Big Spike in CF Plays in OOTP17

Buane · 08-23-2016, 01:55 PM

Howdy all. The following is a bit of a lengthy analysis of some defensive metrics and game tendencies in my OOTP league. I've tried to present everything as clearly and concisely as possible, even when those two endeavors have been in opposition. I apologize in advance if any of the below is not clear, or if any of the below is not concise.

I run a longtime OOTP online league - we've been in business since the OOTP9 days, and we're about to close the books on our first season running on OOTP17. Looking over our league numbers, I've been following a trend that's been obvious from the season's first few weeks - there has been a pretty sizable spike in plays involving CFers across the entire league.

Every individual CFer I looked at was making way, way more plays than they had in previous seasons. Even bad defenders with low range who were pressed into starting or temporary CF duty were getting to far more fly balls than previous numbers suggested they should or did. Stated plainly, centerfielders in OOTP17 are getting more balls hit to them than ever before in any version of OOTP.

So naturally I had a few questions. Was this a conscious decision? Did the new model better represent the balls-in-play distribution from the real MLB? If CFers were making more outs this season, what position was making fewer? Was this just somehow a setting or a change in my league, or was it universal?

Some of these questions I've answered myself, and for others I turn to the ootpdev forums.

Let me get an important caveat out of the way first: My league converted from OOTP15 to OOTP17, so we skipped OOTP16. This change COULD have been introduced in OOTP16 but I wouldn't have seen it. For what it's worth, I would guess it's an OOTP17 change though, otherwise it probably would have come to light before now.

Ok, on to the numbers. As you probably know we don't (yet) have wonderfully complex defensive metrics in OOTP. No statcast numbers telling us how much ground was covered, what a guy's first step was, his route efficiency, etc. That means I have a choice of some VERY imperfect statistics for this analysis. Primarily, I am using Total Chances. Believe me when I say I understand all the limitations of using Total Chances as a defensive stat and/or metric. Thankfully, for the main part of this analysis, Total Chances works as a point-prover since it is only being used as a year-over-year comparative, and can be seen to be very steady from year-to-year in both OOTP and the real MLB.

Ok, actually on to the numbers now. The current year in my league is 2045, so all the significant comparisons are going to be made against that year. For the 2044 season, our previous year, Center Fielders logged 34775 defensive innings, and accumulated 9292 total chances. This is a rate of 2.40 chances per 27 outs, or 2.4 chances per 9-inning game. So far so simple. In real-life MLB the average chances/27 for a CF is about 2.6, so the CF numbers from our LAST season seem pretty in-line with the real world.

However THIS season, our CFers logged a chance rate of 3.53 per 27 outs, almost a 50% jump from the previous season. I dug far into my league's history to see if maybe Total Chances was just subject to these kind of crazy swings. The answer was an emphatic "no":

These numbers show it clearly: there has never been a time in our league when so many balls were being hit to CF.

Now, you may notice the IP totals for this year are way up as well, compared to previous years. In the interest of full disclosure, this year we underwent some league expansion, giving the league additional teams and additional innings. Believe me, my first reaction was the same as your initial reaction is now: that expansion probably had something to do with this change.

So I dug a bit deeper into this year's numbers. League ERA, batting average, BABIP, every significant stat from this season was basically right in line with our previous seasons. So could expansion really have an impact on how many balls get hit to CF and nothing else? Even though that sounds unlikely, I still wanted to disprove it, so I loaded up my league backup from our initial import to OOTP17 - prior to the expansion - and ran a full season without adding any teams. Same league settings, same players, just with the same number of teams as last year. Here are the numbers I got from that alternate season:

So even with expansion completely removed from the equation, the chance rate was still extraordinarily high.

Ok, so what about real MLB? What about the CF chance rates there historically?

While the numbers from my league don't match up perfectly with the MLB numbers (and I'm not expecting them too of course - plenty of league factors can account for these slight differences), you can see the MLB numbers are as steady as my RSL numbers were until this year. As flawed as Total Chances may be as an evaluative metric, this is clearly a number that doesn't fluctuate very much from one season to the next.

If you have a league that has spanned OOTP versions, you can check these numbers yourself. Just export the players_career_fielding_stats.csv file and interrogate the year/league/position totals in excel. Since I changed literally none of my league's settings from last season to this season, I would imagine you will see a similar jump in your leagues as well. I would be very curious to see the numbers from some other leagues out there.

So, that concludes part one of my analysis. I think this reasonably proves there is a change in OOTP17 (or 16) that affected balls in play. What about the other positions on the field though? If more outs are being converted by CFers now, what position is converting fewer? I'm glad you asked! I did this same analysis for the rest of the positions on the field.

Let's start with the rest of the outfield. Here are the LF/RF numbers:

You can see a slight uptick in our LF and RF chances, meaning OF chances are up across the board this year (though obviously not nearly as much as they are in CF). This is a slight change, but not too significant.

Ok, here are the infield positions minus 1B (more on 1B later...):

So my first big surprise was seen here. Despite the CF numbers being up significantly, the IF numbers haven't dropped that much. I was expecting more balls to the outfield to equal fewer balls on the infield. Now, there's a slight drop off at 2B/SS/3B from where we were in previous seasons, but not a ton. And certainly not enough to make up the difference.

At this point I got to thinking that since infield outs weren't down very much, maybe strikeouts had dropped a lot? In theory, fewer strikeouts could potentially cause more balls hit to CF? I guess. Here are strikeouts league-wide, as well as pitcher defensive plays for the hell of it.

