Most
halftime shows include comments from former players and coaches about how teams
must “pick up the intensity” or “step up” in the second half. In basketball
games, analysts talk about strategies like “getting the ball inside” or “taking
better care of the basketball.”
While
such input from former players and coaches is valuable, it is far from complete
analysis. You need to get into the numbers for that to happen. Sports analytics provides powerful insight and
doesn’t need to involve anything complex. The concept of regression to the mean
reveals far more about what to expect in the second half, and only requires
comparing a few key stats.
Let’s
say one team shoots 8-for-10 from three-point range to grab a 10-point lead while
the other clanks 1-for-9. If both teams entered the contest shooting 40 percent
on the season, it is almost certain that both teams regress to the mean – the 40
percent mark – in the second half. Defense impacts these stats, but randomness
(or luck) is a huge factor in small samples. As more shots get taken, teams
should move toward their season percentage and cause the score to tighten up.
Free
throw percentages are another great stat to examine at halftime. Unlike
three-pointers, they aren’t defended. So randomness plays an even
greater role.
I
believe broadcasts will soon have a statistical expert offering such insight –
alongside coaches and/or former players – on halftime shows. But until that
happens, we can all do it ourselves.
Wednesday, December 5, 2012
Thursday, November 29, 2012
Four Ways to Build Value for Arbitration
The arbitration
season is a crazy time of year for baseball agents and The Sports Resource. So
before it gets into full swing, here are strategies for making your briefs a
winner.
Building a brief starts with telling a compelling story in the player profile section. That makes matching the player against key comparables easier and more convincing.
The approaches below work for both the player profile and comparables sections, and will make powerful points that complement a brief's core elements.
History, All-time Greats, and Rarities. While their achievements may not find their way onto SportsCenter, players record historic achievements throughout the regular season. For example, Antonio Bastardo’s 14.0 strikeouts per nine innings rate this season has been matched by just two lefthanders in Major League history: Billy Wagner and Aroldis Chapman. We’re not saying Bastardo is as good as Wagner (obviously), but linking his name to an all-time great is huge. And such feats carry value even when they don’t involve common statistics.
Marginal Value adds Major Value. Players on teams that narrowly reach the postseason – such as the Orioles and Cardinals this year – help their teams generate $25-to-$50 million of additional revenue. That’s according to research by Vince Gennaro, a consultant for Major League teams and author of the book “Diamond Dollars”. Reaching the playoffs also impacts club revenues for up to five seasons. Demonstrate how your player made that two or three-game difference for his club (and his key comparables didn’t), and you score a huge plus.
Ballpark Figures. Park factors can be a tremendous weapon in arbitration. Hitters in Safeco Field, or any of the five California stadiums, are ideal for park adjustments. The same goes for pitchers in Coors Field, U.S. Cellular Field and Fenway Park. Our last newsletter addressed this topic for free agency. The concept works differently in arbitration – because the criteria does not allow for projections – but it’s a great tactic for evaluating past performance.
Advanced Metrics. Clubs have used win expectancies and leverage index against relievers in recent hearings. So why not do the same? Even if they don’t help your case, it pays to prepare information for rebuttal. WAR is a powerful tool as well, but works better at some positions than others. Although their explanations consume some presentation time, advanced metrics complement core numbers extremely well.
Building a brief starts with telling a compelling story in the player profile section. That makes matching the player against key comparables easier and more convincing.
The approaches below work for both the player profile and comparables sections, and will make powerful points that complement a brief's core elements.
History, All-time Greats, and Rarities. While their achievements may not find their way onto SportsCenter, players record historic achievements throughout the regular season. For example, Antonio Bastardo’s 14.0 strikeouts per nine innings rate this season has been matched by just two lefthanders in Major League history: Billy Wagner and Aroldis Chapman. We’re not saying Bastardo is as good as Wagner (obviously), but linking his name to an all-time great is huge. And such feats carry value even when they don’t involve common statistics.
Marginal Value adds Major Value. Players on teams that narrowly reach the postseason – such as the Orioles and Cardinals this year – help their teams generate $25-to-$50 million of additional revenue. That’s according to research by Vince Gennaro, a consultant for Major League teams and author of the book “Diamond Dollars”. Reaching the playoffs also impacts club revenues for up to five seasons. Demonstrate how your player made that two or three-game difference for his club (and his key comparables didn’t), and you score a huge plus.
Ballpark Figures. Park factors can be a tremendous weapon in arbitration. Hitters in Safeco Field, or any of the five California stadiums, are ideal for park adjustments. The same goes for pitchers in Coors Field, U.S. Cellular Field and Fenway Park. Our last newsletter addressed this topic for free agency. The concept works differently in arbitration – because the criteria does not allow for projections – but it’s a great tactic for evaluating past performance.
