As most NBA fans have probably heard by now, the Cleveland Cavaliers' Kevin Love scored 34 points in the first quarter last night in leading his team to a 137-125 victory over visiting Portland. It was a record for most points in the first quarter, but not for any quarter.
Golden State's Klay Thompson once scored 37 points in the third quarter of a game. Although Love's single-quarter point total last night (34) approached Thompson's record, Thompson's is truly one of a kind, in my view, for another reason. Whereas Love missed a few shots last night in the first quarter, going 3-of-4 on two-point attempts, 8-of-10 on shots from behind the arc, and 4-of-4 on free-throws, Thompson didn't miss a single shot of any kind in his big quarter.
Love's 8-of-10 performance on first-quarter threes is nothing to sneeze at, however, and it is the aspect of his record night that I'd like to focus on. Love is a career .363 three-point shooter in a little over eight years in the NBA and his season-specific three-point shooting-percentages have been very consistent in recent years (.376 in 2013-14; .367 in 2014-15; .360 in 2015-16). Thus far in the current season, before last night's game, Love was hitting on .316 (18-of-57) of his treys.
Using Love's career .363 baseline success-rate, we can ask what is the probability that he would make 8 (or more) three-pointers in a 10-attempt sequence. Using a binomial calculator, the answer is .006 or 6-in-1,000.
In one sense, Love's scoring outburst might be considered more impressive than Thompson's. Compared to Thompson's .417 career NBA three-point shooting-percentage (and .444 for the season coming into his record-setting game), Love's career and season-to-date baseline success-rates were several percentage-points lower. It is, of course, harder for someone with a lower baseline success-rate to enter a stretch of hitting at a torrid pace.
Love scored only 6 more points after the first quarter last night, finishing with 40. Cleveland led comfortably for most of the game, entering the fourth quarter up 112-92, so was able to rest its starters.
Thursday, November 24, 2016
Thursday, August 04, 2016
Michael Phelps Looks to Extend Olympic-Gold Streaks
With the opening ceremonies for the 2016 Rio de Janeiro Olympics getting underway tomorrow, swimming enthusiasts are anticipating whether -- and to what degree -- Michael Phelps will be able to extend his career-total medal haul. He currently owns 22 Olympic medals, 18 gold, 2 silver, and 2 bronze.
In terms of Olympic streaks, Phelps has ongoing runs of three straight golds in the 100-meter butterfly and the 200-meter individual medley. He will attempt to extend each of these streaks to four in a row. Before Phelps won the two aforementioned events in 2012, no male swimmer had won the same event at more than two straight Olympiad. He will swim a third individual event in Rio, namely the 200 butterfly, in which he narrowly missed a third straight gold in 2012.
The following chart (which you can click to enlarge) shows Phelps's medal performances not just at the past three Olympiad, but also at the World Championships and Pan-Pacific Championships. The chart includes only the three individual events he will swim in Rio. Phelps did not compete in 2013 due to his brief retirement, plus USA Swimming kept him off the team for the 2015 Worlds for his drunk-driving offenses.
Sports Illustrated's pre-Olympic issue picks Phelps to win one gold -- in the 100-meter butterfly, just ahead of Hungary's Laszlo Cseh. Within 2016, Cseh (50.86) has actually swum this race faster than Phelps (51.00), but we don't know that all circumstances (e.g., amount of rest; pool conditions) were comparable. (You can look up the world rankings in any event, based on fastest times, at the international federation's website.) SI tabs Cseh over Phelps in the 200 fly, and Japan's Kosuke Hagino over Phelps in the 200 IM.
In terms of Olympic streaks, Phelps has ongoing runs of three straight golds in the 100-meter butterfly and the 200-meter individual medley. He will attempt to extend each of these streaks to four in a row. Before Phelps won the two aforementioned events in 2012, no male swimmer had won the same event at more than two straight Olympiad. He will swim a third individual event in Rio, namely the 200 butterfly, in which he narrowly missed a third straight gold in 2012.
The following chart (which you can click to enlarge) shows Phelps's medal performances not just at the past three Olympiad, but also at the World Championships and Pan-Pacific Championships. The chart includes only the three individual events he will swim in Rio. Phelps did not compete in 2013 due to his brief retirement, plus USA Swimming kept him off the team for the 2015 Worlds for his drunk-driving offenses.
