The 2013 Buccaneers Really Know How to Blow It

This post at Reddit noted that the 2013 Buccaneers have blown 4 games in which they had at least a 0.95 Win Probability (WP). This is the most blown games for any team since at least 1999, and there are still 8 games left to blow this season.

Most readers are familiar with the Comeback Factor (CBF) stat. It measures the unlikelihood of the win at the lowpoint of the game for the eventual winning team. For example, if a team comes back to win from a 0.05 WP, that would be a CBF of 20 (1/.05 = 20). A team that comes back from a 0.01 WP earns a CBF of 100.

On the flip side of that equation is the Blown Game Factor (BGF), a stat which measures how badly a team blows a game. If a team has a 0.95 WP and goes on to lose, its BGF is a 20. It's really no different than Comeback Factor--it's just measured from a different perspective.

TB already has 4 games with a BGF of 20 or higher, meaning at one point they had at least a 0.95 WP. The table below lists all the teams in the database (since 1999) with 2 or more games with a BGF of at least 20. That's not the only way to measure total heartbreak, so I included some other numbers.

The 3rd column lists each team's total BGF for their losses. The 4th column lists each team's total peak Win Probability in each of their losses. These are alternative ways of measuring a team's total level of heartbreak in a season. The final column lists the number of losses for the season. All numbers are for the regular season only.

Team>20 BGFTot. BGFTot. Peak WPL
2013 TB4205.96.38
2003 HST3259.26.111
2001 CAR3234.38.315
2012 DET3204.310.812
2011 DAL3126.48.68
2011 MIA2248.68.410
2008 SD2219.49.98
1999 NO2171.95.413
2008 KC2166.05.314
2002 SD2164.94.28
2012 TB2152.35.49
2012 CAR2152.08.19
2006 CIN2151.14.88
2009 CIN2142.76.16
2011 OAK2140.39.38
2002 DEN2137.56.07
2005 KC2136.37.86
2004 SEA2131.15.27
2012 GB2127.24.65
2002 ATL2103.05.57
2009 NE2102.76.76
2002 SF2101.55.96
2013 HST295.13.76
2003 OAK283.94.512
2010 CIN276.94.512
1999 IND269.22.53
2002 CLV266.03.27
2012 NE252.67.04

It's interesting that not all teams on the list are losing teams. There's even a 13-win team and a 12-win team on the list. I suppose that makes sense, good teams are probably more likely to suffer more blown games simply because they hold more commanding leads.

It's also interesting that the 7-9 2012 Buccaneers are on the list.

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13 Responses to “The 2013 Buccaneers Really Know How to Blow It”

  1. Daniel Tilkin says:

    How are you calculating Total Peak WP? For 2013 TB, If they had 4 games where they had a .95 WP, wouldn't those 4 games contribute at least 3.8?

  2. Nick Bradley says:

    a friend of mine pointed out that since the bucs are so much worse than Seattle and New Orleans, the win probability wasn't really that high to begin with.

    i.e. WP models assume evenly-matched teams

  3. Steve says:

    How is the Bucs' total win probability in losses only 1.7?

  4. Brian Burke says:

    Seems like the Total WP column is in error. I'll have to fix that.

  5. Brian Burke says:

    Fixed now. It was the old 'sum(x) when it should have been sum(1-x) error'.

  6. Anonymous says:

    I think the WP does not assume evenly matched teams given that good teams are more likely to build 95% WP over bad teams than the other way around. So in that sample of big leads, more often than not you'll find a better team leading.

  7. John Black says:

    Gunna need a full time corrections department soon; no wonder I caint make heads and tails of all the articles cause the numbers is wrong. more proof that football has no need for spreadsheets, football needs big personalities and more folks like me who played it the right way on and off the field and almost played pro ball in a overseas country.

  8. Memphis MOJO says:

    Do you blame the coach? The players have to execute, but in the end I think it comes down to coaching.

  9. Anonymous says:

    Might want to rephrase the title.

  10. Brian Burke says:

    I'm sure coaching is part of it. Schiano seems to be one the of the exceptions and doesn't seem to have the right idea about a lot of things. That's just my opinion based on what we all get from ESPN. Players are the biggest part of the equation though.

    Maybe I'm getting soft, but I can't imagine just how heartbreaking it must be to have so many games slip though your fingers--for the players and the coaching staff. This isn't a diversion like it is to fans. It's their livelihood.

  11. Anonymous says:

    As a long time lions fan, I am not surprised they lead at least one category, but am surprised that are only on the list once.

  12. Paul Thomas says:

    Ironic to see the 2002 49ers on this list given that they basically flipped the script in the playoffs (that was the ridiculous game where they fell behind the Giants 38-14, came back to take the lead with under a minute left, then almost gave up a winning drive only to win because the refs failed to call offsetting penalties on the last play).

  13. David Ohsie says:

    I think the WP does not assume evenly matched teams given that good teams are more likely to build 95% WP over bad teams than the other way around. So in that sample of big leads, more often than not you'll find a better team leading.

    But, if this is true, this means that true WP for a poor team who is ahead is probably even "more lower" than it's calculated WP that it would be if WP assumed evenly matched teams. If part of the WP for the team far ahead is based on the strength of the team, and good teams are more likely to get far ahead in WP, then the component of WP which is due purely to the score, down and distance, field position and time remaining is even lower.

    Does "far ahead/far behind" WP actually have such a bias, or has that been factored out somehow?

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