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Trends and Outliers

TIBCO Spotfire's Business Intelligence Blog

Category Archives: Sports Analytics


The Data Analytics of Super Bowl XLVIII and the Best Data Geek Commercials

Sometimes when you make predictions based on the available data – they just turn out wrong. Really wrong – especially when it comes to sports. And that’s the takeaway from Super Bowl XLVIII. Three predictions gone awry. Very awry.

shutterstock 88721260 300x225 The Data Analytics of Super Bowl XLVIII and the Best Data Geek CommercialsLet’s start off with the hope we all put in Punxsutawney Phil, American’s favorite weather forecaster. We weren’t really surprised by his forecast, but we were hoping (predicting) that he would give this cold, snowy nation a little glimpse of warmth ahead.

Nope. He saw his shadow. And it’s six more weeks of winter.

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How Boston Won the World Series: Finishing Strong by the Numbers

It’s been 95 years since the Red Sox won a World Series at Fenway Park. It dates all the way back to when a pitcher named Babe Ruth called the venerable ball yard home.

images1 How Boston Won the World Series: Finishing Strong by the NumbersAnd what a fitting win in light of what happened this summer at the Boston Marathon.

The hashtag #BostonStrong came out of that terrible tragedy and describes the sentiment of Wednesday’s big win against the St. Louis Cardinals at Fenway Park. Since Wednesday, this hashtag has been used more than 202K times.

“There are no perfect endings after life and limb are lost, but this was the best thing this great American city could hope for Wednesday night,” according to “The Red Sox won the 109th World Series, beating the Cardinals in six games, and took the next step in a healing process that followed the Patriots’ Day bombings at the Boston Marathon.”

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Analytics, King James and the Next Generation of Moneyball

Perhaps the most visible evidence of the competitive advantage that can be fueled by data analysis is LeBron James’ performance in the NBA playoffs this year and last, compared to previous lackluster post-season play by the Miami Heat superstar.

nba Analytics, King James and the Next Generation of MoneyballBut King James’ less-than-stellar performance on the basketball court happened before he took a hard look at the analytics behind his play, notes Michael Schrage, a research fellow at MIT Sloan School’s Center for Digital Business, in a post in Harvard Business Review.

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Visualizing Fantasy Football Success: NFL Week 5

Before finalizing your Fantasy roster for Week 5, @TIBCOSpotfire‘s resident sports analytics geek, @Brett2point0, has a few last minute data-driven insights for head-to-head, “start ‘em/sit ‘em” matchups:

heatmapwk4 Visualizing Fantasy Football Success: NFL Week 5

#FantasyFootball insight: Chiefs among bottom 11 #NFL defenses, allow back-breaking pass plays>>result in TDs

The data suggests that Kansas City’s glaring weakness is in the secondary. Good news for owners of Baltimore’s deep threat, Torrey Smith, and quarterback Joe Flacco!


#FantasyFootball insight: despite Atlanta’s above average D, still safe to “run” with RG-III! #NFL #analytics 


NFLdefWk4 1 Visualizing Fantasy Football Success: NFL Week 5

Given the star rookie’s start, this is a bit of a no-brainer. Though Atlanta is among the top 15 defenses in the league, Washington should have success on the ground as Atlanta allows an average of 147 rushing yards per game (as well as 4+ yards per carry).

So, good luck, and after you bring home a “W” against your friend, work colleague, or crazy uncle . . .

 Next Steps:

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Visualizing Fantasy Football Success: NFL Week 4

Before you set your lineup and hit the Fantasy gridiron this weekend, consult the data-driven insights of @TIBCOSpotfire’s resident sports analytics geek @Brett2point0:

1heatmapwk31 Visualizing Fantasy Football Success:  NFL Week 4#FantasyFootball #analytics insight: Confidently start BOTH Texans RBs! Titans>>most rush. yards/points allowed in #NFL

When Houston gets down to the second half, the team will turn to both Arian Foster and Ben Tate and the ground game to protect their lead on Tennessee, kill the clock, control the ball, and escape with an easy victory. Grab those “garbage time” points!