Sports Illustrated's pre-Olympic issue picks Phelps to win one gold -- in the 100-meter butterfly, just ahead of Hungary's Laszlo Cseh. Within 2016, Cseh (50.86) has actually swum this race faster than Phelps (51.00), but we don't know that all circumstances (e.g., amount of rest; pool conditions) were comparable. (You can look up the world rankings in any event, based on fastest times, at the international federation's website.) SI tabs Cseh over Phelps in the 200 fly, and Japan's Kosuke Hagino over Phelps in the 200 IM.
Friday, July 15, 2016
What’s Up (Or In This Case, Down) With the Cubs?
Perhaps it’s the Cubs’ historical futility – anyone can have an off-century, paraphrasing former manager Tom Trebelhorn. Or perhaps it’s the reputations of current team executive Theo Epstein and manager Joe Maddon. Whatever the reason, the team’s fast start this season inspired no shortage of superlatives from the media.
On May 15, with the Cubs sitting at 27-9, CBS Sports.com splashed around words such as “historic,” “remarkable,” and “incredible” in describing the team’s start.
On June 7, with the Cubs having advanced their record to 40-16 the night before, FiveThirtyEight made the stunning comparison of Maddon’s bunch to the 1927 Yankees.
Now, as the season resumes Friday after the All-Star Break, the Northsiders are 53-35. The team’s record has been 26-26 since the CBS Sports article and 13-19 since FiveThirtyEight’s piece.
The Cubs’ slide began on June 20, the opening day of a three-game Wrigley Field series with St. Louis, which the Cardinals swept. Chicago has now lost five of its last six series (plus a one-game make-up game with Atlanta). Using the Cubs’ game-by-game log, I plotted the results of all of their series so far this season, in chronological order. Opponents are shown on the horizontal axis and the outcome of each series is shown on the vertical axis (sweeping a three-game series would be +3, getting swept four would be -4, etc.; see legend below the graph). You may click on the graphics to enlarge them.
[Legend: On the vertical axis, +4, +3, -3, and -4 represent sweeps of 4- or 3-game series; +2 or -2 can result from sweeps of 2-game series or winning or losing 3 in a 4-game series; 0 = split of 2- or 4-game series. The number of games in a series is shown in parentheses after the opponent’s name on the horizontal axis. Asterisk (*) indicates series with 1-game rain postponement until later in season.]
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Presumably, the Cubs have declined in one or more of the following areas: hitting, pitching, and defense. Hitting does not seem to be the major problem. The team’s two leaders in OPS (On-base Plus Slugging percentages), Anthony Rizzo and Kris Bryant, have maintained a torrid pace. In fact, Rizzo’s two best monthly OPS figures have come in June (1.211) and July (1.178). The same is true for Bryant (June, 1.058; July, 1.222). Addison Russell and Jason Heyward have been steady, if unspectacular, with monthly OPS values in the .700-.800 range of late. That’s not to say that nobody has slumped. Dexter Fowler’s OPS in April, May, and June fell respectively from 1.087 to .879 to .605, and Ben Zobrist has fallen to an OPS of .707 in June and .640 in July, after he had attained a 1.136 in May. Still, there is no universal collapse in hitting among the Cubs.
To evaluate starting pitchers’ individual outings, I use the “game score” statistic developed by Bill James. The scoring system starts a pitcher out with 50 points, then adds points for good pitcher outcomes (e.g., 1 point for each out, plus an additional point for a strikeout) and subtracts points for bad outcomes (-2 for each hit allowed, -4 for each earned-run yielded). Game scores for each and every start by a given pitcher are included among ESPN.com’s pitching statistics. I have plotted game scores for each of the Cubs’ five regular starters, shown in chronological order.
Although the data are noisy, the general trend is that Cubs starters – four of whom are age 30 and older – began declining around their 15th starts. Before that, most outings were in the 50-80 range (highlighted in gray), meaning that pitchers made a net gain in points above the 50 with which they automatically started.
John Lackey recorded a 23 in his 15th start (a 9-6 Cubs loss at Miami), Jason Hammel struggled badly with a 5 in his 16th start (a 10-2 loss at the Mets), and Jon Lester also registered a 5; this came in his 17th start, another blow-out loss (14-3) at Citi Field. Jake Arrieta, though not hitting the low points of some of his teammates, has thrown clearly subpar games in his last three starts (game scores of 38, 38, and 35). Kyle Hendricks has been the even-keel starter, never deviating from a range of 41-80.
