Tuesday, September 20, 2011

We Can Do That

Critics like to point out the shortcomings of sports statistics. There are areas where the numbers have minimal impact. But much of the criticism comes from misunderstanding what analytics do best.

A recent article stated that statistics do a much better job of describing the past than predicting the future. While there is some truth to that point, the predictive power depends on what you’re measuring.

The article states that no stat could have predicted that Mark Whiten would have the greatest one-game offensive performance ever. That’s true, but it’s also an impossible task. On the other hand, metrics like batting average on balls in play and home runs per fly ball can identify which hitters should break out after slow starts. Remember Dan Uggla earlier this season?

The real power of sports analytics is what they can do now and will do in the future, especially when combined with technology and/or social media. Last week, I learned about an Austin startup which built an algorithm that measures the level of excitement in sports games. Now fans know immediately if their favorite team is headed for a thrilling finish and whether to watch the game or not.

Several years ago, while struggling to learn a new computer program, a colleague offered invaluable advice: write down everything you’d like the program to do, because it probably has that capability. Turns out that it could do everything I thought of and far more.

I believe analytics and technology can solve many of the problems agents and other sports insiders face. In general, sports analytics can do much more than we realize.

What is your greatest challenge? Analytics may have a solution.

Wednesday, August 17, 2011

Simple and Informative

Save percentage is a useful statistic for closers, but not for other types of relievers. It has minimal value when evaluating setup men. Relievers that protect leads in the seventh and eighth innings rarely close games. Therefore, they have few chances to earn saves, but can still get blown saves.

That explains how an outstanding setup man like Mike Adams could have a 50 percent save percentage (two saves in four save opportunities). The stat fails to demonstrate his ability to maintain leads, which he had shown by accumulating 24 holds this season.

Save plus hold percentage evens the playing for closers and setup men, showing how well all relievers maintain leads. It is simple to calculate, yet gets little attention in the mainstream sports media. A hold is a save situation that gets preserved and passed on to the next reliever. So a hold is basically a save that does not end a game.

To calculate save plus hold percentage, combine saves and holds and then divide by saves, holds and blown saves. Among relievers with at least 15 save and hold opportunities through August 16, these pitchers led the Major Leagues.

The top 10 includes four closers, five setup men and one pitcher (Antonio Bastardo) who has filled both roles.

Adams’ 92.9 save plus hold percentage left him just short of the top 10. But he easily surpassed the Major League average of 84.9 percent this season.

Since it’s easy to explain and informative, save plus hold percentage makes a great tool for agents in both arbitration and free agency.

Monday, August 15, 2011

The Accelerators: Point Guards who Pick up the Pace

When Pooh Jeter took the court for the Sacramento Kings last season, his teammates had to be ready to run. Based on a metric comparing team pace with and without each NBA player on the court, Jeter increased the pace more than any other point guard.

The Kings had 4.1 more possessions per 48 minutes when Jeter played versus when he sat. Only three players at any position – who saw at least 750 minutes in 2010-11– surpassed him.

This stat is just one way to put words into numbers and tell a story. While a scouting report saying a player pushes the ball is strong evidence, it becomes even more powerful when hard statistical information backs it up.

Three starting one guards followed Jeter in this category: Jose Calderon, Russell Westbrook and Stephen Curry. Jeff Teague, another backup point known for his quickness, placed fifth.

This metric may not always demonstrate speed. Calderon, for example, could excel at getting the Raptors a good shot early in their offensive sets. So while he’s not the type of guard who usually pushes the ball, Toronto still played faster with Calderon in the game.

This stat does get influenced by who shares the court with each point guard. Obviously, you can’t run if your teammates can’t keep up. It also matters who plays the same position for their team.

Nonetheless, NBA agents now have another tool to show how their free agents can impact clubs looking to up the tempo.

Friday, August 12, 2011

The Other Side of Twitter

I’ve built a sports news gathering organization comparable to ESPN. There are 640 correspondents everywhere from Rio de Janeiro to Rochester, New York to Vilnius, Lithuania. Twenty-four hours per day, seven days a week, the news keep flowing directly to my phone. And it costs absolutely nothing.

Some view Twitter as a way of reaching out to others, which is absolutely true. But there’s another huge component that rarely gets mentioned: Twitter enables you to customize the news that comes to you. Whether I want to learn about a hot high school basketball prospect in New York City, track a minor leaguer in Williamsport, Pennsylvania or learn about emerging sports research or technology, I have a source.