Avoid #FantasyFootball match-ups w/NFC West teams, toughest #NFL division to score against in 2012: #dataviz #analytics

If you can avoid it in a choice between players in a flex roster spot, avoid players matching up against NFC West teams whenever possible (especially San Francisco, Seattle, and Arizona). It can be a very, very long Sunday afternoon when your Fantasy players’ offense isn’t even on the field.

treemapwk3 Visualizing Fantasy Football Success:  NFL Week 4


#FantasyFootball insight of the week: bench “Action” Jackson vs SEA (tough against the run): #NFL #dataviz #analytics

With that said about Seattle in the NFC West, one player facing a tough road to production this week is St. Louis running back Steven “Action” Jackson. If you have better options, bench him.

GetImage.ashx  Visualizing Fantasy Football Success:  NFL Week 4

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Is the NFL Fumbling Big Data Analytics?

The world of big data analytics first enters the public mainstream with the popular book and hit film Moneyball, which chronicles the Oakland A’s success using statistics and data mining to win Major League Baseball games.

Many of Oakland’s MLB competitors have started playing Moneyball, as have a bevy of National Basketball Association teams. Recently, English soccer teams began turning to analytics to boost their performance on the field.

fumble 300x199 Is the NFL Fumbling Big Data Analytics?But, the NFL may be ignoring the benefits of big data analytics at its own peril, according to a Ted Sundquist, former general manager of the Denver Broncos.

While so much of today’s game has been boosted by technological advances – such as film being replaced by digital video and game planning that can be done via software – many teams have not fully embraced the power of analytics to enhance their scouting, Sundquist argues.

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Gooooooal: Soccer Scores with Moneyball and Statistical Analytics

England’s Manchester City Football Club (soccer to those of us in the US) is taking the Moneyball statistical analytics concept made famous by the Oakland A’s baseball team a step further, by releasing detailed data about the team to the public to try to mirror the success the NBA and MLB have had in the US.

Soccer ball and money 150x150 Gooooooal: Soccer Scores with Moneyball and Statistical Analytics“There are many people in the analytics community right now who have the skills, desire and vision to make a difference in the performance analytics space, people who can add significant value such as Bill James did in baseball,” team officials note when announcing the move. “But those people have no significant data to work with.”

While this move is “essentially unprecedented in the soccer world,” it follows the open-source and crowdsourcing trend of making data open to large groups of people to spur innovation, notes the Atlantic magazine.

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An Olympics Data Site Worthy of a Gold Medal

I am a sports fanatic (although I draw the line at professional wrestling) and as such, I can’t wait for the kick off to the London 2012 Summer Olympics.

And that got me to thinking about what we could learn from all the data associated with the Olympics. So I did a little research and found the really terrific official Olympic site and I thought I’d share some of the more interesting Olympics factoids from that site and others with you.

Did you know that London will be the first city ever to have hosted three Olympics? The city was a last-minute choice in 1908, stepping in for Rome after Mount Vesuvius blew its top. Then London got the nod again in 1948 when Germany and Japan were banned after they lost World War II.

And here’s an infographic with some interesting Olympic info:

Olympic Infographic WEB 478x1024 An Olympics Data Site Worthy of a Gold Medal













































The cheapest tickets in Athens in 2004 were £43 ($67), more than double London 2012’s bargain price of £20.12 ($31) for certain events including the opening ceremony, according to The Telegraph in the UK. But at the other end of the spectrum the most expensive tickets to events at the 2004 Olympics in Athens cost a maximum of £833 ($1,298), much less than the $7,300 (£4,684) per person price tag (before taxes) to some of the events in London.

The UK Anti-Doping association has released figures on drug testing for athletes from 26 of the sports participating at the 2012 London Summer Olympics. The statistics, complied by the World Anti-Doping Agency, include the number of samples tested in each sport for every year between 2003 and 2010, as well as the number of tests that indicate the use of a prohibited substance.

Between 2003 and 2008 the total number of samples taken across all sports increases from just over 100,000 to 166,185. In 2009 this figure falls slightly to 166,106, and the most recent total, taken in 2010, stands at 162,130 .

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The Data Analytics of the NFL Draft

draft 2007 2010 2009 2008 The Data Analytics of the NFL Draft Today is a big day for all you football fans and data geeks. Are you ready for the NFL draft?

This year’s draft features more analytics than ever before. Plus, the business decisions of NFL owners are center stage in light of what happened in Denver and Indianapolis the past couple months.

Tonight, after nearly not having a 2011 season, we’ll see NFL teams lessen their risks as new NFL collective bargaining rules go into effect. According to an article in Forbes, this year’s draft is less of a risk than years past and “drastically” reduces the amount of moolah “an unproven player” can receive in his first year.