According to another FiveThirtyEight article, as of June 19 (right before the Cubs’ spate of losing series), Chicago pitchers appeared to be benefiting from two developments: their “contact-management skills” or “tendency to allow batted balls that do less damage;” and excellent defensive play from the fielders. Getting into the physics of batted balls, “Cubs pitchers [had] depressed exit velocity by 0.4 miles per hour and launch angle by almost 2 degrees, relative to average.” In terms of fielding, free-agent acquisition Heyward has saved 35 runs with his defense in 2015 and 2016 combined, according to one estimate, which is one of the best performances for an outfielder during this time.
One would guess Cub pitchers lately were allowing balls to leave opposing bats with greater exit velocity and launch angle, although I do not have updated statistics on those parameters. The Cubs need some rest, according to Maddon. That’s as good a recommendation as any, especially for the starting pitchers.
On May 15, with the Cubs sitting at 27-9, CBS Sports.com splashed around words such as “historic,” “remarkable,” and “incredible” in describing the team’s start.
On June 7, with the Cubs having advanced their record to 40-16 the night before, FiveThirtyEight made the stunning comparison of Maddon’s bunch to the 1927 Yankees.
Now, as the season resumes Friday after the All-Star Break, the Northsiders are 53-35. The team’s record has been 26-26 since the CBS Sports article and 13-19 since FiveThirtyEight’s piece.
The Cubs’ slide began on June 20, the opening day of a three-game Wrigley Field series with St. Louis, which the Cardinals swept. Chicago has now lost five of its last six series (plus a one-game make-up game with Atlanta). Using the Cubs’ game-by-game log, I plotted the results of all of their series so far this season, in chronological order. Opponents are shown on the horizontal axis and the outcome of each series is shown on the vertical axis (sweeping a three-game series would be +3, getting swept four would be -4, etc.; see legend below the graph). You may click on the graphics to enlarge them.
Presumably, the Cubs have declined in one or more of the following areas: hitting, pitching, and defense. Hitting does not seem to be the major problem. The team’s two leaders in OPS (On-base Plus Slugging percentages), Anthony Rizzo and Kris Bryant, have maintained a torrid pace. In fact, Rizzo’s two best monthly OPS figures have come in June (1.211) and July (1.178). The same is true for Bryant (June, 1.058; July, 1.222). Addison Russell and Jason Heyward have been steady, if unspectacular, with monthly OPS values in the .700-.800 range of late. That’s not to say that nobody has slumped. Dexter Fowler’s OPS in April, May, and June fell respectively from 1.087 to .879 to .605, and Ben Zobrist has fallen to an OPS of .707 in June and .640 in July, after he had attained a 1.136 in May. Still, there is no universal collapse in hitting among the Cubs.
To evaluate starting pitchers’ individual outings, I use the “game score” statistic developed by Bill James. The scoring system starts a pitcher out with 50 points, then adds points for good pitcher outcomes (e.g., 1 point for each out, plus an additional point for a strikeout) and subtracts points for bad outcomes (-2 for each hit allowed, -4 for each earned-run yielded). Game scores for each and every start by a given pitcher are included among ESPN.com’s pitching statistics. I have plotted game scores for each of the Cubs’ five regular starters, shown in chronological order.
Although the data are noisy, the general trend is that Cubs starters – four of whom are age 30 and older – began declining around their 15th starts. Before that, most outings were in the 50-80 range (highlighted in gray), meaning that pitchers made a net gain in points above the 50 with which they automatically started.
John Lackey recorded a 23 in his 15th start (a 9-6 Cubs loss at Miami), Jason Hammel struggled badly with a 5 in his 16th start (a 10-2 loss at the Mets), and Jon Lester also registered a 5; this came in his 17th start, another blow-out loss (14-3) at Citi Field. Jake Arrieta, though not hitting the low points of some of his teammates, has thrown clearly subpar games in his last three starts (game scores of 38, 38, and 35). Kyle Hendricks has been the even-keel starter, never deviating from a range of 41-80.
According to another FiveThirtyEight article, as of June 19 (right before the Cubs’ spate of losing series), Chicago pitchers appeared to be benefiting from two developments: their “contact-management skills” or “tendency to allow batted balls that do less damage;” and excellent defensive play from the fielders. Getting into the physics of batted balls, “Cubs pitchers [had] depressed exit velocity by 0.4 miles per hour and launch angle by almost 2 degrees, relative to average.” In terms of fielding, free-agent acquisition Heyward has saved 35 runs with his defense in 2015 and 2016 combined, according to one estimate, which is one of the best performances for an outfielder during this time.