Pitcher plays remain steady, and strikeout numbers ticked down very, very slightly - this is likely the only effect of the expansion I mentioned earlier. But you can see there's no big change at all. Strikeouts are a dead end.

That leaves us with two remaining positions: catcher and first base. Unfortunately for us...catcher and first base are the two defensive positions where Total Chances is a real mess of a metric. Catcher Total Chances includes pitcher strikeouts, and 1B Total Chances includes, well, every ball another infielder throws to them. So we need to use a bit of creative license to get our comparative numbers.

For catchers, we really just need to remove strikeouts from their Chances totals. That gives us numbers that look like this:

So, no real change there, either. Leaving us with the real 1B conundrum.

See, Total Chances for first basemen contains a ton of noise, because they're involved in so many plays on balls NOT hit to them. There is noise in the Total Chances number for all positions, true (for example, on a ball hit to SS where the fielder flips to 2B for the force, both players get credit for the "chance") but I have been comfortable up to this point ignoring that noise. For the other infield positions, the vast majority of their chances do not involve one and other. But that is not true for 1B - the vast, vast, vast majority of plays a 1B is involved in are not on balls hit to them, but rather thrown to them.

So to get a workable Total Chances number, I've decided to subtract 3B, 2B, and SS assists from the 1B total chances number. Now, obviously, some 3B/SS/3B assists are not on throws to 1B. Obviously, this is NOT an accurate representation of the actual number of balls hit to first base, but it will serve us as a decent rough estimate. Again, what is more important in this study is how these totals have changed from year to year - indicating a change in the balls-in-play engine - and not necessarily with determining the precise number of balls hit to a fielder. For that, we would need a much more surgical way of extracting balls-in-play data.

So, with all that said, here's the 1B totals:

Whoops. Looks like we found those missing outs. This year, there are almost NO balls being hit to first base at all. Or, at least, no balls that first basemen are making plays on. Compared to previous seasons, when our numbers were very much similar to those of the real world, this seems to be a huge change, and almost singlehandedly makes up the difference in the spike of CF plays.

So to sum up:

In OOTP17, at least compared to OOTP15, there is a rather sizable change in the number of balls hit to & played by first basemen, and balls hit to & played by center fielders. This would appear to be either a conscious design change, or a mistake/bug.

If this was a conscious design change, then the question is obvious. Why change something when the previous results were very much in line with the real world numbers?

If this was a mistake or a bug, then let's fix it!

I'm happy to provide any more data anybody would be interested in, and would be very interested to see some of the totals people are seeing in their leagues! While I think my data is comprehensive, in the end, this is only a study of one league...

Spritze · 08-23-2016, 02:08 PM

This issue has been noted and fixed (for CF anyway), probably in the maintenance patch but in OOTP18 for sure. The CF challenge has been around unnoticed for 5 or 6 years.

The 1B challenge will be investigated by the investigators who investigate things that need to be investigated. I'd put that part under the bug reports thread if you can.

Matt Arnold · 08-23-2016, 02:16 PM

The CF chances was pointed out in the beta boards shortly after the last patch, and will be fixed/tweaked for the next patch. Essentially, our flyball landing locations were wrong, and thus too many balls were going to CF. I updated the landing locations and the numbers line up much better now.

The 1B numbers are odd. I'm not sure what could be causing that.

BoomerSoonerAMH · 08-25-2016, 03:52 PM

The first thing that comes to mind after reviewing all of the data is that the fly ball to ground ball ratio might be off kilter, as well as the number of ground ball double plays.

If the OP could look at and post that data, I'd love to see if that enlightens us at all. I can go into detail as to why I think these issues could be contributing to the problem, but I'll save us all a lengthy post if the data refutes my line of thinking.

JMDurron · 08-26-2016, 09:40 AM

Quote:

Originally Posted by BoomerSoonerAMH

The first thing that comes to mind after reviewing all of the data is that the fly ball to ground ball ratio might be off kilter, as well as the number of ground ball double plays.

If the OP could look at and post that data, I'd love to see if that enlightens us at all. I can go into detail as to why I think these issues could be contributing to the problem, but I'll save us all a lengthy post if the data refutes my line of thinking.

Yeah, I'm wondering about the above as well. Even though the CF and 1B positions were outliers, there was still a noticeable uptick in both LF and RF, with a noticeable reduction in chances for all of 3B, SS, and 2B. That would seem to imply an issue with flyball vs groundball ratios.

JMDurron · 08-26-2016, 10:11 AM

Looking at the last 7 years (including ongoing current season, in Aug) of my MLB Quickstart League, with only the current season in OOTP17, I'm seeing the same behavior.

Note on methodology - I was a tad lazier than the OP, and did not subtract the assists by 2B, SS, and 3B from the 1B totals. I'm concerned that GB totals in general may be getting depressed here, so I actually would like to see the overall impact on TC for 1B on the broader scale anyway.

My league is currently in 2026, started in 2012. I used 2020-2026 as my dataset. Comparing the 2020-2025 AVG (labeled as "Pre-17") to 2026 ("17") actuals, with no league setting changes heading into 2026, based on C/27o as defined above.

