Today marks the 10th anniversary of the launching of the Hot Hand in Sports website. The page has gone through a few different looks, as shown below. From 2002 to 2006, I used just a very basic FrontPage HTML format for the site, which was hosted on my college's server at Texas Tech University.
In 2006, I transferred the site to Blogger/Blogspot, where it has remained ever since. However, I've changed the template somewhat during the past six years. Here's how the page looked in its early years on Blogger.
Finally, 2011 and 2012 have brought major new developments. The book Hot Hand has now been published (see upper-right column). Also, I have started issuing brief updates on streaky performances right as they occur, via Twitter (http:/www.twitter.com/alanreifman), reserving the blog for more elaborate analyses.
As long as athletes keep going on streaks and I enjoy writing about them, this blog and associated activities will keep on going!
Analyzing Sports Streakiness with Texas Tech Professor Alan Reifman........................................................................(See twitter.com/alanreifman for more frequent postings)...................................................................................
Saturday, January 28, 2012
Monday, January 23, 2012
New York Giants Bring Unusual Stat into Super Bowl
The New York Giants are the first team with a four-game losing streak during the season to make it to the Super Bowl, since the 2002 Oakland Raiders. No other team in American football's Super Bowl era (beginning with the 1966 season) has lost four straight and made it all the way to the title game in the same season.
I find it very surprising that a team with four straight losses during a 16-game season could make the Super Bowl, for two reasons. First, because the season is so short, it doesn't give teams much time to recover and compile a playoff-worthy record (although it is possible to make the playoffs with a weak record). Second, if a team loses four straight, one has to wonder how good that team really is. A lot of Super Bowl teams didn't even lose four games the entire season!
In fairness to New York, the four straight losses were to three eventual playoff teams and a fourth team (Philadelphia), which was good in spurts. Plus, the losses were mostly close. The Giants lost on November 13 to San Francisco (27-20), Nov. 20 to Philadelphia (17-10), Nov. 28 to New Orleans (49-24), and December 4 to Green Bay (38-35). In the playoffs, however, the Giants avenged their losses to the Packers and 49ers. (Click here for the Giants' 2011-12 game-by-game log.)
Interestingly, the Giants played their upcoming Super Bowl opponent, the New England Patriots, during the season. New York won that game, 24-20 on Nov. 6, and immediately went into its four-game skid!
Looking at this all-time chart of Super Bowl teams (with won/loss records during the season and links to game-by-game logs), we see that a few teams during the past decade nearly lost four straight the season they made the Super Bowl. The 2005 Pittsburgh Steelers and 2003 Carolina Panthers each lost three straight, whereas the 2008 Arizona Cardinals lost four out of five.
In 1978, the NFL adopted a 16-game schedule to replace the previous 14-game docket. Also, prior to 1978 there was only one wild-card playoff team per conference, making it extremely unlikely that a team with four consecutive losses could even make the playoffs.
I find it very surprising that a team with four straight losses during a 16-game season could make the Super Bowl, for two reasons. First, because the season is so short, it doesn't give teams much time to recover and compile a playoff-worthy record (although it is possible to make the playoffs with a weak record). Second, if a team loses four straight, one has to wonder how good that team really is. A lot of Super Bowl teams didn't even lose four games the entire season!
In fairness to New York, the four straight losses were to three eventual playoff teams and a fourth team (Philadelphia), which was good in spurts. Plus, the losses were mostly close. The Giants lost on November 13 to San Francisco (27-20), Nov. 20 to Philadelphia (17-10), Nov. 28 to New Orleans (49-24), and December 4 to Green Bay (38-35). In the playoffs, however, the Giants avenged their losses to the Packers and 49ers. (Click here for the Giants' 2011-12 game-by-game log.)
Interestingly, the Giants played their upcoming Super Bowl opponent, the New England Patriots, during the season. New York won that game, 24-20 on Nov. 6, and immediately went into its four-game skid!
Looking at this all-time chart of Super Bowl teams (with won/loss records during the season and links to game-by-game logs), we see that a few teams during the past decade nearly lost four straight the season they made the Super Bowl. The 2005 Pittsburgh Steelers and 2003 Carolina Panthers each lost three straight, whereas the 2008 Arizona Cardinals lost four out of five.
In 1978, the NFL adopted a 16-game schedule to replace the previous 14-game docket. Also, prior to 1978 there was only one wild-card playoff team per conference, making it extremely unlikely that a team with four consecutive losses could even make the playoffs.