Advanced Metrics. Clubs have used win expectancies and leverage index against relievers in recent hearings. So why not do the same? Even if they don’t help your case, it pays to prepare information for rebuttal. WAR is a powerful tool as well, but works better at some positions than others. Although their explanations consume some presentation time, advanced metrics complement core numbers extremely well.
Thursday, November 15, 2012
Aircraft Carriers, Adjustments and Arbitration
Last Sunday, Syracuse faced San Diego State aboard the USS Midway in San Diego Harbor. The wind made shots beyond a few feet an adventure. One baseline jumper by Syracuse forward C.J. Fair seemed to blow two feet off course and wound up an air ball.
The shooting percentages were low for both sides, but especially dismal for the Aztecs. They made just one three-pointer in 18 attempts and shot 27 percent overall. At the foul line, they sank 42.4 percent. Broadcasters Dick Enberg and Steve Kerr commented frequently about the conditions, at one time saying the players probably wish these stats wouldn’t count in their season numbers.
While the statistics need to count, we can make adjustments for the context. Other teams have played on ships. Using those averages to adjust actual statistics provide a better indication of how well the teams and players performed. Of course, it’s only one game and won’t impact final season numbers very much.
Baseball players on teams with extreme venues like Safeco Field and Coors Field aren’t so lucky. They play 81 games in settings that have a huge impact on their statistics. While the Aztecs and Orange escaped the aircraft carrier after one game, Mariners hitters and Rockies pitchers have no such opportunity. The altitude never changes in Denver, and neither does its effect on statistics.
Fortunately, in baseball arbitration and free agency, we can make adjustments for context, but it’s not always simple. Just as the outside shooters struggled more than big men aboard the ship, ballparks affect different players in different ways. Left-handed power hitters in Minute Maid Park make a great example. Since the stadium debuted in 2000, there have been 28 20-home run seasons by Astros’ right-handed batters, just one by a lefty hitter.
Extreme environments call attention to the need for adjustments. However, we need them for less obvious conditions as well, not just for basketball games aboard aircraft carriers.
The shooting percentages were low for both sides, but especially dismal for the Aztecs. They made just one three-pointer in 18 attempts and shot 27 percent overall. At the foul line, they sank 42.4 percent. Broadcasters Dick Enberg and Steve Kerr commented frequently about the conditions, at one time saying the players probably wish these stats wouldn’t count in their season numbers.
While the statistics need to count, we can make adjustments for the context. Other teams have played on ships. Using those averages to adjust actual statistics provide a better indication of how well the teams and players performed. Of course, it’s only one game and won’t impact final season numbers very much.
Baseball players on teams with extreme venues like Safeco Field and Coors Field aren’t so lucky. They play 81 games in settings that have a huge impact on their statistics. While the Aztecs and Orange escaped the aircraft carrier after one game, Mariners hitters and Rockies pitchers have no such opportunity. The altitude never changes in Denver, and neither does its effect on statistics.
Fortunately, in baseball arbitration and free agency, we can make adjustments for context, but it’s not always simple. Just as the outside shooters struggled more than big men aboard the ship, ballparks affect different players in different ways. Left-handed power hitters in Minute Maid Park make a great example. Since the stadium debuted in 2000, there have been 28 20-home run seasons by Astros’ right-handed batters, just one by a lefty hitter.
Extreme environments call attention to the need for adjustments. However, we need them for less obvious conditions as well, not just for basketball games aboard aircraft carriers.
Wednesday, July 18, 2012
Do-It-Yourself Three-Point Shooters
With five seconds left on
the shot clock and all their teammates covered, guards have to create. Some perform much better at it than others.
Creating and then converting
a three-pointer is basketball’s version of a grand slam. A 24-second violation nets
nothing – and a wild shot attempt isn’t much better. So it’s a three-point
swing if a player can nail a three off the dribble. Since few players shoot high percentages in these situations, the players who excel have tremendous value.
After evaluating all three-point
shooters for volume, accuracy and the ability to create their shot without an
assist, Spurs guard Gary Neal stood out.
He hit 41.9 percent overall from three-point range last season, even though only
54.2 percent of his made threes were assisted. On average, 84.2 of NBA three-pointers were assisted in 2011-12.
Most top three-point
marksmen have a very high percentage of their threes assisted. That’s no
problem of course, it’s their job to spot up and drain threes. But it makes players who can convert threes off
the dribble even more valuable, especially for teams that don’t get many
open three-point looks from their set offense.