Position - Pre-17 - 17

1B - 9.42 - 8.31
2B - 4.74 - 4.62
3B - 2.47 - 2.44
SS - 4.30 - 4.16
LF - 2.05 - 2.28
CF - 2.43 - 3.65
RF - 1.82 - 2.01

We seem to have a consensus on CF, but there's a visually notable change in 3 out of 4 IF positions downward, and in all 3 OF positions upward. My league's overall talent level has not significantly changed from 2025 to 2026. If anything, the number of stud pitchers (frequently GB type) has gradually increased over time, so it doesn't track to me that the overall GB/FB rate would be decreasing.

JMDurron · 08-26-2016, 10:29 AM

I followed-up by digging into the career pitching stats CSV file and taking a look at GB and FB totals at the MLB level. I took a straight GB/FB stat to get the ratio

2020-2025 average - 1.125
2026 - 0.943

The CFs may be getting a disproportionate amount of the FBs in general, but my thinking is that the underlying culprit still requiring analysis is the overall shift in GB/FB ratio.

If the OP wouldn't mind looking at the same stats in his leagues, I'd appreciate it. I'm open to doing additional analysis/screenshots/uploading league files to OOTPD if so desired.

Matt Arnold · 08-26-2016, 10:46 AM

I know when I was looking at stuff, I was trying to get the rates accurate to MLB, so it's possible the old rates were wrong (don't always assume what used to happen was correct!). I know for sure that we used to have too many popups, and I think I adjusted a few of the other stats to get rates that more closely matched real life.

Roughly speaking, in MLB right now, LD are around 20%, GB are around 45%, and FB are around 35%, of which 10% are infield fly's. Keep in mind I believe we report slightly differently than you will often see on other sites (whether LD or IFFB are reported within the FB stats or not).

If you do want to change, you can adjust the groundball percentage in your league stats settings. However I believe the default setting should be close to the real life stats.

BoomerSoonerAMH · 08-26-2016, 10:58 AM

Quote:

Originally Posted by JMDurron

I followed-up by digging into the career pitching stats CSV file and taking a look at GB and FB totals at the MLB level. I took a straight GB/FB stat to get the ratio

2020-2025 average - 1.125
2026 - 0.943

The CFs may be getting a disproportionate amount of the FBs in general, but my thinking is that the underlying culprit still requiring analysis is the overall shift in GB/FB ratio.

If the OP wouldn't mind looking at the same stats in his leagues, I'd appreciate it. I'm open to doing additional analysis/screenshots/uploading league files to OOTPD if so desired.

This supports my concern about GB/FB ratio, but what about the number of DPs? I'd look at it myself, but I don't have any pre-17 data to use as a baseline data set.

The reason the number of DPs interests me is that 1B typically only gets one chance on a DP, where as the other two players involved get a combined 3 chances in this situation. That could explain why 1B saw the most substantial decrease in total chances.

In summary, my theory (based on the data presented) is that the GB/FB ratio has shifted in favor of more FBs (supported by your data) and that more double plays are being turned on the ground balls that are hit. My gut is telling me that the decrease in total chances across the infield would be more evenly distributed (or at least proportionally) between all infield positions, unless there is another factor at play. The only factor I can come up with that would have a significant impact is the number of double plays has increased.

BoomerSoonerAMH · 08-26-2016, 11:11 AM

Quote:

Originally Posted by Matt Arnold

I know when I was looking at stuff, I was trying to get the rates accurate to MLB, so it's possible the old rates were wrong (don't always assume what used to happen was correct!). I know for sure that we used to have too many popups, and I think I adjusted a few of the other stats to get rates that more closely matched real life.

Roughly speaking, in MLB right now, LD are around 20%, GB are around 45%, and FB are around 35%, of which 10% are infield fly's. Keep in mind I believe we report slightly differently than you will often see on other sites (whether LD or IFFB are reported within the FB stats or not).

If you do want to change, you can adjust the groundball percentage in your league stats settings. However I believe the default setting should be close to the real life stats.

Good point Matt...of course that is why you made it. My analysis is only considering the data presented in an attempt to explain the difference. I'll go back and look at MLB data on total chances from this year and the past couple of years so we can compare apples to apples.

Rain King · 08-26-2016, 12:16 PM

As someone in an online league still using 16, do we know when this issue was introduced?

Hoiles · 08-26-2016, 12:33 PM

Good catch... I guess this partly explains why my starting CF gets injured every year (all the extra plays handled)

BoomerSoonerAMH · 08-26-2016, 01:29 PM

MLB Data for 2016 (YTD), 2015 and 2014

2016 (YTD)
TC/27outs
P - 1.59
C - 8.69
1B - 9.13
2B - 4.64
3B - 2.71
SS - 4.33
RF - 2.09
CF - 2.46
LF - 1.86
OF combined - 6.41

GO:AO ratio (Ground ball outs to Air ball outs) - 1.09

Balls in play GB:FB ratio (all batted balls) - 1.30
GB% (all batted balls) - 44.9%
FB% (all batted balls) - 34.4%
LD% (all batted balls) - 20.7%

IFFB% (all batted balls) - 9.6%
HR% of FB (HRs/FBs) - 12.9%

Double Plays - 2207

2015
TC/27outs
P - 1.69
C - 8.43
1B - 9.26
2B - 4.76
3B - 2.67
SS - 4.41
RF - 2.05
CF - 2.57
LF - 1.88
OF combined - 6.50

GO:AO ratio (Ground ball outs to Air ball outs) - 1.10

Balls in play GB:FB ratio (all batted balls) - 1.34
GB% (all batted balls) - 45.3%
FB% (all batted balls) - 33.8%
LD% (all batted balls) - 20.9%

