Analytics is A Confusing Word To Use for Everything Statistical

Recently Charles Barkley took those who use “analytics” in professional basketball to task. His complaint was that he felt people were trying to use them to get themselves involved in a sport they couldn’t play themselves.  Barkley was being far too simplistic and did not recognize the true meaning of the world analytics.  But that is not just his fault.  Like “polar vortex” being thrown around for any cold weather system that moves down into the U.S. from Canada, analytics is being used for any statistical measures for sports.

Both are wrong.  No every cold spell is from a polar vortex.  Not all analytics are inventions of mathematicians who want to invent something new.

Analytics actually includes all the stats fans have followed for years.  Scoring average, field goal percentage, free throw percentage, points scored, points allowed and personal fouls are analytics.  In baseball batting average, home runs, runs batted in, on base percentage and slugging percentage are also analytical.  Baseball has a whole lot more as you know.

The point is that we have been using analytics for years.  We just didn’t call them that.

However, there IS a problem.  Some analytic formulas devised in recent years–primarily in baseball– seem to have no real reason for their existence except to be used for rating or ranking players.  That may be OK for fantasy league players perhaps–and may have been why many of the new analytics were devised in the first place, but don’t really have significant relevance to the game itself.

It has been the “in” thing for some sportswriters to cite stats like War (Wins Above Replacement) or Win Shares..or even OPS, for example.  The first two are of no value to the actual game really and the latter tells less than the two statistics it has been combined from (adding on base percentage and slugging percentage) do when viewed individually.  OPS is, like WAR and Win Shares simply a way to rank players.  For what reason I have no idea other than a way to put value on them for fantasy leagues.  Using any of them for MVP voting would be OK if the voters spent the season locked in a basement and never actually saw any baseball games.

At this point those who want to defend WAR and Win Shares and Runs created and other of what I call artificial stats are screaming, “He is an old timer who doesn’t get it…a dinosaur.”   They would be wrong.

Analytics IS  very important part of modern sports.  It just isn’t the artificially combined numbers that matter. It is what has resulted from hours and hours of researchers documenting actual play on the field and/or courts.

The stats that show where a hitter should be played defensively based on his past tendencies against various pitches and pitchers is a good part of analytics.  The same with how effective a basketball shooter is from various spots on the court with different defensive set ups is good analytics.

The numbers that show which umpires tend to call which pitches strikes and which don’t is a valuable tool.

This are the analytics that matter.  The stats that are aids to the eyes on the field or court–the scouts.  Scouts, for instance, have known for years that David Ortiz is a dead pull hitter.  They didn’t need analytic proof. But to convince the manager of the opposing team that a radical shift on Ortiz might be the best idea is where the analytic statistics makes the point.

In baseball some pitchers are nervous about seeing their defense aligned radically behind them since they feel hindered in what they can throw.  But the stats have shown that if that pitcher throws his normal game and the hitter swings in his normal way the defensive alignment is correct.

Analytic measurement such as now done is not a predictor of the future.  All the numbers that have been used to come up with the final product are based on the past.  Baseball has always been a game of percentages.  The use of analytics aids in that use.

Oakland A’s General Manager Billy Beane has been credited with using analytics to build a winning baseball team.  He did use some stats to find players that might have been under-valued as examined in the book and movie, “Moneyball.”  However, he won with some big stars during the period cited.   He filled some holes.  Primarily he went after some players that appeared to have enough talent to learn new defensive positions and had a good on base percentage in relation to their actual batting average. But most important for the A’s of the time, he went bargain basement shopping.  The A’s could not spend lavishly on high dollar free agents in bulk like the Yankees or Red Sox at the time.

All of us have gone bargain shopping before.  Whether at a garage sale, flea market or discount department stores bargains can be found.  Its no different in sports.  Some players are sitting on the bench of another team or stuck in the minor leagues because stronger players are ahead of them.  They doesn’t mean they might not be exactly what your team could use.  GM’s are always looking for players like that.  They watch them play, but also evaluate based on the statistical record of the player from his past.  That is all analytics.   The name scares some away…like Charles Barkley perhaps–but in most cases it is just using the stats to help evaluate a player’s skill set.   Good analytics aren’t concerned about ranking players, but helping scouts, GMs, writers, broadcasters and fans evaluate them.

Don’t be scared of the word “analytics”.  It is a catch-word for a lot.  Some of it of great value and some of it less so.  Using some of the modern scouting and evaluation tools is no sure fire way to build a winner.  The best players do that.  But using all the tools available can help teams be as good as they can be…whatever that level may be.

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About gregclucas

Author, "Baseball-Its More Than a Game" available through Amazon.com, BN.com or by order. Veteran sportscaster with extensive play by play experience in MLB, NBA and college sports.
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