Twitter has major advantages over more traditional ways of gathering information, even Google:

1) Getting the jump on real-time sports information. If there is a big trade brewing or other breaking news, you’ll see it on Twitter well before it hits the major sports websites. Why? Writers like Buster Olney or Ken Rosenthal will usually tweet before they post a story. It takes far less time to blast out 140 characters than an entire article that needs to pass through editors before reaching a webpage.

2) Everything comes to you. The mindset has always been to seek out topics which interest and have value to us. Since Twitter enables you to select followers and subjects that provide news you care about, there is no effort or energy required to find it. Whenever you want it, specialized information is there waiting for you.

3) Going beyond Google. For all its strengths, Google requires multiple steps to finding great sports info. You need to first find the right search terms. When you do, there’s no guarantee Google will have what you need. Even if it does, you may waste time sifting through meaningless links. With Twitter, the posts and links come to you. Your trusted followers do the legwork!

While negative tweets have come back to haunt athletes and other people in sports, it’s not very common. Besides, interacting isn’t necessary. It’s possible to build your news gathering organization without ever posting.

I’ve heard skeptics say “I barely have time to check email, why do I want to get on Twitter?” Unlike email, Twitter isn’t something you need to respond to. I’ll avoid reading Twitter for several days during baseball arbitration season. If somebody wants to contact you via Twitter, they’ll use one of its methods that directs correspondence to your inbox, just like an email.

For sports agents, the other side of Twitter can have tremendous value. And it will only get bigger and better.

Tuesday, August 9, 2011

The Big Three for Pitchers

Limit walks, avoid home runs and strike batters out. If pitchers excel in those three areas over time, they will succeed. It is easier said than done.

All three areas are controlled primarily by the pitcher. He does not depend on his fielders for success in them, although home runs can get impacted by his home ballpark.

Sabermetric theory holds that pitchers have limited control over the batting average on balls put into play against them. On these plays, pitchers with a strong defense behind them have a huge edge over those that don’t. Pitchers who perform well in the big three can usually offset poor fielding. And when helped by a strong defense, they can dominate.

Our research shows that very few pitchers shine in all three of these vital areas. For both relievers and starters, we chose levels about 10 percent better than league averages. For relief pitchers, that was 8.5 strikeouts per nine innings and fewer than 3.0 walks and .75 home runs allowed per nine innings in at least 250 career innings pitched. Four active pitchers made the cut: Joakim Soria, Jonathan Papelbon, Mike Adams and Takashi Saito.

The criteria for starters proved even tougher: 500 innings pitched, 7.25 strikeouts per nine innings, and fewer than 2.5 walks and .8 home runs allowed per nine innings. Roy Oswalt stood alone at these levels. Two young starters – Daniel Hudson and Madison Bumgarner – join Oswalt if we drop the innings requirement to 250.

Incredibly, the groups expand by just one player apiece with non-active pitchers included. Reliever Tom Henke and starter Pedro Martinez join them.

Several elite pitchers miss these lists by falling just short in one category, such as Mariano Rivera, C.C. Sabathia and Felix Hernandez.

Prior to free agency and arbitration, we will update this research and vary the criteria to identify other pitchers who stand out in the big three. Why is this important for baseball agents? Because success in these areas makes pitchers more likely to sustain excellence when changing teams.

Monday, August 1, 2011

Beyond the Basics: Sports Analytics and Baseball Free Agency

Baseball free agency is an exciting time for players, agents and The Sports Resource. Analytics can highlight a player’s achievements, demonstrate and quantify his value, and show his contribution to the club. Unlike arbitration – a process restricted by specific criteria – free agency packages can also focus on what’s ahead with statistical projections.

Since free agency usually involves changing teams, this may add another level of complexity. But the insight gained from this research pays off both immediately and down the road, when it comes time for the next contract. Context impacts statistics far more than many realize, and joining a new club can dramatically change it.

These four key questions address areas where sports analytics can have a major impact beyond the basic components of a free agency package.

1. How will the level of competition affect your player? We elaborated on the AL East's impact on player statistics in the January 2010 issue of The Sports Resource Newsletter. Fortunately, methods exist to predict the impact of competition changes on individual players.

2. In which ballparks would he excel? Actual performance in different ballparks can be valuable. However, players may lack enough plate appearances to make those statistics meaningful.