One would guess Cub pitchers lately were allowing balls to leave opposing bats with greater exit velocity and launch angle, although I do not have updated statistics on those parameters. The Cubs need some rest, according to Maddon. That’s as good a recommendation as any, especially for the starting pitchers.
Saturday, July 09, 2016
Serena Williams Just Keeps Winning Grand Slam Titles
Serena Williams continues to defy the age curve, winning the Wimbledon women's singles title earlier today. At 34 years old (born September 26, 1981), Williams is now the oldest player, woman or man, to win a Wimbledon singles championship, overtaking Martina Navratilova (33 years, 8 months when she captured her final title in 1990). Accordingly, I have updated the age chart of women's tennis greats that I have displayed on this site from time to time.
Sunday, April 17, 2016
Obscure Baseball-Card Find: Walt Dropo, Co-Record Holder for Hits in Consecutive At-Bats (12)
As I wrote about in my book Hot Hand, maintaining some types of streaks is more pressure-packed than maintaining others. In baseball, a streak of getting at least one hit per game, while not an easy task, still allows a batter to make one or more outs per game and still potentially preserve the streak. A streak of getting hits in numerous consecutive at-bats, on the other hand, has no margin for error. You make an out and the streak is over.
As I further noted in the book (page 5), the Major League record for most consecutive at-bats getting a hit each time is 12, co-held by Mike "Pinky" Higgins (1938) and Walt Dropo (1952). Think of that: 12 straight hits without making an out! (Because walks and certain other outcomes do not count as official at-bats, players could have walked during their streaks.)
Shortly after my book came out, Trent McCotter, a leading authority on baseball records and old-time hitting streaks, e-mailed me that, "You can also add Johnny Kling, 1902, to that list [with Higgins and Dropo]. I discovered it a few years back." Trent informed me that the famous Elias Sports Bureau accepted this change, and indeed, recent versions of the Elias record book list Kling with Higgins and Dropo.
I saved Trent's message for the next time I wrote about hit streaks in consecutive at-bats, not exactly knowing when that might be. A few months ago, the topic returned, and I have waited until the start of the new baseball season to write about it.
While browsing in a used record/CD/DVD store, which also had a small section on baseball cards, I came upon a Walt Dropo card, which I promptly purchased. (You may click on the following photo to enlarge it.)
Though Dropo's big league career lasted from 1949-1961, the card was issued in 1990, as part of the "Swell" Baseball Greats retrospective series.
The most recent threat to Kling, Higgins, and Dropo's mark that I could find was a stretch in 2002 by the Yankees' Bernie Williams, during which he produced hits in 11 consecutive at-bats.
As I further noted in the book (page 5), the Major League record for most consecutive at-bats getting a hit each time is 12, co-held by Mike "Pinky" Higgins (1938) and Walt Dropo (1952). Think of that: 12 straight hits without making an out! (Because walks and certain other outcomes do not count as official at-bats, players could have walked during their streaks.)
Shortly after my book came out, Trent McCotter, a leading authority on baseball records and old-time hitting streaks, e-mailed me that, "You can also add Johnny Kling, 1902, to that list [with Higgins and Dropo]. I discovered it a few years back." Trent informed me that the famous Elias Sports Bureau accepted this change, and indeed, recent versions of the Elias record book list Kling with Higgins and Dropo.
I saved Trent's message for the next time I wrote about hit streaks in consecutive at-bats, not exactly knowing when that might be. A few months ago, the topic returned, and I have waited until the start of the new baseball season to write about it.
While browsing in a used record/CD/DVD store, which also had a small section on baseball cards, I came upon a Walt Dropo card, which I promptly purchased. (You may click on the following photo to enlarge it.)
Though Dropo's big league career lasted from 1949-1961, the card was issued in 1990, as part of the "Swell" Baseball Greats retrospective series.
The most recent threat to Kling, Higgins, and Dropo's mark that I could find was a stretch in 2002 by the Yankees' Bernie Williams, during which he produced hits in 11 consecutive at-bats.
Saturday, April 09, 2016
Here's the Story, of a Man Named... Story
As of a few days ago, I had never heard of Trevor Story, a 23-year-old rookie shortstop for the Colorado Rockies. With so much else going on in the sports world such as March Madness, the Masters, and the Warriors' quest for 73 wins, I just wasn't following the start of the MLB season that closely.