IFFB% (all batted balls) - 9.5%
HR% of FB (HRs/FBs) - 11.4%

Double Plays - 2810

2014
TC/27outs
P - 1.67
C - 8.39
1B - 9.20
2B - 4.72
3B - 2.65
SS - 4.25
RF - 2.10
CF - 2.62
LF - 1.94
OF combined - 6.66

GO:AO ratio (Ground ball outs to Air ball outs) - 1.07

Balls in play GB:FB ratio (all batted balls) - 1.30
GB% (all batted balls) - 44.8 %
FB% (all batted balls) - 34.4%
LD% (all batted balls) - 20.8%

IFFB% (all batted balls) - 9.6%
HR% of FB (HRs/FBs) - 9.5%

Double Plays - 2648

GoodOlKevin · 08-26-2016, 01:36 PM

Do you people even have fun playing this game? How can you with posts like this?

JMDurron · 08-26-2016, 02:22 PM

Quote:

Originally Posted by Matt Arnold

I know when I was looking at stuff, I was trying to get the rates accurate to MLB, so it's possible the old rates were wrong (don't always assume what used to happen was correct!). I know for sure that we used to have too many popups, and I think I adjusted a few of the other stats to get rates that more closely matched real life.

Roughly speaking, in MLB right now, LD are around 20%, GB are around 45%, and FB are around 35%, of which 10% are infield fly's. Keep in mind I believe we report slightly differently than you will often see on other sites (whether LD or IFFB are reported within the FB stats or not).

If you do want to change, you can adjust the groundball percentage in your league stats settings. However I believe the default setting should be close to the real life stats.

Matt, thanks for the response. Can you provide any insight into how OOTP's stats should or should not translate compared to the MLB GO/AO rate posted in BoomerSoonerAMH's post? I ask because his rate data sure seems to line up well with the average of 1.125 for my league from previous versions of OOTP, which makes it *look* like OOTP17 is the problem here, not the old data. I don't know how we can determine that without insight into what your GB/FB stats mean in comparison to the MLB figures posted in this thread for comparison.

Quote:

Originally Posted by BoomerSoonerAMH

MLB Data for 2016 (YTD), 2015 and 2014

2016 (YTD)
TC/27outs
P - 1.59
C - 8.69
1B - 9.13
2B - 4.64
3B - 2.71
SS - 4.33
RF - 2.09
CF - 2.46
LF - 1.86
OF combined - 6.41

GO:AO ratio (Ground ball outs to Air ball outs) - 1.09

Balls in play GB:FB ratio (all batted balls) - 1.30
GB% (all batted balls) - 44.9%
FB% (all batted balls) - 34.4%
LD% (all batted balls) - 20.7%

IFFB% (all batted balls) - 9.6%
HR% of FB (HRs/FBs) - 12.9%

Double Plays - 2207

2015
TC/27outs
P - 1.69
C - 8.43
1B - 9.26
2B - 4.76
3B - 2.67
SS - 4.41
RF - 2.05
CF - 2.57
LF - 1.88
OF combined - 6.50

GO:AO ratio (Ground ball outs to Air ball outs) - 1.10

Balls in play GB:FB ratio (all batted balls) - 1.34
GB% (all batted balls) - 45.3%
FB% (all batted balls) - 33.8%
LD% (all batted balls) - 20.9%

IFFB% (all batted balls) - 9.5%
HR% of FB (HRs/FBs) - 11.4%

Double Plays - 2810

2014
TC/27outs
P - 1.67
C - 8.39
1B - 9.20
2B - 4.72
3B - 2.65
SS - 4.25
RF - 2.10
CF - 2.62
LF - 1.94
OF combined - 6.66

GO:AO ratio (Ground ball outs to Air ball outs) - 1.07

Balls in play GB:FB ratio (all batted balls) - 1.30
GB% (all batted balls) - 44.8 %
FB% (all batted balls) - 34.4%
LD% (all batted balls) - 20.8%

IFFB% (all batted balls) - 9.6%
HR% of FB (HRs/FBs) - 9.5%

Double Plays - 2648

Thanks for posting this. Matt's post implies that the GB/FB or GO/AO ratio from MLB might not be a direct comparison to OOTP's info, so I'm not sure how to proceed with that information. The comparison to the TC data from the pre-OOTP17 averages sure looks to align better with the MLB data to my eye, though.

BoomerSoonerAMH · 08-26-2016, 02:41 PM

I agree that we need Matt to verify how the stats from OOTP compare to the MLB data. I think we can all agree something changed from OOTP 16 to OOTP 17. Now we have to determine if it was to align more closely to MLB data or if we got farther away from it. I tried to provide as much info as I could from the past 2 years plus this year so that we could determine what we should be comparing to answer this question.

JMDurron · 08-26-2016, 02:47 PM

Just to clarify to anybody asking if this wall of data really "matters", here's why I think it does, *if* there is really an underlying game engine issue here.

I, personally, am fine with unrealistic outcomes, but only within certain parameters. My parameters are my own and won't match everyone else's, hence "it's your game, play it your way." Those parameters include having an outlandishly good team dominating the league, but doing so by assembling an unrealistically talented roster that combines to be unrealistically good at the baseball-related skills that impact their play on the field *in a realistic way*.