Park factors give us an indication of how a player will perform when changing stadiums. Everybody knew that Adrian Gonzalez would benefit from leaving PETCO Park for Fenway Park. But it isn’t always that easy. Park factors vary from year to year largely due to weather patterns. Complicating matters further, many stadiums help certain types of hitters more than others. For example, Minute Maid Park is great for right-handed pull hitters with power, but not nearly as great for lefty home run hitters.

3. What impact will a new lineup have? Hitting in a strong batting order has a positive effect on context-dependent statistics like RBI and runs scored, as well as batting average to a lesser extent.

4. Are the potential new teams over or undervalued? Every player wants to win, so this last question is vital. Team records can prove misleading. So it’s better to examine Pythagorean won-lost records, which project winning percentage based on runs scored and allowed. For example, the Astros went 76-86 in 2010 and finished strong. That made them look like a team poised to turn the corner. However, their Pythagorean record was just 68-94. This makes their poor 2011 performance less surprising.

Sunday, July 10, 2011

A Closer Look at Goal Scorers

Sports analytics hasn’t made nearly the same impact on the NHL that it has in the NBA or MLB, but that is changing.

The MIT Sports Analytics Conference held this past March, included a Hockey Analytics Panel. Don Fishman, the assistant general manager and director of legal affairs for the Capitals, had one of the more interesting comments.

“I think even strength stats and power play stats need to be drilled down more in terms of the value of a forward,” said Fishman. “You might have a fantastic forward that the coach is playing zero minutes on the power play. And you might think he’s having a down year. But when you filter out for even strength or shorthanded, he’s actually having a wonderful year. So statistics can lie, if you’re relying on power play stats.”

The overall goal scoring leaders get impacted by both the situations in which they play and how much they play. But a couple adjustments can identify the league’s best scorers.

We ran the numbers for all skaters who saw at least 750 minutes of even strength ice time in the 2010-11 regular season (430 players total). Here is the top 10 in even strength goals per 60 minutes.

Only four of these players also finished in the top 10 for total goals scored: Corey Perry, Jeff Carter, Michael Grabner and Danny Briere. Grabner was most impressive, making the overall list despite only spending 70 minutes all season on the power play. He topped the table above with 1.62 even strength goals per 60 minutes.

Alexandre Burrows also saw limited action on power plays - which hurt his overall statistics – but shined by scoring 1.45 goals per 60 minutes in even strength situations.

Thursday, June 30, 2011

Will This Be Your Breakout Year?

There are many articles out there about finding a job in sports. Almost every sports conference has a panel devoted to this topic. Most of the advice is sound, since it often comes from insiders holding influential positions.

The focus is always on “breaking into sports,” which has become very difficult due to the huge number of people attempting it. There is an alternate approach. I describe it as “breaking out”, like a hitter having a breakout season.

The world has changed. Back in the 1990’s, you had to build and polish a resume with all the right background, send it off to the decision makers, and then hope for the best. Now, technology enables sports outsiders to become insiders without actually breaking in. The barrier is still there, but the right skills and knowledge can streamline the process.

The key step is to put your work out there for all to see. Whether through a website, blog, app or videos, you can gain exposure in sports far easier than ever before. When I wrote The Baseball Perspective in the early 1990’s, it required a graphic designer, print shop and the U.S. Postal Service for a 12-page newsletter to reach 1,000 or so subscribers and prospects. The same process would take far less time and cost almost nothing today!

While your passion and skills should determine what you put out there, I recommend avoiding the edgy sports opinion blogs that are everywhere. Specialize as much as possible. Great examples exist all over the internet. HitTracker is an amazing website that tracks the flight and distance of every Major League home run. Darren Heitner’s Sports Agent Blog is a tremendous resource for insiders, as is Cots Contracts. How about starting a website analyzing NFL coaching decisions? Or how weather conditions impact game outcomes and/or statistics? Everybody wins – you gain exposure and the industry gets another resource.

Internships are great for making contacts and gaining experience. However, your work may not reach the masses or have your name attached to it. With our approach, there’s no limitation on who sees it, especially if you have no problem presenting at conferences and seminars.

Although easier than breaking in, breaking out in sports presents its own challenges. I’m sure the people who run the websites mentioned above had to work long and hard. But fortunately, talented individuals with something valuable to offer now have far more control over their own future in sports. Isn’t that the way it should be?

Thursday, June 23, 2011

One Simple Test for Predicting NBA Success

If a college player can score at a high rate before turning 20 years old, they have a great chance for NBA success.