Something has happened in the young baseball season, however, to make a streaks aficionado such as myself take notice. Namely, Story hit two home runs last Monday in his first-ever major-league game and he's maintained a streak of homering at least once in all four of the Rockies' games! I've created the following chart (which you can click to enlarge) to document all of Story's plate-appearances so far this season. (Each game appears on a new line. The numbers after ground-outs [G] and fly-outs [F] are standard fielding position numbers and other abbreviations are explained at the bottom of the chart.)
As this article from last night's game documents, "Story became the first major leaguer to homer in each of his first four games."
Another article notes that, even throwing non-rookies into the mix, Story is just the "[f]ifth player to homer in four straight games to start a season, joining Baltimore Orioles' Chris Davis (2013), Texas' Nelson Cruz (2011), St. Louis' Mark McGwire (1998) and San Francisco's Willie Mays (1971)." Pretty good company!
As the above chart reveals, Story has entered the big leagues as a free-swinger. He has no walks in his first 19 plate appearances. In addition to his six home runs, he has four strikeouts (three swinging), seven fly-outs (which includes line-drives), one ground-out, and one single.
The Rockies host the Padres again tonight, with the Colorado rookie trying to homer in his fifth straight game. We'll continue to follow the story...
UPDATE -- END OF STORY: No home run for Story on Saturday night, ending his streak.
Something has happened in the young baseball season, however, to make a streaks aficionado such as myself take notice. Namely, Story hit two home runs last Monday in his first-ever major-league game and he's maintained a streak of homering at least once in all four of the Rockies' games! I've created the following chart (which you can click to enlarge) to document all of Story's plate-appearances so far this season. (Each game appears on a new line. The numbers after ground-outs [G] and fly-outs [F] are standard fielding position numbers and other abbreviations are explained at the bottom of the chart.)
As this article from last night's game documents, "Story became the first major leaguer to homer in each of his first four games."
Another article notes that, even throwing non-rookies into the mix, Story is just the "[f]ifth player to homer in four straight games to start a season, joining Baltimore Orioles' Chris Davis (2013), Texas' Nelson Cruz (2011), St. Louis' Mark McGwire (1998) and San Francisco's Willie Mays (1971)." Pretty good company!
As the above chart reveals, Story has entered the big leagues as a free-swinger. He has no walks in his first 19 plate appearances. In addition to his six home runs, he has four strikeouts (three swinging), seven fly-outs (which includes line-drives), one ground-out, and one single.
The Rockies host the Padres again tonight, with the Colorado rookie trying to homer in his fifth straight game. We'll continue to follow the story...
UPDATE -- END OF STORY: No home run for Story on Saturday night, ending his streak.
Friday, April 01, 2016
Has Buddy Hield Regained His Yield?
With the men's NCAA basketball Final Four getting underway tomorrow, the player getting the most attention is Oklahoma's Buddy Hield. His Sooner squad will face Villanova, with North Carolina and Syracuse meeting in the other semifinal.
Hield has been a rare entity this season -- an actual streaky shooter -- going through sizable stretches of hot shooting, as well as of more mediocre marksmanship. In each of OU's final five non-conference games (from December 12-25), Hield shot .500 or better on threes, with at least five attempts in each contest (game-by-game log).
The first graph below shows Hield's game-by-game success from behind the three-point arc beginning with the start of Big 12 conference play (you can click on the graphics to enlarge them). After a rough outing at Iowa State in the opener (2-of-9), the senior guard went on a tear of eight straight games shooting .500 or better from long distance (the sizes of the basketball icons are proportional to the number of shots taken in each game, and the opponents are indicated by two-letter abbreviations, which is all I could fit in).* At roughly the midpoint of conference play, Hield's hot shooting was bringing him a lot of media attention.
Hield cooled down during the latter part of Big 12 play, however, shooting in the .300s on treys in seven of OU's last 10 regular-season games (and never higher than .462 during this span). The Big 12 tournament did go well either for Hield, as he shot .333 (2-of-6) in a win over Iowa State and .167 (1-of-6) in a loss to West Virginia.