For example, I prioritized getting my top hitting 2B and SS prospects who were *also* stud defenders onto my MLB roster, and traded away slightly better-hitting, but less fielding-capable alternative prospects. I do so based upon the assumption (and previous OOTP outcomes to that effect) that the axiom of "strong defense up the middle is key to run prevention, and enhances whatever pitcher talent level you happen to have" applied in my OOTP universe. The shift in GB/FB within OOTP17 appears to have somewhat negated the impact of that decision, unrealistically in comparison to the actual MLB outcomes posted by BoomerSooner above.

I happen to have two excellent hitting 1B, but one is about 40% better at hitting, but 90% worse defensively than the one I chose to be the starter in 2026. I happened to do this in the offseason prior to my first season in OOTP17 in this league, and now I see that I weighed that decision incorrectly based on how 1B are actually getting far fewer chances than the position as a whole realistically does in MLB, and used to in previous OOTP versions.

I had to make a decision in my 2025-2026 offseason between keeping an excellent stud DH nearing 300 career HRs all on my team, and my stud defensive CF who is merely very good offensively against RHP, for a CFer. I decided to keep the CFer instead of going with a more offensively-focused OF, and in hindsight, boy am I glad I did so, between the GB/FB shift and the identified issue with excessive CF chances that will be addressed by OOTPD.

This isn't a game breaker by any means, because as Matt pointed out, I can adjust the GB/FB ratio on my own. It does, however, matter when it comes to how play-by-play outcomes are determined, which matters when it comes to how I should focus resources and preferences when constructing my roster, which is a huge proportion of what makes OOTP fun for me.

So, yes, while playing around with PivotTables in Excel isn't my idea of a roaring good time on a Friday morning, I do happen to have loads of fun playing OOTP17, this is all about helping to keep an awesomely responsive developer aware of a potential issue that might have a negative impact on my enjoyment, and the enjoyment of others.

NoOne · 08-26-2016, 03:29 PM

Quote:

Originally Posted by GoodOlKevin

Do you people even have fun playing this game? How can you with posts like this?

intelligence has a weak inverse correlation to happiness. ignorance truly is bliss, as they say.

in a general sense: i am happy to analyze just about anything. i use my brain to improve on what i and others have already learned.

analyzing the video game, i will understand the probability of various choices and make better decisions, therefore i will win more. winning is fun.

some people have a perception of what baseball is and regardless of RL or the paramaters of the video game, they are going to force that square peg through a round hole no matter what.... i wouldn't enjoy playing like that, but i understand that it's possible others do.

when this is worked out, understanding it will allow you to win more in the video game... sounds fun right? if you do this for many aspects of the game you can be as good as anyone when making a decision. you will literally make the "best" decision all of the time. difficult in RL, but easy in a video game.

PS - this thread is interesting and thank you for the information.

NoOne · 08-26-2016, 03:37 PM

back on topic:

averages are a start... but distribution and volatility are required to give a real comparison... and definitely not based on small samples, like the ones above.

batted ball stats are a %$#@. good luck with that stuff. one website i go to only has info for the last 10-12 years or so. then, you have the problem of conflicting definitions of what a line drive / fly ball is, etc... at this moment in time the data is a bit murky and difficult to use in a precise way. i.e. you can get 2 data sets from the same period of time in the MLB and get 2 completely different results. so, what kind of integrity is there at the moment? not much.

Barkingturtle · 08-26-2016, 04:19 PM

I just suffered through an August swoon wherein I lost three center-fielders and two of each right and left-fielders for the majority of the month. That's seven injured outfielders, all sitting in the jacuzzi at once. I lost sixteen games in a row, a new personal worst. I fell from contention like seven outfielders leaping from a plane without parachutes. I'm going to blame OOTP's injury engine combined with the data in this thread. It is some small consolation.