This quick test was explained a few years ago in The Sports Resource Newsletter. That year, the 2008 NBA Draft had seven players selected who had averaged 20 points per 40 minutes in their final college season before turning 20 years old. Among that group, Derrick Rose, Kevin Love, Michael Beasley and Eric Gordon have emerged as strong NBA players. J.J. Hickson appears headed for a solid career. Jerryd Bayless and Kosta Koufos still have a ways to go.

The next two drafts produced just two “20 under 20” players apiece. All seem destined for excellent careers. The 2009 draft included Tyreke Evans and James Harden, while 2010 had DeMarcus Cousins and Al-Farouq Aminu.

This year’s draft features just three members of the 20 under 20 club. Kyrie Irving and Alec Burks have gotten their share of attention, but a third player isn’t projected to go until the 20’s in most mock drafts. Tennessee’s Tobias Harris actually did the other prospects one better – he averaged 20 points per 40 minutes before turning 19 years old! This hasn’t been done by a drafted player in his final college season since Kevin Durant in 2007.

Burks turned in his own impressive feat by going 20 under 20 in both of his college seasons. He joined Derrick Williams, Jordan Hamilton, Kenneth Faried and Chris Wright as players who did this in seasons other than their final college campaign.

Tuesday, June 21, 2011

Five Reasons to Activate Your Sponsorships with Statistics

When fans enter professional sports venues today, they become immersed in technology. While the huge HD video boards grab their attention, they also want unique insight about their favorite team. Diehard fans seek the type of information that only comes from innovative statistical content. So where is it?

In the past year, I have visited numerous NBA, MLB and NFL facilities – including some of the newest and most technologically advanced in the nation – yet not once did they present anything beyond the basic stats.

This is great news for brands looking for creative ways to activate their sponsorships. Fans seek out revealing statistical content. And while teams want to provide it, they may lack the resources or expertise to make that happen.

Here are five reasons why it pays to make creative statistical content part of your sponsorship activation strategy:

1. This approach brings sponsorships to life. Rich statistical content educates fans about the strengths of their favorite team and its players, and sends a crystal clear message. The right metrics won’t confuse fans at all, but build on their connection to both the sponsor and property.

2. Innovative statistical content is ideal for social media. Besides gaining exposure on the video boards, sponsors can also deliver a powerful message in 140 characters, whether by text, Facebook, Twitter or all three mediums. Since fans following a team via social media tend to be its most loyal enthusiasts, brands connect directly to them. Of course, the content must have value.

3. Creative sports statistics are sticky: they get repeated over and over.

4. It is cost effective. Putting such a plan in place will fit well within your activation budget. Brands get ROI for a fraction of what other methods deliver.

5. Analytics tell a great story. Much of the sports industry has yet to discover this. So if you’re looking for fresh ideas, why not make them part of your brand’s story?

Activating sponsorships in this way requires the right content and approach to make it happen. And The Sports Resource has that covered.

Steve Fall's business The Sports Resource has provided NBA, MLB and NFL agents with sports analytics consulting since 1997. Agents use his statistical packages to build player value for contract negotiations, free agency, arbitration and the draft. Last year alone, he worked on over $335 million in contracts. His analytical tools also help companies activate their sports sponsorships.

Tuesday, June 14, 2011

Properly Valuing Hit Types

It seems logical that a double is twice as good as a single, a triple three times as good as a single, etc. However, the run values for offensive events vary tremendously from those figures. And they also change over time, depending on the level of offense in the Major Leagues.

Making use of a statistical technique called regression analysis, The Sports Resource calculated run values for five offensive events over two different time frames. Run production dipped from the first timeframe (2000-07) to the second (2008-10), which impacted the results.

The value for triples stands out more than anything else, especially in the more recent timeframe. There’s a large gap between the value of doubles (.75 runs) and triples (1.28), and a much narrower one separating triples (1.28) and home runs (1.42). Common sense would assume that a hit covering 4 bases would carry 33 percent more value than one for three bases. But the actual difference is just 10.9 percent.

What does this mean for agents? Players who hit lots of triples and relatively few homers – such as Jose Reyes and Dexter Fowler – produce more runs than many would think. For example, Reyes' three homers and 11 triples (through June 13) are equivalent to 13 homers and 0 triples.

