We know this much: Johnny Cueto had an excellent 2014 season.

How excellent was it? That depends on how you like your pitching stats.

The Reds starter was fourth in baseball in both raw ERA (2.25) and ERA- (61) and third in WHIP (0.96). Cueto was sixth in rWAR (which is based on runs allowed per nine innings) with 6.4, and only Clayton Kershaw ranked higher in RA9-WAR at FanGraphs.

If we switch our focus from pure run prevention to defense independent stats, while Cuetoâ€™s 2014 season still looks great, it is has the markings of a top-20 campaign, rather than one in the top five.

Cueto ranked 18th in FIP- (88) and 20th in xFIP- (87), while tying for 14th in fWAR (4.1).

We know that defense-independent statistics tend to be more predictive than ERA, so what does this mean for Cueto in 2015?

It would be important to start by noting Cueto has a history of out-pitching his peripherals, as since 2011, Cuetoâ€™s 2.48 ERA is 0.89 points better than his 3.37 FIP. Only Chris Young and Miguel Gonzalez have a larger negative ERA-FIP differential during this span.

Last season, Cueto struck out 8.9 batters per nine innings, walked 2.4 per nine, and allowed 0.81 home runs per nine. This translated to a 3.30 FIP, which was 1.05 points higher than his ERA.

As you might expect, a low batting average on balls in play (BABIP) and strand rate helped fuel this difference. Cueto allowed a .238 BABIP last season, tying with Young for the lowest rate in MLB. His 82.5% strand rate was second highest in baseball. While these factors can keep opponents off the scoreboard, they are generally not predictive going forward.

The Reds excellent defense is, at the very least, one factor here. Cincinnati led the majors in defensive runs saved, tied for the league-lead in defensive efficiency, and ranked fourth in both team UZR and UZR/150, according to Fangraphs.

Does Cueto also deserve some credit for keeping his BABIP low? Probably, but it is hard to say to what degree.

His low BABIP was not exactly something new last year, as since 2011, he has allowed the fifth-lowest BABIP among qualified starters (.260). Then again, balls in play are notoriously random, and BABIP takes about 2000 balls in play stabilize for an individual pitcher, according to Russell Carleton, so we should probably not put too much stock into this (Cueto allowed 1772 balls in play during this span).

In 2011, Cuetoâ€™s .249 BABIP made some sense in light of his batted-ball profile. His 16.2% line drive rate and infield fly rate of 11.6% were both better the league averages of 19.6% and 10.6%, respectively. This implies that he was in fact generating weak contact, which would help explain his low BABIP.

Last season, Cuetoâ€™s line drive rate (19.3%) was closer to the league average (20.8%), though his infield fly rate of 11.3% was tied for 17th best in the majors and above the league average of 9.6%.

There could be something here, but given Cincinnatiâ€™s strong defense and the fact the Reds pitching staff as a whole outperformed its collective peripherals (seven of the eight Reds pitchers who threw more than 50 innings last season had a better ERA than FIP), I would caution against apportioning too much credit to Cueto for his low BABIP.

For fantasy purposes, this may not matter as long as the Reds defense continues its elite level of play and runs are staying off the board in Cuetoâ€™s starts. Be aware, though, as Josh Barnes writes, that the Reds could sacrifice some defense in 2015 to improve an anemic offense that posted the second-worst team wRC+ last season.

That said, we should not discount the role Cuetoâ€™s own ability to field his position plays here, as he tied for third among pitchers in defensive runs saved in 2014 (6) and is tied for sixth in the league since 2011 (19).

He has also shown an above-average ability to control opponentsâ€™ running games, as he leads all pitchers in caught-stealing percentage (62%) since 2008 and is tied for eighth in pickoffs (granted, the Reds have been in the top four as a team in terms of caught stealing percentage, but Cueto has still outpaced his fellow Cincinnati pitchers here).

Keeping runners hesitant on the base-paths probably also has something to do with his better-than-average strand rates, but last year's mark of 82.5% certainly seems unsustainable, given left on base percentgeâ€™s (LOB%) tendency to regress towards the mean.

2014 was not the first time Cueto out-performed the league average in this regard, as he has posted a career LOB% of 76.9%, higher than the major-league average which has fluctuated between 71.4% and 73.5% since he made his big league debut.

Still, expecting another season with a strand rate greater than 80% is almost certainly asking too much. Consider this: there have been 22 seasons in history in which a pitcher posted a LOB% of 83.8% or better, and 21 of these pitchers returned the following season. All but two saw their strand rate fall below 80%, and the group saw its average strand rate fall from 85.2% to 76.7%).

Strikeouts could be one other area where we see Cueto regress.

This is far from a sure thing, as unlike strand rate and BABIP, strikeout rate tends to be fairly consistent. There are useful variations of expected strikeout rate, but you can often get away with using strikeout rate itself to predict future strikeouts, given its high self-correlation from year to year.

Still, I bring this up because Cueto came into 2014 with a career strikeout rate of 18.6% (7.0 K/9) yet posted a rate of 25.2% (8.9 K/9) last season, without a comparable uptick in the underlying metrics.

FanGraphsâ€™ Mike Podhorzer writes that Cueto outperformed his expected strikeout rate, given that a disproportionate amount of his strikes came via foul ball.

Cueto set a career high in strikeout rate, despite a looking-strike rate identical to his career average and a swinging-strike rate that marked a 1.5% decline from his 2013 average. His foul ball percentage, which Podhorzer notes is the least reliable of the three strike variations, was third-highest in the National League, according to Baseball-Reference.

By looking at expected strikeouts in a different way -- using swing-and-misses per swing (or "whiff rate") -- we reach a similar conclusion about Cueto and his strikeout rate. Beyond the Boxscore found that whiff rate explains 70% of the variance in strikeout rate and a 23% whiff rate should translate to about a 20% strikeout rate.

Cueto forced a swing-and-miss on 23.1% of his swings against (77th among starting pitchers), according to Baseball Prospectus, yet had an actual strikeout rate of 25.2%.

Finally, letâ€™s look at what the projection models expect from Cueto this year.

Projection Model IP ERA K/9 BB/9 WAR/WARP Steamer 182 3.30 8.59 2.41 2.7 ZiPS 181.1 2.88 8.09 2.28 4.8 PECOTA 194 3.02 7.7 2.3 2.9

Even though we should expect regression in a few areas, we are still talking about a very good pitcher, and the projections reflect this.

Just donâ€™t expect him to replicate his stellar 2014.