08-23-2016, 01:55 PM	#1
Buane Minors (Double A) Join Date: Mar 2006 Posts: 163	Big Spike in CF Plays in OOTP17 Howdy all. The following is a bit of a lengthy analysis of some defensive metrics and game tendencies in my OOTP league. I've tried to present everything as clearly and concisely as possible, even when those two endeavors have been in opposition. I apologize in advance if any of the below is not clear, or if any of the below is not concise. I run a longtime OOTP online league - we've been in business since the OOTP9 days, and we're about to close the books on our first season running on OOTP17. Looking over our league numbers, I've been following a trend that's been obvious from the season's first few weeks - there has been a pretty sizable spike in plays involving CFers across the entire league. Every individual CFer I looked at was making way, way more plays than they had in previous seasons. Even bad defenders with low range who were pressed into starting or temporary CF duty were getting to far more fly balls than previous numbers suggested they should or did. Stated plainly, centerfielders in OOTP17 are getting more balls hit to them than ever before in any version of OOTP. So naturally I had a few questions. Was this a conscious decision? Did the new model better represent the balls-in-play distribution from the real MLB? If CFers were making more outs this season, what position was making fewer? Was this just somehow a setting or a change in my league, or was it universal? Some of these questions I've answered myself, and for others I turn to the ootpdev forums. Let me get an important caveat out of the way first: My league converted from OOTP15 to OOTP17, so we skipped OOTP16. This change COULD have been introduced in OOTP16 but I wouldn't have seen it. For what it's worth, I would guess it's an OOTP17 change though, otherwise it probably would have come to light before now. Ok, on to the numbers. As you probably know we don't (yet) have wonderfully complex defensive metrics in OOTP. No statcast numbers telling us how much ground was covered, what a guy's first step was, his route efficiency, etc. That means I have a choice of some VERY imperfect statistics for this analysis. Primarily, I am using Total Chances. Believe me when I say I understand all the limitations of using Total Chances as a defensive stat and/or metric. Thankfully, for the main part of this analysis, Total Chances works as a point-prover since it is only being used as a year-over-year comparative, and can be seen to be very steady from year-to-year in both OOTP and the real MLB. Ok, actually on to the numbers now. The current year in my league is 2045, so all the significant comparisons are going to be made against that year. For the 2044 season, our previous year, Center Fielders logged 34775 defensive innings, and accumulated 9292 total chances. This is a rate of 2.40 chances per 27 outs, or 2.4 chances per 9-inning game. So far so simple. In real-life MLB the average chances/27 for a CF is about 2.6, so the CF numbers from our LAST season seem pretty in-line with the real world. However THIS season, our CFers logged a chance rate of 3.53 per 27 outs, almost a 50% jump from the previous season. I dug far into my league's history to see if maybe Total Chances was just subject to these kind of crazy swings. The answer was an emphatic "no": These numbers show it clearly: there has never been a time in our league when so many balls were being hit to CF. Now, you may notice the IP totals for this year are way up as well, compared to previous years. In the interest of full disclosure, this year we underwent some league expansion, giving the league additional teams and additional innings. Believe me, my first reaction was the same as your initial reaction is now: that expansion probably had something to do with this change. So I dug a bit deeper into this year's numbers. League ERA, batting average, BABIP, every significant stat from this season was basically right in line with our previous seasons. So could expansion really have an impact on how many balls get hit to CF and nothing else? Even though that sounds unlikely, I still wanted to disprove it, so I loaded up my league backup from our initial import to OOTP17 - prior to the expansion - and ran a full season without adding any teams. Same league settings, same players, just with the same number of teams as last year. Here are the numbers I got from that alternate season: So even with expansion completely removed from the equation, the chance rate was still extraordinarily high. Ok, so what about real MLB? What about the CF chance rates there historically? While the numbers from my league don't match up perfectly with the MLB numbers (and I'm not expecting them too of course - plenty of league factors can account for these slight differences), you can see the MLB numbers are as steady as my RSL numbers were until this year. As flawed as Total Chances may be as an evaluative metric, this is clearly a number that doesn't fluctuate very much from one season to the next. If you have a league that has spanned OOTP versions, you can check these numbers yourself. Just export the players_career_fielding_stats.csv file and interrogate the year/league/position totals in excel. Since I changed literally none of my league's settings from last season to this season, I would imagine you will see a similar jump in your leagues as well. I would be very curious to see the numbers from some other leagues out there. So, that concludes part one of my analysis. I think this reasonably proves there is a change in OOTP17 (or 16) that affected balls in play. What about the other positions on the field though? If more outs are being converted by CFers now, what position is converting fewer? I'm glad you asked! I did this same analysis for the rest of the positions on the field. Let's start with the rest of the outfield. Here are the LF/RF numbers: You can see a slight uptick in our LF and RF chances, meaning OF chances are up across the board this year (though obviously not nearly as much as they are in CF). This is a slight change, but not too significant. Ok, here are the infield positions minus 1B (more on 1B later...): So my first big surprise was seen here. Despite the CF numbers being up significantly, the IF numbers haven't dropped that much. I was expecting more balls to the outfield to equal fewer balls on the infield. Now, there's a slight drop off at 2B/SS/3B from where we were in previous seasons, but not a ton. And certainly not enough to make up the difference. At this point I got to thinking that since infield outs weren't down very much, maybe strikeouts had dropped a lot? In theory, fewer strikeouts could potentially cause more balls hit to CF? I guess. Here are strikeouts league-wide, as well as pitcher defensive plays for the hell of it. Pitcher plays remain steady, and strikeout numbers ticked down very, very slightly - this is likely the only effect of the expansion I mentioned earlier. But you can see there's no big change at all. Strikeouts are a dead end. That leaves us with two remaining positions: catcher and first base. Unfortunately for us...catcher and first base are the two defensive positions where Total Chances is a real mess of a metric. Catcher Total Chances includes pitcher strikeouts, and 1B Total Chances includes, well, every ball another infielder throws to them. So we need to use a bit of creative license to get our comparative numbers. For catchers, we really just need to remove strikeouts from their Chances totals. That gives us numbers that look like this: So, no real change there, either. Leaving us with the real 1B conundrum. See, Total Chances for first basemen contains a ton of noise, because they're involved in so many plays on balls NOT hit to them. There is noise in the Total Chances number for all positions, true (for example, on a ball hit to SS where the fielder flips to 2B for the force, both players get credit for the "chance") but I have been comfortable up to this point ignoring that noise. For the other infield positions, the vast majority of their chances do not involve one and other. But that is not true for 1B - the vast, vast, vast majority of plays a 1B is involved in are not on balls hit to them, but rather thrown to them. So to get a workable Total Chances number, I've decided to subtract 3B, 2B, and SS assists from the 1B total chances number. Now, obviously, some 3B/SS/3B assists are not on throws to 1B. Obviously, this is NOT an accurate representation of the actual number of balls hit to first base, but it will serve us as a decent rough estimate. Again, what is more important in this study is how these totals have changed from year to year - indicating a change in the balls-in-play engine - and not necessarily with determining the precise number of balls hit to a fielder. For that, we would need a much more surgical way of extracting balls-in-play data. So, with all that said, here's the 1B totals: Whoops. Looks like we found those missing outs. This year, there are almost NO balls being hit to first base at all. Or, at least, no balls that first basemen are making plays on. Compared to previous seasons, when our numbers were very much similar to those of the real world, this seems to be a huge change, and almost singlehandedly makes up the difference in the spike of CF plays. So to sum up: In OOTP17, at least compared to OOTP15, there is a rather sizable change in the number of balls hit to & played by first basemen, and balls hit to & played by center fielders. This would appear to be either a conscious design change, or a mistake/bug. If this was a conscious design change, then the question is obvious. Why change something when the previous results were very much in line with the real world numbers? If this was a mistake or a bug, then let's fix it! I'm happy to provide any more data anybody would be interested in, and would be very interested to see some of the totals people are seeing in their leagues! While I think my data is comprehensive, in the end, this is only a study of one league... __________________ Commissioner - Rising Star League Congratulations to the 2060 Champion Buffalo Rangers!