Saturday, January 14, 2012
College Hoops Hotness and Coldness
It's only late afternoon, and we've already seen instances of pronounced hot and cold shooting in men's college basketball.
Florida State's Deividas Dulkys hit 8-of-10 on three-pointers in Seminoles' 90-57 shocker over No. 3 North Carolina. Dulkys, a senior guard, has made almost exactly one-third of his shots from behind the arc during his junior (.333) and senior (.321) years, making this afternoon's 8-of-10 performance extremely unusual. How unusual?
Using what is known as a binomial probability calculator, we can answer the question of how likely a long-term .333 three-point shooter is to make 8 (or more) out of 10 attempts from downtown. The answer is .003 or roughly 3-in-1,000.
Jaron Nash is a Texas Tech sophomore forward who plays about 10 minutes per game (Nash stats). He doesn't get to the free-throw line much, but when he has, he hasn't shot well. In fact, before making a pair from the stripe late in the Red Raiders' 67-54 loss to Texas A&M, Nash had missed 11 straight free throws.
It's not like Nash got flustered and missed several free throws in one game while in a funk. Rather, he compiled the streak gradually over five games.
Florida State's Deividas Dulkys hit 8-of-10 on three-pointers in Seminoles' 90-57 shocker over No. 3 North Carolina. Dulkys, a senior guard, has made almost exactly one-third of his shots from behind the arc during his junior (.333) and senior (.321) years, making this afternoon's 8-of-10 performance extremely unusual. How unusual?
Using what is known as a binomial probability calculator, we can answer the question of how likely a long-term .333 three-point shooter is to make 8 (or more) out of 10 attempts from downtown. The answer is .003 or roughly 3-in-1,000.
Jaron Nash is a Texas Tech sophomore forward who plays about 10 minutes per game (Nash stats). He doesn't get to the free-throw line much, but when he has, he hasn't shot well. In fact, before making a pair from the stripe late in the Red Raiders' 67-54 loss to Texas A&M, Nash had missed 11 straight free throws.
It's not like Nash got flustered and missed several free throws in one game while in a funk. Rather, he compiled the streak gradually over five games.
- Against Oral Roberts, he missed his last free-throw of the game, after two previous makes (box score, play-by-play).
- He then went 0-for-4 against Cal State Bakersfield (box score).
- And 0-for-3 vs. Southeast Louisiana (box score).
- He had no free-throw attempts in Texas Tech's next two outings, against Oklahoma State and Baylor.
- He missed his only attempt against Kansas (box score).
- Finally, this afternoon vs. Texas A&M, he missed his first two before making a pair (box score, play-by-play).
Thursday, January 12, 2012
Hot Hand in Volleyball?
Science News has just published an article on research by German and Austrian investigators purporting to document a hot hand in volleyball spiking, and the reporter was nice enough to contact me for comment. A hot hand in this context would mean that a player who has successfully put away a few spikes in a row (known as "kills") would have a higher likelihood of a kill on his or her next spike than the player's long-term kill percentage would suggest. A cold hand would represent the opposite, that a player whose last few spike attempts have resulted in errors (e.g., ball hit out of bounds) would have higher than usual odds of an error on the next attempt than his/her long-term percentages would suggest.
Within the constraints of the data set to which the authors had access (partial game-sequence data from top players in a German men's professional league), the analyses were conducted with full rigor and in a manner consistent with previous hot hand research. However, as I elaborate below, I feel there was at least one major limitation in the available data.
One type of analysis done by the authors used the runs test. This statistical technique requires the researcher first to list the sequence of events, in this case, a given player's order of kills (K) and errors (E). A "run" is an uninterrupted sequence of the same outcome, either all K's or all E's. The following hypothetical sequence, with few runs, would indicate streaky performance (i.e., clustering of K's and of E's):
KKKKEEEKKKKK (3 runs)
Another hypothetical sequence (with the same number of total attempts), this time with many runs, would indicate less (or absent) streakiness:
KKEKEEKKKKEK (7 runs)
According to the Science News piece:
An analysis of playoff data from the 1999/2000 season for 26 top scorers in Germany’s first-division volleyball league identified 12 players as having had scoring runs that could not be chalked up to chance. Hot-handed players’ shots contained fewer sequences of consecutive scores than expected by chance, the result of a small number of especially long scoring runs.
As volleyball fans know, however, there is a third category of outcome for spike attempts, namely the ball is dug up (or otherwise kept in play) by the defense, and the rally continues. As I told the reporter, I definitely think those hit attempts should have been included in the analyses, but they apparently were unavailable in the data set the authors received. Hitting errors were very rare in the data, so balls kept in play may have been a better measure than errors of unsuccessful spike attempts.