Once NCAA-tournament action got underway, Hield began to reverse his regular-season slump. In OU's first game, against Cal State Bakersfield (abbreviated as "BK" on the horizontal axis), Hield hit 50% of his three-pointers (3-of-6), his first time at the break-even point in his last 13 games. A .429 (6-of-14) outing against VCU was solid, if not spectacular. Then, after regressing to .286 (2-of-7) vs. Texas A&M, Hield broke out with a .615 (8-of-13) performance from downtown in the Sooners' regional-final rout of Oregon.
Hield's March Madness upturn has involved only a few games, however, so whether or not he's really "back" remains open to debate. Using the statistical technique of local (or "loess") regression to discern larger trends, the results are inconclusive. If the analysis is specified to be highly sensitive or reactive to changes occurring over small numbers of games (left graph, below), there does appear to be a modest NCAA-tournament rise for Hield. However, if the analysis is programmed to less sensitivity and reactivity, and greater smoothness (right graph), no recent rise is detectable
So whether Hield has regained his yield is unclear. Until tomorrow...
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*For fans of the Big 12, the abbreviations should be interpretable, albeit odd (e.g., "TC" instead of TCU, "KS" for Kansas State). In the midst of conference play, Oklahoma took on LSU ("LS") in the Big 12/SEC Challenge. In the NCAA tournament, BK = Cal State Bakersfield, VC = Virginia Commonwealth, AM = Texas A&M, and OR = Oregon.
Hield has been a rare entity this season -- an actual streaky shooter -- going through sizable stretches of hot shooting, as well as of more mediocre marksmanship. In each of OU's final five non-conference games (from December 12-25), Hield shot .500 or better on threes, with at least five attempts in each contest (game-by-game log).
The first graph below shows Hield's game-by-game success from behind the three-point arc beginning with the start of Big 12 conference play (you can click on the graphics to enlarge them). After a rough outing at Iowa State in the opener (2-of-9), the senior guard went on a tear of eight straight games shooting .500 or better from long distance (the sizes of the basketball icons are proportional to the number of shots taken in each game, and the opponents are indicated by two-letter abbreviations, which is all I could fit in).* At roughly the midpoint of conference play, Hield's hot shooting was bringing him a lot of media attention.
Hield cooled down during the latter part of Big 12 play, however, shooting in the .300s on treys in seven of OU's last 10 regular-season games (and never higher than .462 during this span). The Big 12 tournament did go well either for Hield, as he shot .333 (2-of-6) in a win over Iowa State and .167 (1-of-6) in a loss to West Virginia.
Once NCAA-tournament action got underway, Hield began to reverse his regular-season slump. In OU's first game, against Cal State Bakersfield (abbreviated as "BK" on the horizontal axis), Hield hit 50% of his three-pointers (3-of-6), his first time at the break-even point in his last 13 games. A .429 (6-of-14) outing against VCU was solid, if not spectacular. Then, after regressing to .286 (2-of-7) vs. Texas A&M, Hield broke out with a .615 (8-of-13) performance from downtown in the Sooners' regional-final rout of Oregon.
Hield's March Madness upturn has involved only a few games, however, so whether or not he's really "back" remains open to debate. Using the statistical technique of local (or "loess") regression to discern larger trends, the results are inconclusive. If the analysis is specified to be highly sensitive or reactive to changes occurring over small numbers of games (left graph, below), there does appear to be a modest NCAA-tournament rise for Hield. However, if the analysis is programmed to less sensitivity and reactivity, and greater smoothness (right graph), no recent rise is detectable
So whether Hield has regained his yield is unclear. Until tomorrow...
---
*For fans of the Big 12, the abbreviations should be interpretable, albeit odd (e.g., "TC" instead of TCU, "KS" for Kansas State). In the midst of conference play, Oklahoma took on LSU ("LS") in the Big 12/SEC Challenge. In the NCAA tournament, BK = Cal State Bakersfield, VC = Virginia Commonwealth, AM = Texas A&M, and OR = Oregon.
Wednesday, March 16, 2016
"Explosiveness" of NCAA Men's Basketball High Seeds
With the annual NCAA men's basketball tournament getting underway, I wanted to apply a measure I originally developed for the Golden State Warriors, namely offensive "explosiveness," to the leading teams in March Madness.
Reuters news-agency blogger Chris Taylor contacted me a week ago, as part of his investigation of statistical tools that might inform March Madness predictions. I told him about explosiveness, which he included among his "Seven tips for crunching March Madness math." As Taylor characterized my explanation of why one might want to study explosiveness, "Winning teams need to be able to come back from behind, or pull away [in] close games." It remains to be seen whether explosiveness has any predictive power in this year's NCAA tourney. However, as I told Taylor somewhat flippantly, "It seems to work for Golden State!" In the remainder of this posting, I discuss explosiveness in greater detail.