08-23-2016, 02:08 PM	#2
Spritze OOTP Historical Czar Join Date: Dec 2001 Location: Bothell Wa Posts: 7,254	This issue has been noted and fixed (for CF anyway), probably in the maintenance patch but in OOTP18 for sure. The CF challenge has been around unnoticed for 5 or 6 years. The 1B challenge will be investigated by the investigators who investigate things that need to be investigated. I'd put that part under the bug reports thread if you can. __________________ It's madness, madness, I tell you! For the love of God, don't do it!

08-26-2016, 02:47 PM	#17
JMDurron All Star Starter Join Date: Mar 2011 Posts: 1,262	Just to clarify to anybody asking if this wall of data really "matters", here's why I think it does, if there is really an underlying game engine issue here. I, personally, am fine with unrealistic outcomes, but only within certain parameters. My parameters are my own and won't match everyone else's, hence "it's your game, play it your way." Those parameters include having an outlandishly good team dominating the league, but doing so by assembling an unrealistically talented roster that combines to be unrealistically good at the baseball-related skills that impact their play on the field in a realistic way. For example, I prioritized getting my top hitting 2B and SS prospects who were also stud defenders onto my MLB roster, and traded away slightly better-hitting, but less fielding-capable alternative prospects. I do so based upon the assumption (and previous OOTP outcomes to that effect) that the axiom of "strong defense up the middle is key to run prevention, and enhances whatever pitcher talent level you happen to have" applied in my OOTP universe. The shift in GB/FB within OOTP17 appears to have somewhat negated the impact of that decision, unrealistically in comparison to the actual MLB outcomes posted by BoomerSooner above. I happen to have two excellent hitting 1B, but one is about 40% better at hitting, but 90% worse defensively than the one I chose to be the starter in 2026. I happened to do this in the offseason prior to my first season in OOTP17 in this league, and now I see that I weighed that decision incorrectly based on how 1B are actually getting far fewer chances than the position as a whole realistically does in MLB, and used to in previous OOTP versions. I had to make a decision in my 2025-2026 offseason between keeping an excellent stud DH nearing 300 career HRs all on my team, and my stud defensive CF who is merely very good offensively against RHP, for a CFer. I decided to keep the CFer instead of going with a more offensively-focused OF, and in hindsight, boy am I glad I did so, between the GB/FB shift and the identified issue with excessive CF chances that will be addressed by OOTPD. This isn't a game breaker by any means, because as Matt pointed out, I can adjust the GB/FB ratio on my own. It does, however, matter when it comes to how play-by-play outcomes are determined, which matters when it comes to how I should focus resources and preferences when constructing my roster, which is a huge proportion of what makes OOTP fun for me. So, yes, while playing around with PivotTables in Excel isn't my idea of a roaring good time on a Friday morning, I do happen to have loads of fun playing OOTP17, this is all about helping to keep an awesomely responsive developer aware of a potential issue that might have a negative impact on my enjoyment, and the enjoyment of others. Last edited by JMDurron; 08-26-2016 at 02:48 PM.

08-23-2016, 02:16 PM	#3
Matt Arnold OOTP Developer Join Date: Jun 2009 Location: Here and there Posts: 14,111	The CF chances was pointed out in the beta boards shortly after the last patch, and will be fixed/tweaked for the next patch. Essentially, our flyball landing locations were wrong, and thus too many balls were going to CF. I updated the landing locations and the numbers line up much better now. The 1B numbers are odd. I'm not sure what could be causing that.

08-25-2016, 03:52 PM	#4
BoomerSoonerAMH Minors (Double A) Join Date: Mar 2015 Posts: 111	The first thing that comes to mind after reviewing all of the data is that the fly ball to ground ball ratio might be off kilter, as well as the number of ground ball double plays. If the OP could look at and post that data, I'd love to see if that enlightens us at all. I can go into detail as to why I think these issues could be contributing to the problem, but I'll save us all a lengthy post if the data refutes my line of thinking.

08-26-2016, 10:11 AM	#6
JMDurron All Star Starter Join Date: Mar 2011 Posts: 1,262	Looking at the last 7 years (including ongoing current season, in Aug) of my MLB Quickstart League, with only the current season in OOTP17, I'm seeing the same behavior. Note on methodology - I was a tad lazier than the OP, and did not subtract the assists by 2B, SS, and 3B from the 1B totals. I'm concerned that GB totals in general may be getting depressed here, so I actually would like to see the overall impact on TC for 1B on the broader scale anyway. My league is currently in 2026, started in 2012. I used 2020-2026 as my dataset. Comparing the 2020-2025 AVG (labeled as "Pre-17") to 2026 ("17") actuals, with no league setting changes heading into 2026, based on C/27o as defined above. Position - Pre-17 - 17 1B - 9.42 - 8.31 2B - 4.74 - 4.62 3B - 2.47 - 2.44 SS - 4.30 - 4.16 LF - 2.05 - 2.28 CF - 2.43 - 3.65 RF - 1.82 - 2.01 We seem to have a consensus on CF, but there's a visually notable change in 3 out of 4 IF positions downward, and in all 3 OF positions upward. My league's overall talent level has not significantly changed from 2025 to 2026. If anything, the number of stud pitchers (frequently GB type) has gradually increased over time, so it doesn't track to me that the overall GB/FB rate would be decreasing.