In addition to Neal, other
players who shine in this area include Kyrie
Irving, Kyle Lowry, Jose Juan Barea and Lou Williams.
Wednesday, June 27, 2012
The Common Factor
Besides playing for the
Oklahoma City Thunder, Kevin Durant, Russell Westbrook and James Harden don’t
seem to have much in common. And that was the case when the Sonics/Thunder selected
them in three consecutive drafts, except for one key factor.
All three players were exceptionally young for
their class. At 18.74 years old on
draft night, Durant was the youngest freshmen
(and player) taken in the past five drafts combined. One year later, they
landed the youngest sophomore from
these five draft classes. Westbrook, at 19.62 years old, was actually younger
than many freshmen in the 2008 draft.
Then they took Harden in 2009. Only one other sophomore besides Westbrook was
younger than Harden at 19.83.
As a result, the Thunder
nabbed three players with far more college playing experience than prospects
their same age. The Sports Resource Newsletter covered this topic last year. Westbrook,
for example, had played 75 games for UCLA. Most of the draft selections close
to his age had fewer than half that many.
Obviously, it wasn’t just
about their age relative to their class. Durant and Harden also put up
outstanding statistics, but so had many others in their draft class. Their numbers were made far more impressive
by the fact that they were over one year younger (in some cases) than
players that shared the same college class.
Maybe other teams valued
this common factor, but went another direction on draft night. Perhaps it’s
just a coincidence that Oklahoma City exploited this edge three straight years. Whatever happened, the
Thunder may soon start the next NBA dynasty because of those selections.
Friday, February 24, 2012
Time to Move On
If a point guard had these averages after his name (3.6 PPG, 1.9 APG), most people wouldn’t think much of him. But if you change them to 21.3 and 11.3, that’s a different story. These stats are actually for the same player during the same timeframe. They show Jeremy Lin’s production in his first nine games this season before he saw regular action and exploded on the scene. The second set of numbers reveal Lin’s numbers per 36 minutes of game action. He began his strong performance before Linsanity, although few noticed.
Once some ideas become entrenched in sports, it’s difficult to change. I have no idea why basketball started using per game statistics, but it’s time to stop. NBA players – even those that we call regulars – vary widely in minutes played per game. We already saw how useless they are for bench players. Per game stats cause misconceptions about performance, and hamper the ability to identify breakout players. We should evaluate players per minute or, better yet, per possession. But the latter concept is too great a leap for the mainstream.
In the meantime, here’s an alternative to points per game. True Scoring Rate (TSR) is simply a player’s points scored per 36 minutes. Why 36 minutes? That’s the approximate average for a top NBA starter. This way we find out who scores at the greatest rate, something points per game has never done.
Points per game shortchanges players like Kyrie Irving, who had played just 31 minutes per game (through February 23). Irving ranked 23rd in points per game (18.1), but his 21.1 TSR placed 15th, ahead of point guards Tony Parker (20.3) and Chris Paul (19.1). Both surpassed him in points per game, largely because they saw more minutes.
True Scoring Rate is not really new, just a way of simplifying per minute rates. It’s easy to understand and calculate. Most importantly, it adjusts for the large discrepancies in playing time.
The next Jeremy Lin might be sitting on an NBA bench right now, and TSR can help find him.
Once some ideas become entrenched in sports, it’s difficult to change. I have no idea why basketball started using per game statistics, but it’s time to stop. NBA players – even those that we call regulars – vary widely in minutes played per game. We already saw how useless they are for bench players. Per game stats cause misconceptions about performance, and hamper the ability to identify breakout players. We should evaluate players per minute or, better yet, per possession. But the latter concept is too great a leap for the mainstream.
In the meantime, here’s an alternative to points per game. True Scoring Rate (TSR) is simply a player’s points scored per 36 minutes. Why 36 minutes? That’s the approximate average for a top NBA starter. This way we find out who scores at the greatest rate, something points per game has never done.
Points per game shortchanges players like Kyrie Irving, who had played just 31 minutes per game (through February 23). Irving ranked 23rd in points per game (18.1), but his 21.1 TSR placed 15th, ahead of point guards Tony Parker (20.3) and Chris Paul (19.1). Both surpassed him in points per game, largely because they saw more minutes.
True Scoring Rate is not really new, just a way of simplifying per minute rates. It’s easy to understand and calculate. Most importantly, it adjusts for the large discrepancies in playing time.
The next Jeremy Lin might be sitting on an NBA bench right now, and TSR can help find him.
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