The other interesting change is the drop in run value for singles. The best possible explanation is that with less overall offense, it’s harder to bring home runners from first base (especially due to the dip in home run rate). In addition, there tends to be fewer runners on base when singles get hit than from 2000 through 2007, further decreasing their value.

Monday, June 6, 2011

Better Sports Statistics and Missed Opportunities

Moving beyond core statistics has immense benefits for anybody associated with or interested in sports. Advanced metrics – or even relatively simple per minute stats – bring greater insight and understanding.

It takes a look inside the numbers to see the value of players like Joel Anthony. The ABC announcers missed a great chance to do so in Game Two of the NBA Finals. When Anthony made an amazing block, commentator Jeff Van Gundy joked that play-by-play man Mike Breen would have been far more expressive had LeBron James made the play. Did anybody on the broadcast realize that Anthony is the second-greatest shot blocker in Miami Heat history? Don’t the viewers deserve such insight?

Among Heat players with 1000 career minutes played, only Alonzo Mourning (3.67) blocked more shots per 40 minutes than Anthony (3.01). They rank one-two in block percentage as well, which estimates the percentage of opposing two-point shots a player swats while on the court. Unfortunately, that’s not the type of information provided during telecasts, at least not yet.

Anthony is so good defensively that it enables him to contribute despite obvious shortcomings in his game. According to ESPN.com’s Tom Haberstroh, the Heat outscored their opponents by over 19 points per 100 possessions during the regular season when Anthony played with James, Dwyane Wade and Chris Bosh. With this sensational shot blocker positioned down low, the Heat can play tight defense on the perimeter and force turnovers.

Anthony has increased his blocks per 40 minutes figure during the playoffs (2.85 through June 6) compared to the regular season (2.54). He also had Miami’s best postseason plus/minus figure (+88).

As detailed in a recent post, analytics tell a great story. None of these statistics are confusing or difficult to explain, and they show the impact Anthony has on the game.

Agents and clubs officials see the value of advanced metrics, and use them because they increase bargaining power and influence lucrative contracts. It will take some time before sports analytics has a major presence on game broadcasts, stadium and arena video boards, and sports talk radio. But it will arrive, and it won’t be long.

Wednesday, June 1, 2011

In Defense of Win Totals

In a recent issue of ESPN the Magazine, Steve Wulf wrote about the debate over pitchers’ win totals. He summarized that wins have far more value when used to evaluate careers than individual seasons.

The Sports Resource put this to the test by comparing pitchers wins – which many statistical experts despise – to Wins Above Replacement (WAR), perhaps the best individual metric for quantifying a starting pitcher’s contributions.

During the 2010 season, the top 10 pitchers in wins had a 3.14 ERA. The best 10 pitchers in WAR posted an outstanding 2.60 ERA. Obviously, the latter group was much stronger. Phil Hughes made the wins group with a 4.19 ERA. The highest ERA in the WAR group was Jered Weaver’s 3.01.

As the timeframe expands, something interesting happens: the gap begins to narrow considerably. After the 0.54 ERA difference in 2010, it drops to just 0.19 over five seasons (2006-10). In a 10-year stretch (2001-10), the gap falls to 0.11 (see chart). While wins never match WAR as an evaluation tool, they become much more valuable.

While run support, defense and bullpen support impact win totals tremendously in one season, those factors tend to even out over time. Rarely will a pitcher receive horrible run support over a 10-year timeframe. His support/luck will eventually improve. Or, if he pitches for a poor team with consistent offensive problems, he could sign as a free agent or get traded to a higher scoring club.

The takeaway message is that agents shouldn’t dismiss win totals completely. Career and multi-year win totals can demonstrate value for starting pitchers, especially in the later arbitration and free agency seasons.

Friday, May 20, 2011

Let the Numbers Tell the Story

Speaking at the MIT Sports Analytics Conference, Microsoft’s Bruno Aziza explained how “Analytics tell a great story.”

Unfortunately, analytics rarely get used by the mainstream sports media in this way. Instead, metrics often get cherry-picked to fit their story. As a result, the public never gets the entire unbiased view that analytics provide.

For example, the media focused attention on the Miami Heat’s dismal shooting percentage in crunch time, concluding that they couldn’t excel in the clutch. They did shoot one for their first 18 when tied or trailing by three points or less in final 30 seconds. However, most teams have a low success rate in these situations (because defense is tight, referees hesitate to call fouls, etc.). And there are many more clutch situations during games. A balanced analysis would have taken these shots into account as well.