The explosiveness statistic measures high-scoring bursts in short stretches of time. Instead of looking at 12-minute quarters in the NBA, I looked at 6-minute "eighths" of games. An explosive burst in NBA play is defined as scoring 18 or more points in 6 minutes (3 points per minute), which if maintained over an entire 48-minute game would yield a whopping 144 points. In the Warriors' first 25 games of the present season, in nearly one-fourth of all their 6-minute blocks did they register an explosive burst.
For the 40-minute length of college-basketball games, I looked at 5-minute blocks (one-eighth of regulation game-length) to see how often teams scored 15 or more points (i.e., 3 points per minute). Due to time constraints, I analyzed only the top eight projected teams in the field (i.e., all the No. 1 and 2 seeds in the bracket) and looked only at each of these teams' final 10 regular-season games. I did not include overtime periods, so each team had a total of 80 5-minute blocks. As shown in the following table (on which you can click to enlarge), the eight teams varied greatly in their explosiveness.
As can be seen, Xavier (Ohio), the No. 2 seed in the East region, was the most explosive team among those studied. Playing in the Big East Conference, the Musketeers recorded 13 explosive (15-point or more) bursts in their 80 5-minute blocks. Here are several examples:
Kansas (No. 1 seed in South region) and Oregon (No. 1 in the West) followed with nine explosive bursts each. Oklahoma (No. 2 in West) surprised me with only four bursts, given the excellent three-point shooting this season by the Sooners' Buddy Hield. Virginia (No. 1 in the Midwest) had no explosions in its final 10 regular-season games.
Reuters news-agency blogger Chris Taylor contacted me a week ago, as part of his investigation of statistical tools that might inform March Madness predictions. I told him about explosiveness, which he included among his "Seven tips for crunching March Madness math." As Taylor characterized my explanation of why one might want to study explosiveness, "Winning teams need to be able to come back from behind, or pull away [in] close games." It remains to be seen whether explosiveness has any predictive power in this year's NCAA tourney. However, as I told Taylor somewhat flippantly, "It seems to work for Golden State!" In the remainder of this posting, I discuss explosiveness in greater detail.
The explosiveness statistic measures high-scoring bursts in short stretches of time. Instead of looking at 12-minute quarters in the NBA, I looked at 6-minute "eighths" of games. An explosive burst in NBA play is defined as scoring 18 or more points in 6 minutes (3 points per minute), which if maintained over an entire 48-minute game would yield a whopping 144 points. In the Warriors' first 25 games of the present season, in nearly one-fourth of all their 6-minute blocks did they register an explosive burst.
For the 40-minute length of college-basketball games, I looked at 5-minute blocks (one-eighth of regulation game-length) to see how often teams scored 15 or more points (i.e., 3 points per minute). Due to time constraints, I analyzed only the top eight projected teams in the field (i.e., all the No. 1 and 2 seeds in the bracket) and looked only at each of these teams' final 10 regular-season games. I did not include overtime periods, so each team had a total of 80 5-minute blocks. As shown in the following table (on which you can click to enlarge), the eight teams varied greatly in their explosiveness.
As can be seen, Xavier (Ohio), the No. 2 seed in the East region, was the most explosive team among those studied. Playing in the Big East Conference, the Musketeers recorded 13 explosive (15-point or more) bursts in their 80 5-minute blocks. Here are several examples:
- In one game alone, vs. Creighton on March 5, the Musketeers pulled off three bursts (play-by-play sheet). Xavier went from having 44 points at halftime to 60 points with 15:00 min remaining; from 66 points with 10:00 left to 82 with 5:00 to go; and 82 with 5:00 left to 98 points at the end.
- At Seton Hall on February 28, a game in which the Musketeers trailed 45-26 at the half and ultimately lost 90-81, Xavier rallied feverishly in the second half. XU went from 43 points with 10:00 left to 58 with 5:00 left; and from 58 with 5:00 left to 81 at the final buzzer, a 23-point super-explosion (play-by-play).
Kansas (No. 1 seed in South region) and Oregon (No. 1 in the West) followed with nine explosive bursts each. Oklahoma (No. 2 in West) surprised me with only four bursts, given the excellent three-point shooting this season by the Sooners' Buddy Hield. Virginia (No. 1 in the Midwest) had no explosions in its final 10 regular-season games.