From a business perspective, it’s a good move to make a decision based on analytics and performance over the perceived value of talent. And some teams fare better than others when you look at the historical data.

To determine which teams have scored touchdowns in past drafts and which teams couldn’t even split the uprights, Forbes turned to a source after our own hearts – the analytics of drafted players over the course of four years (2005 to 2009).

The author defined parameters and specific questions before engaging the data and was able to make some solid decisions on which teams have made the best and worst NFL draft picks over time.

Best & Worst Teams in Draft Proficiency

We won’t leave you in suspense for the best and worst teams regarding drafting proficiency (according to research conducted by the author, Patrick Rishe, and a Syracuse sophomore with a bright career ahead – perhaps in analytics – named Tyler Wasserman).

According to Rishe’s feature in Forbes, the best teams at draft proficiency are the Green Bay Packers and the New York Jets and the worst teams at draft proficiency are the Cincinnati Bengals and the St. Louis Rams.

Now, for the data analytics criteria:

  • The researchers looked at a strict time period – 2005 to 2009 – to ensure that the players had sufficient time in the league to adapt to the pro environment;
  • They analyzed seven rounds of draft picks for 32 teams. (That’s all of the teams and all of the rounds.);
  • They looked at four variables to determine draft proficiency: the percentage of games a draft pick played; the percentage of games the player started; the career of a player (still playing in the NFL); and the number of Pro Bowl nods a player earned.

With this criteria, Rishe calculated an index that he explains here to get his top picks for draft proficiency. It’s well worth the read.

Bad Draft Pick = Costly Decision?

According to our featured infographic, the impact of a bad hiring decision in football can result in the loss of millions of dollars. However, a traditional college grad who works from age 25 to age 64 earns about $2.1 million or roughly $51,000 per year. That’s just 1% of an NFL draft flop. But here’s a question for you to ponder: Would a $51,000 flop hurt your business? Analytics can help any HR executive come up with the right answer.

The Year of the Quarterback Draft

Who will be the lucky first named pick – the appropriately named Andrew Luck (Stanford) or Heisman Trophy winner RG3 (Robert Griffin III of Baylor)? The expectation is that Luck will get the draw and take Peyton Manning’s old seat at the head of the Indianpolis Colts and RG3 will go second to the Washington Redskins. But strange things can happen in the NFL draft.

An interesting note about this year’s draft is that it’s only the fourth time since the NFC and AFC combined their selection processes in 1967 that two quarterbacks will go first and second. Even more interesting – in each of the other three times two quarterbacks went first and second in the draft, only one of the two went on to have a successful career in the league. Maybe RG3 and Luck will change this stat.

Defensive Deficiency Draft Indicator

data analytics of nfl draft 300x238 The Data Analytics of the NFL Draft Just for fun and to give the data geeks a little context around the defensive side of the draft, we’ve put together a heat map visualization on the 2011 season defenses. It breaks down the most important team defense KPIs and ranks each team by yards per rush, yards per pass, total yards allowed and total points allowed. It could give you a few insights into NFL draft strategy based on the defensive deficiencies. For instance a team that has high yards per rush allowed may need to draft interior linemen and middle linebackers and teams with high pass yards allowed may need a little help in the pass rusher and corner back positions.

Next Steps:

  • Tweet us your thoughts on this year’s draft and our heat map on the defensive deficiencies.
  • Don’t forget to check out our complimentary “5-Minute Guide to HR Analytics“ to see how you can get solid answers to questions like: “How do we spot and retain the most valuable players?”

Amanda Brandon
Spotfire Blogging Team

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Using Analytics to Handicap The Masters Golf Tournament

golf 150x150 Using Analytics to Handicap The Masters Golf TournamentWhen Bubba Watson made par on the second hole of a sudden-death playoff to defeat Louis Oosthuizen of South Africa at The Masters Golf Tournament on Sunday, he wasn’t the odds-on-favorite to win.

However, he was among the top seven golfers in the event picked by Las Vegas oddsmakers to win the tournament at 30-to-1. Tiger Woods was the odds-on favorite among Las Vegas bookmakers to win this year’s Masters at 4-to-1. Irish phenom Rory McIlroy was next at 5-to-1 odds, followed by Phil Mickelson and Lee Westwood at 10-to-1 and 18-to-1, respectively. Oosthuizen, the runner-up, was given 100-to-1 odds to win.

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