Most importantly, all statistics need a sufficiently large sample before we can reach any conclusions. The Heat had taken just 18 shots which met the specific criteria used. That’s far too few to say that they were poor clutch shooters.

The same thing applies for the hitter who has gone 0-for-10 lifetime versus a certain pitcher. Should the manager decide that he can’t handle the pitcher? Of course not! It would take a sample of at least 50 plate appearances before knowing that for certain.

Presenting a player’s complete statistical profile requires looking at numerous metrics over a significant sample of games. That’s why it’s vital for agents to examine every piece of relevant statistical data possible.

In baseball, all encompassing categories like WAR make valuing players easier. But that is just the start. As explained last year in The Sports Resource Newsletter, role players can have greater impact in select circumstances. Sustained success in high leverage situations also adds to player value.

Yes, analytics tell a great story. But it requires thorough analysis to present the data in a way that builds maximum value for your players.

Thursday, March 31, 2011

The Problem with Per Game Statistics

With so many better metrics available, it’s hard to believe the mainstream sports media still uses per game statistics to evaluate player performance.

ESPN Radio’s Colin Cowherd recently compared Derrick Rose to Allen Iverson. The comparison makes sense on some levels. Both players are shoot first, pass second point guards. Both are incredibly quick and great finishers. Cowherd’s mistake was using per game statistics, which made the players appear closer in performance than they really are.

Cowherd started by saying Iverson had the edge in points per game over Rose in their third NBA seasons: 26.8 to 25.0. This brings up the biggest reason per game numbers fall short: starters vary tremendously in how many minutes they see per game. Iverson played 41.5 minutes per game versus 37.4 for Rose. Using points per 40 minutes to even the playing field, Rose (26.7) has actually scored more than Iverson (25.8).

Rose had a huge edge in assists per game (7.9) over Iverson (4.6) in their third seasons. That difference increases with the more revealing assists per 40 minutes figures: 8.4 to 4.5. Iverson did spend extensive time at shooting guard that year while Eric Snow played point for the Sixers, which impacted his assist numbers. Still, Iverson never came close to matching Rose’s assists per 40 minutes figure in any career season. Rose had also shot for the higher percentage from both two-point (47.2 to 44.0) and three-point range (33.2 to 29.1) in season number three.

Rose had the advantage in John Hollinger’s PER as well, 23.4 to 22.2 over Iverson. Both players have high usage rates – which estimates the number of their team’s plays they use while on the court – of nearly 33 percent. So while they both use a high percentage of their team’s possessions, Rose produces more in those opportunities.

Iverson did have a big edge in steals per 40 minutes in his third season. And while he reached the foul line more often than Rose, they made nearly the same number of free throws per minute due to Rose’s far superior free throw percentage.

Most importantly, Rose is younger than Iverson was in his third season by one year and four months. It makes more sense to compare Rose’s third season to Iverson’s second campaign, which would cause the gap between the players to widen even further. Finally, Rose stands three inches taller than Iverson and weighs 25 pounds more.

While they have some similarities, Rose holds a decisive edge over Iverson at the same stage of their careers. That becomes clear when taking a look beyond their per game statistics.

Iverson was a great player. But in both performance and from a branding perspective, Rose is on track to soar much higher than Iverson ever did.

Wednesday, March 16, 2011

Sports Statistics as a Marketing Tool

Politicians discovered the power of numbers long ago. One might say “my administration created one million more jobs than any other in history.” Of course, it only takes a few minutes to pick that apart: How many jobs were lost? What was the net increase? What was the percentage increase? What was the average salary of these created jobs? But by the time his statement gets scrutinized, the politician moves on to the next talking point.

The same thing works in sports. In 2009, when Colt McCoy was a top Heisman Trophy candidate, the media repeated this statement over and over: “McCoy has won more games than any quarterback in college football history.” Wins are powerful, the true currency of sports. The stat spread everywhere and stuck in people’s minds, even though it was not a particular good statistic.

McCoy won more football games partly because he played in so many. Longer seasons and conference title games gave him more opportunity to record victories. Yes, he won the most games of any quarterback, but he was one of 22 starters. And many of those former teammates have joined him in the NFL.

Obviously it took a great quarterback to win that many football games. McCoy had to earn the starting job and keep it four years; no easy feat at a top program. He had a major role in 45 wins. Nonetheless, teams win games, not quarterbacks.