I next inquired into what other skills and styles of play might contribute to a team's explosiveness (or lack thereof). The first things that occurred to me were that an explosive team was likely to play at a fast tempo (i.e., shooting early in the shot clock, generating many possessions per game) and be good at shooting the three. Results only partially supported these hypotheses (see the grey columns in the chart above). Note, however, that whereas explosiveness was only measured in teams' final 10 regular-season games (because combing through play-by-play sheets is time-consuming), all the other statistics are based on teams' full seasons.
Xavier indeed plays at the fastest pace (74.5 possessions per game) among the No. 1 and 2 seeds, corresponding to the Musketeers' explosiveness. However, Oklahoma plays nearly as fast (73.7 possessions per game), but had low explosiveness. Virginia plays at a very slow pace (62.4 possessions per game, dead last among the 351 Division I men's teams), which seems to go a long way toward explaining the Cavaliers' lack of explosiveness. (Tempo/possession statistics are available here.)
Kansas, with nine explosive bursts, thrives on the three-pointer. Not only do the Jayhawks have one of the nation's highest shooting percentages from behind the arc; they also are attempting more treys than they have in the past. (All shooting, rebounding, and defensive statistics cited here are from the NCAA statistics webpage.)
Michigan State, with seven explosive bursts, is first in the nation in two categories: three-point shooting percentage and defensive rebounds per game. Limiting opponents to one shot and making shots yourself should contribute to explosiveness. However, the Spartans are quite low in turnovers forced per game, which presumably works against MSU being able to score quickly.
Oklahoma, which shoots well, cleans the defensive glass, and plays relatively fast, remains an enigma.
Oklahoma, which shoots well, cleans the defensive glass, and plays relatively fast, remains an enigma.
Keep an eye out for whether the eight teams seeded No. 1 or 2 make it to the Final Four. Either the explosiveness statistic will go out with a bang or be a dud.
Thursday, January 21, 2016
A Decade of UConn Women's Basketball Wins and Losses, At a Glance
Last Friday, ESPN.com ran a piece documenting the best 100-game stretches in U.S. college sports and major pro leagues such as the NBA, NFL, NHL, and MLB. At the time the article appeared, the University of Connecticut (UConn) women's basketball program had won 99 of its last 100 games (now 101 of its last 102). The legendary UCLA men's basketball program under coach John Wooden also had recorded a 99-1 stretch, from 1971-74.
The UConn women under coach Geno Auriemma have been dominant since winning the first of their 10 NCAA national times (and compiling the first of their five undefeated seasons) in 1995. I, therefore, wanted to look at the Huskies' long-term success beyond their past 100 games.
I decided to examine UConn's last 400 games, representing roughly the past decade of play. The Huskies' past 400 games span from the opening game of the 2005-06 season all the way to last night, when UConn routed Central Florida, 106-51. In these games, the Huskies are 377-23 (.942).
This record appears more compelling, in my view, when viewed in graphic form. I've thus created a diagram that shows 400 dots (one for each game), with wins depicted in blue and losses in red. The games are arranged in chronological sequence, from the first contest in the upper-left corner, advancing across each row of dots, until the 400th game in the lower-right corner. Here's the diagram:
The UConn women under coach Geno Auriemma have been dominant since winning the first of their 10 NCAA national times (and compiling the first of their five undefeated seasons) in 1995. I, therefore, wanted to look at the Huskies' long-term success beyond their past 100 games.
I decided to examine UConn's last 400 games, representing roughly the past decade of play. The Huskies' past 400 games span from the opening game of the 2005-06 season all the way to last night, when UConn routed Central Florida, 106-51. In these games, the Huskies are 377-23 (.942).
This record appears more compelling, in my view, when viewed in graphic form. I've thus created a diagram that shows 400 dots (one for each game), with wins depicted in blue and losses in red. The games are arranged in chronological sequence, from the first contest in the upper-left corner, advancing across each row of dots, until the 400th game in the lower-right corner. Here's the diagram:
Pretty blue, huh? I can't think of a way to convey the Huskies' dominance any more dramatically. The picture includes both a 90-game winning streak (the NCAA Division I record among men or women) and the current 101-1 stretch, as indicated by the side annotations. To help with interpretation of the diagram, I also created the following legend:
(You can click on the graphics to enlarge them.)
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