(Cross-posted with VolleyMetrics.)
Within the constraints of the data set to which the authors had access (partial game-sequence data from top players in a German men's professional league), the analyses were conducted with full rigor and in a manner consistent with previous hot hand research. However, as I elaborate below, I feel there was at least one major limitation in the available data.
One type of analysis done by the authors used the runs test. This statistical technique requires the researcher first to list the sequence of events, in this case, a given player's order of kills (K) and errors (E). A "run" is an uninterrupted sequence of the same outcome, either all K's or all E's. The following hypothetical sequence, with few runs, would indicate streaky performance (i.e., clustering of K's and of E's):
KKKKEEEKKKKK (3 runs)
Another hypothetical sequence (with the same number of total attempts), this time with many runs, would indicate less (or absent) streakiness:
KKEKEEKKKKEK (7 runs)
According to the Science News piece:
An analysis of playoff data from the 1999/2000 season for 26 top scorers in Germany’s first-division volleyball league identified 12 players as having had scoring runs that could not be chalked up to chance. Hot-handed players’ shots contained fewer sequences of consecutive scores than expected by chance, the result of a small number of especially long scoring runs.
As volleyball fans know, however, there is a third category of outcome for spike attempts, namely the ball is dug up (or otherwise kept in play) by the defense, and the rally continues. As I told the reporter, I definitely think those hit attempts should have been included in the analyses, but they apparently were unavailable in the data set the authors received. Hitting errors were very rare in the data, so balls kept in play may have been a better measure than errors of unsuccessful spike attempts.
(Cross-posted with VolleyMetrics.)
Thursday, January 05, 2012
Doug McDermott's Three-Point Shooting Highs and Lows
I heard on ESPN Radio the other morning that Creighton University's Doug McMermott has been hitting at a .580 clip on three-point attempts so far this season. The sophomore's high success rate behind the arc is surprising for a couple of reasons. Typically, guards are the main outside shooters and McDermott is a 6-7 forward. Also, his percentage from long-distance a season ago was much lower (though still good) at .405 (47-for-116)
To see if there were any interesting trends this season, I plotted his game-by-game three-point shooting percentages (below), based on his seasonal log. The size of each data point corresponds to his number of three-point attempts in a given game (see graph's legend) and opponents are listed along the horizontal axis. You may click on the graph to enlarge it.
First off, McDermott doesn't attempt that many threes, just 50 (of which he's made 29) in 14 games. In his most recent outing, against Drake, McDermott didn't try any treys, despite playing 32 minutes. Twice, against Northwestern and Wichita State, he didn't miss from behind the arc, but he was only 2-for-2 in each of these games.
His steadiest stretch of hot three-point shooting occurred in Games 3-8. In each of these contests (except vs. San Diego State), McDermott shot within a range of .667-.750. Accounting for number of attempts, his most impressive game was against St. Joseph's (5-of-7, .714).
Otherwise, he's had a lot of ups and downs, but not any prolonged stretches of poor three-point shooting.
Creighton and McDermott are next in action on Saturday at Bradley.
To see if there were any interesting trends this season, I plotted his game-by-game three-point shooting percentages (below), based on his seasonal log. The size of each data point corresponds to his number of three-point attempts in a given game (see graph's legend) and opponents are listed along the horizontal axis. You may click on the graph to enlarge it.
First off, McDermott doesn't attempt that many threes, just 50 (of which he's made 29) in 14 games. In his most recent outing, against Drake, McDermott didn't try any treys, despite playing 32 minutes. Twice, against Northwestern and Wichita State, he didn't miss from behind the arc, but he was only 2-for-2 in each of these games.
His steadiest stretch of hot three-point shooting occurred in Games 3-8. In each of these contests (except vs. San Diego State), McDermott shot within a range of .667-.750. Accounting for number of attempts, his most impressive game was against St. Joseph's (5-of-7, .714).
Otherwise, he's had a lot of ups and downs, but not any prolonged stretches of poor three-point shooting.
Creighton and McDermott are next in action on Saturday at Bradley.
Monday, January 02, 2012
Follow My Hot-Hand Tweets on Twitter
Happy New Year! Something new for 2012 is that I've started a Twitter feed and will use it from now on to "tweet" brief statements about streaky sports performances. For more in-depth analyses, I will still be writing here on the blog.
Follow me at: http://twitter.com/#!/alanreifman.
Follow me at: http://twitter.com/#!/alanreifman.
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