First there was the error. A century later, we finally have the natural antithesis to the error: the Web Gem.

The good people over at ESPN track all the best defensive plays in baseball on a daily basis, and come up with that short minute segment which is often a highlight of my night. This year, they began keeping track of who made each Web Gem, and were kind enough to share the data with me. Web Gems are intended solely for the purposes of the television viewer. They are simply the most entertaining plays to watch, and aren’t supposed to be used as a defensive measure. But errors really never should have been used as a defensive measure either. Nonetheless, these are all valuable data points, so my first order of business was to see how errors and Web Gems stack up. Here you have error to Web Gem ratio.

I assigned every player a position based on where he played the most innings, and all stats count toward that position.

There were five players who made no errors but tallied three or more Web Gems.

Here, you see some hits and some misses. Sizemore and Vizquel are, by all accounts, excellent defensive players. David DeJesus and Austin Kearns are average. And then there’s Jason Bay. For the Jason Bays of the world, I submit to you the Gary Matthews Jr. effect. Matthews, you may recall, made a stupendously phenomenal catch a couple years ago that was replayed and analyzed like the Zapruder film. His defensive reputation was built off of one play. And you can't point out the number of errors for outfielders to disprove the reputation, since outfielders don't make errors. Anyway, I hope nobody signs Jason Bay to a GMJ-type contract.

But it’s the aughts, and we’ve moved past errors. In fact, Baseball Info Solutions came up with a similar method presented in the Fielding Bible II called Good Plays/Misplays that uses objective criteria to come up with a more advanced Web Gems/Errors. These data aren’t available to the public, but some BIS defensive data is. FanGraphs lists the number of expected outs each non-catcher position player should make based on the distribution of balls in his zone. So I'm going to call the amount of Web Gems per expected out each player's Web Gem percentage.

That looks much more like the defensive spectrum. Third basemen get a boost for playing the hot corner, where there are myriad opportunities to show off quick reactions as right-handed batters scorch balls down the line at over 100 MPH. 3Bs Ryan Zimmerman, Mark Reynolds, Brandon Inge, and David Wright were the only players to total double-digit Web Gems this year.

How does the ability to make the spectacular play match up with UZR, the most popular advanced defensive metric? For the rest of this article, I'll use the statistical method of correlation. A correlation coefficient returns the strength of the relationship between two variables. Closer to 1 indicates that there is a positive correlation, closer to -1 indicates a negative correlation, and closer to 0 means that there is no relationship. The overall correlation was .08, which is very weak. I think that on the Opening Day Web Gem segment, Karl Ravech should ask John Kruk* whether he knew that the .26 correlation coefficient between UZR and Web Gem percentage for third basemen was easily the strongest correlation of any position.

*How is it possible that someone who is so outspokenly anti-statistics literally walked away from the game the moment he reached a .300 career batting average?

I would venture that Web Gem percentage correlates with UZR not because Web Gems assess skill, but because they track the most influential plays. The average runs saved per play defensively is .8, a tick higher than that for outfielders. I’d venture that most Web Gems are plays made no better than 10% of the time on average. So for every web gem, you can probably attribute at least half a run to that player's value.

Tangotiger’s invaluable Fans' Scouting Reports finished balloting this week. I’m guessing that Web Gems will be even more influential in shaping the fan’s opinion than in swaying any defensive statistics. Here, I'll report the correlation coefficients between Web Gem percentage and several ratings from the FSR.

You see that fans are likely more influenced by spectacular plays made by infielders than by outfielders. Since such a significant portion of a third baseman's fielding ability is making the remarkable play, Web Gems correlate well for 3Bs in both UZR and scouting reports. The only surprising result I found is that there isn't a positive correlation between throwing strength from right and center fielders and Web Gem percentage. I figured a lot of outfield Web Gems would be a result of throwing strength. Perhaps throwing strength isn't strongly correlated with outfield assists. Something to look into.

And since the Gold Gloves were announced this week, I'll leave you with a table of each Gold Glovers relevant statistics as well as the guys at each position who I consider to be the best not to have won the award. Adam Jones over Franklin Gutierrez really stands out as a poor selection.

Thanks to the Baseball Tonight staff for giving me access to the Web Gem data. The Baseball Tonight schedule can be found here, and Web Gem leaderboards are updated during the season on the BBTN Clubhouse page here.