The McCoy stat still got extensive airtime on sports talk radio, highlight shows and game broadcasts. As with a smooth-talking politician, there was little opportunity in those settings to contradict it with objective evidence.

This demonstrates the power of numbers. Since few people effectively use sports statistics as a marketing tool, they present a blank canvas to work with. And the timing couldn’t be better with the rise of social media, when you may only get 140 characters to send a clear powerful message.

If even bad stats have value, can you imagine the impact from innovative statistical content? Finding this isn’t easy – as the best information lies beyond the core stats that dominate the mainstream sports media – but it is well worth the effort.

Monday, March 14, 2011

Summary of the MIT Sports Analytics Conference

Here’s a wrap-up of the MIT Sports Analytics Conference held earlier this month, with the focus on items of interest to sports agents.

This year’s conference drew 1,500 people to the Boston Convention and Exhibition Center. Representatives from 53 different professional teams attended, according to the organizers. Now in its fifth year, the event has evolved into as much a business conference as an analytics one, with topics about sponsorships and enhancing the game day experience.

Rockets GM Daryl Morey, one of the event’s organizers, pointed out that basketball is a sport that punishes mistakes during the opening panel on developing the modern athlete. He explained how people focus on all the dunks, but mistakes are costly and need to be minimized for success. While players that shoot high percentages and avoid turnovers get little media attention, teams clearly build such contributions into their statistical models and projections.

In the same panel, Morey said that during the NBA Draft process they’re often looking for flaws more than attributes. They identify what problems a player has that they think they can improve upon. This shows why it may be a good idea to address a player’s shortcomings in draft packages and then demonstrate how they will overcome them.

The Baseball Analytics panel also had some interesting exchanges. Tom Tippett, director of baseball information services for the Red Sox, talked about the Carl Crawford contract. Although he lacked the power of most well-paid outfielders, Tippett said that between triples and home runs, Crawford clears the bases about 30 times per year. Tippett said the team also researched how Fenway Park’s dimensions would impact Crawford’s defensive performance.

Both Major League Baseball and the NBA are moving toward having a complete digital record of each game. This creates tremendous opportunities for sports agents and their staffs to analyze and present this data on behalf of their clients.

Wednesday, January 26, 2011

Relievers and Consistency

Are relief pitchers more volatile than starters? While that seems to be the case, relievers also get evaluated in much smaller sample sizes.

Statistics usually get expressed in terms of seasons. That works great for starters, but not so well for relievers. Starters throw approximately three times as many innings as bullpen pitchers in a typical season, which gives them far more time to work through their struggles.

For this reason, we compared starters in one-third of a season timeframes to relievers in full seasons. This evens the playing field to help determine which group maintains more consistency.
We identified all relief pitchers that pitched 150 innings or more from 2008 through 2010 and posted an earned run average between 3.00 and 3.50. The starters had to pitch 150 or more innings in 2010 alone with an ERA in that same range. Nineteen relievers and 17 starters met the criteria.

The starters group included CC Sabathia, Cliff Lee, Chris Carpenter and Tim Lincecum. The relievers had pitchers like Francisco Cordero, Huston Street, Brian Fuentes and Jonathan Broxton. The two groups accumulated a comparable number of innings: the bullpen group totaled 3510.2 innings versus 3602.1 for the starters. Both groups had an identical ERA of 3.25.

Based on inspection, the starters appeared slightly more volatile. None of the relievers posted an ERA over 5.00 in any of their annual timeframes. However, two starters did so in their two-month periods: Max Scherzer (6.42) in April/May and Jon Garland (5.16) in June/July. The starters failed to post a single ERA below 2.00, while the bullpen group had three: Jeremy Affeldt (1.73) and Ryan Franklin (1.92) in 2009 and Chris Perez (1.71) in 2010.

The best way to measure consistency is through standard deviation, which simply measures how much figures differ from the average. The standard deviation for the starters (.635) was slightly lower than the relievers (.677). Basically, there was very little difference in consistency between these groups.

The starters also had one huge advantage. While the relievers had an entire offseason in between their seasons, the starters flowed directly from one two-month period into the next. In several cases, the relievers changed teams and/or leagues during the offseason, making it even harder to sustain consistent performance.

Before making any conclusions, more data should be examined beyond this rather small study. It would also be valuable to examine statistics like OPS allowed, since ERA does not account for how relievers pitch with inherited runners.

Nonetheless, it appears that what some perceive as lack of consistency has more to do with the limited number of innings relievers pitch per season.