averages the point spreads and over under lines.  The favored team is selected, and the picks are ranked according to point spread, with wider spreads getting a larger weight.  Ties on point spread are broken by the over under line, with a larger over under line mapping to a larger weight.

Now I’m wondering how to improve this simple algorithm.  I might break ties by giving a smaller over under a higher weight.  The reasoning would be that smaller over under lines will have less variance.  Surely there are other ways to improve the rankings.

Here’s the table that my little script prints out.

weight | winner                         loser                     spread    o/u
================================================================================
    16 | Minnesota Vikings         over Detroit Lions              -9.83  45.17
    15 | Washington Redskins       over St. Louis Rams             -9.58  37.00
    14 | Green Bay Packers         over Cincinnati Bengals         -9.08  42.00
    13 | Tennessee Titans          over Houston Texans             -6.50  40.92
    12 | Atlanta Falcons           over Carolina Panthers          -6.08  42.50
    11 | Buffalo Bills             over Tampa Bay Buccaneers       -4.42  42.00
    10 | New England Patriots      over New York Jets              -3.42  46.17
     9 | Jacksonville Jaguars      over Arizona Cardinals          -3.08  42.50
     8 | Indianapolis Colts        over Miami Dolphins             -3.08  42.17
     7 | San Diego Chargers        over Baltimore Ravens           -3.00  40.33
     6 | Denver Broncos            over Cleveland Browns           -3.00  38.83
     5 | Kansas City Chiefs        over Oakland Raiders            -3.00  38.50
     4 | Pittsburgh Steelers       over Chicago Bears              -2.92  37.50
     3 | Dallas Cowboys            over New York Giants            -2.75  45.00
     2 | San Francisco 49ers       over Seattle Seahawks           -1.10  39.58
     1 | New Orleans Saints        over Philadelphia Eagles        -1.00  46.08

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