Adjusting for Context and Arbitration

One of the keys to solving the value puzzle in sports is separating what the player controls and what he doesn’t. Sounds simple, but it’s not.

In baseball arbitration, context can be a huge factor. In extreme examples – such as pitcher who plays home games in Coors Field – the arbitration process makes the proper adjustments to salaries. But there are many others where it doesn’t. For example, factors like run support, defensive play, and bullpen performance all have a massive impact on starting pitcher statistics.

Relievers also face challenges when it comes to context. Holds and saves greatly influence arbitration salaries, and they get impacted by the man calling the shots. Managers vary tremendously in how they handle relievers, and this can be good or bad for pitching stats. Here are just a few examples:

Pitching Changes: Some managers change pitchers far more often than others. Giants Manager Bruce Bochy used 524 relievers in 2013 versus 440 for Washington’s Davey Johnson. The frequency of Bochy’s changes created more opportunities for holds. Giants relievers had 46 holds of less than one inning. The Nationals had just 15.

Free Passes: Seattle’s Eric Wedge ordered 48 intentional walks last season, compared to 10 by John Farrell and the Red Sox. This hits the statistics of relievers especially hard, since they pitch far fewer inning than starters. Intentional walks cause stats like walks per nine innings and WHIP to rise, even though the pitcher did nothing to cause it. Because intentional walks are usually poor strategic moves, they can also increase a reliever’s ERA.

Wearing Them Down: Overuse can also make relief pitchers less effective. The Red Sox and Indians had similar ERA figures – both for their starting rotation and bullpen – yet Terry Francona worked his pen much harder. Cleveland relievers pitched on consecutive days 122 times. Farrell, on the other hand, used Red Sox pitchers only 71 times without a day of rest.

Every player’s situation is different. And The Sports Resource identifies how context impacts all the stats that matter in arbitration.

Ghosts, Moonlight Graham, and the Fan Experience

During the movie Field of Dreams, Kevin Costner’s character Ray Kinsella sees Moonlight Graham’s statistics on the scoreboard while watching a game at Fenway Park. Kinsella soon realizes that a ghost is responsible for that information, and nobody else in the ballpark sees it besides him.

Now 24 years since the movie debuted, are we approaching the day when sports venues display personalized content on the video board?

While it’s currently impossible for each fan to view different content on the same scoreboard, personalized statistical content would benefit fans, clubs, and brands/sponsors. Why should I have to view meaningless items like “Pujols has gone 2-for-3 lifetime against pitcher A?” On the other hand, I’d like to see stats like win expectancy and left/right splits that have a major impact on the game.

Mobile apps provide one solution. However, do teams want thousands of fans looking down at their devices? Fortunately, there are other alternatives.

1)      Teams could dedicate one of their smaller video boards to advanced statistical content. A tech/data-related company would jump at the chance to sponsor this feature to build its brand. 

2)     Fans in luxury boxes could choose between content options like “old school stats”, “advanced metrics”, or “fun and games” on their video screens. All three could share the screen with the game’s live video feed. 

3)     One inning per game, clubs could show advanced statistical content on the big screen.

All three approaches offer great sports sponsorship activation opportunities. Best of all, they make the game far more interesting for the fan.

The Best Defense for Arbitration

One of our recent posts detailed vital differences between baseball arbitration and free agency. Here’s another major one: an opposing party isn’t trying to discredit exhibits in your free agency packet. That is true in an arbitration hearing.

The Sports Resource strives to make agents arbitration briefs “rebuttal proof” by going on the offensive. One way to do this is make key points at least three different ways. This strengthens your arguments and defends them against the close scrutiny that always follows your presentation.

Even a powerful arbitration exhibit can get refuted when the club has its rebuttal time. Dismissing a point supported by multiple exhibits is much more difficult.

If one theme focuses on a position player’s clutch performance, we first demonstrate with core numbers. For example, we could show a strong slash line (batting average/on-base percentage/slugging percentage) late in close ballgames. Another exhibit could detail all the player’s clutch achievements in the platform season: extra inning hits, game-winning RBI, etc.

Advanced metrics like win probability added – a great tool for this purpose – can drive home the point even further. Finally, we may include pertinent quotes from baseball insiders like teammates, coaches, or even front office members. This not only supports the numbers, but makes them come alive.

It’s never easy. The player may not have excelled in all these statistical categories, or he may have shined in some during the platform year but not his career timeframe. We find the right balance, avoiding anything that appears contrived, and build support for the main themes of the case.

Arbitration and Free Agency: A Key Distinction

Baseball arbitration and free agency differ tremendously in one respect: free agency is about what a player will achieve while arbitration focuses on what he has done.

Future projections – based on past performance – play a role in free agency. But projections aren’t included in the arbitration criteria. This distinction makes certain types of information and analysis, which clubs may not want to see in a free agent package, extremely important to an agent’s arbitration brief.

For example, skills like bunting and advancing runners with outs won’t fetch top dollar on the free agent market. But arbitration is a whole different ballgame. Exhibits detailing how a player excelled at “little things” – that resulted in wins – help make your brief a winner. Demonstrate how he performed better than comparable arbitration eligibles in these areas, and it strengthens your case even further.

Gregor Blanco didn’t post big numbers in core statistical categories, but he delivered in many other ways that impacted the Giants outstanding season.

1) Blanco did not hit into a double play in 453 plate appearances. This had only been done seven times since 1950.

2) He advanced a runner from second base with nobody out in seven of eight plate appearances in this situation.

3) He drove in a runner from third base with less than two outs 10 times in 18 opportunities. Six of these RBI came in the seventh inning or later, seven contributed to wins and three made up the margin of victory in one-run games.

4) Blanco topped 25 steals and had 5 triples in fewer than 400 at-bats. Only one other Giants player had done that since 1912.

5) He executed five successful sacrifice bunts. The Giants went 4-1 in these games.

All those feats are impressive enough, but they also contributed to a World Championship team. Looking back, for arbitration, that bottom line is all that matters.

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.

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.

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.

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.