08-26-2016, 10:29 AM	#7
JMDurron All Star Starter Join Date: Mar 2011 Posts: 1,262	I followed-up by digging into the career pitching stats CSV file and taking a look at GB and FB totals at the MLB level. I took a straight GB/FB stat to get the ratio 2020-2025 average - 1.125 2026 - 0.943 The CFs may be getting a disproportionate amount of the FBs in general, but my thinking is that the underlying culprit still requiring analysis is the overall shift in GB/FB ratio. If the OP wouldn't mind looking at the same stats in his leagues, I'd appreciate it. I'm open to doing additional analysis/screenshots/uploading league files to OOTPD if so desired.

08-26-2016, 10:46 AM	#8
Matt Arnold OOTP Developer Join Date: Jun 2009 Location: Here and there Posts: 14,111	I know when I was looking at stuff, I was trying to get the rates accurate to MLB, so it's possible the old rates were wrong (don't always assume what used to happen was correct!). I know for sure that we used to have too many popups, and I think I adjusted a few of the other stats to get rates that more closely matched real life. Roughly speaking, in MLB right now, LD are around 20%, GB are around 45%, and FB are around 35%, of which 10% are infield fly's. Keep in mind I believe we report slightly differently than you will often see on other sites (whether LD or IFFB are reported within the FB stats or not). If you do want to change, you can adjust the groundball percentage in your league stats settings. However I believe the default setting should be close to the real life stats.

08-26-2016, 12:16 PM	#11
Rain King Hall Of Famer Join Date: Nov 2005 Posts: 2,108	As someone in an online league still using 16, do we know when this issue was introduced?

08-26-2016, 12:33 PM	#12
Hoiles All Star Reserve Join Date: Dec 2001 Location: Canada Posts: 572	Good catch... I guess this partly explains why my starting CF gets injured every year (all the extra plays handled)

08-26-2016, 01:29 PM	#13
BoomerSoonerAMH Minors (Double A) Join Date: Mar 2015 Posts: 111	MLB Data for 2016 (YTD), 2015 and 2014 2016 (YTD) TC/27outs P - 1.59 C - 8.69 1B - 9.13 2B - 4.64 3B - 2.71 SS - 4.33 RF - 2.09 CF - 2.46 LF - 1.86 OF combined - 6.41 GO:AO ratio (Ground ball outs to Air ball outs) - 1.09 Balls in play GB:FB ratio (all batted balls) - 1.30 GB% (all batted balls) - 44.9% FB% (all batted balls) - 34.4% LD% (all batted balls) - 20.7% IFFB% (all batted balls) - 9.6% HR% of FB (HRs/FBs) - 12.9% Double Plays - 2207 2015 TC/27outs P - 1.69 C - 8.43 1B - 9.26 2B - 4.76 3B - 2.67 SS - 4.41 RF - 2.05 CF - 2.57 LF - 1.88 OF combined - 6.50 GO:AO ratio (Ground ball outs to Air ball outs) - 1.10 Balls in play GB:FB ratio (all batted balls) - 1.34 GB% (all batted balls) - 45.3% FB% (all batted balls) - 33.8% LD% (all batted balls) - 20.9% IFFB% (all batted balls) - 9.5% HR% of FB (HRs/FBs) - 11.4% Double Plays - 2810 2014 TC/27outs P - 1.67 C - 8.39 1B - 9.20 2B - 4.72 3B - 2.65 SS - 4.25 RF - 2.10 CF - 2.62 LF - 1.94 OF combined - 6.66 GO:AO ratio (Ground ball outs to Air ball outs) - 1.07 Balls in play GB:FB ratio (all batted balls) - 1.30 GB% (all batted balls) - 44.8 % FB% (all batted balls) - 34.4% LD% (all batted balls) - 20.8% IFFB% (all batted balls) - 9.6% HR% of FB (HRs/FBs) - 9.5% Double Plays - 2648

08-26-2016, 01:36 PM	#14
GoodOlKevin Minors (Single A) Join Date: Oct 2011 Posts: 63	Do you people even have fun playing this game? How can you with posts like this?

08-26-2016, 02:41 PM	#16
BoomerSoonerAMH Minors (Double A) Join Date: Mar 2015 Posts: 111	I agree that we need Matt to verify how the stats from OOTP compare to the MLB data. I think we can all agree something changed from OOTP 16 to OOTP 17. Now we have to determine if it was to align more closely to MLB data or if we got farther away from it. I tried to provide as much info as I could from the past 2 years plus this year so that we could determine what we should be comparing to answer this question.

08-26-2016, 03:37 PM	#19
NoOne Hall Of Famer Join Date: Apr 2015 Posts: 7,167	back on topic: averages are a start... but distribution and volatility are required to give a real comparison... and definitely not based on small samples, like the ones above. batted ball stats are a %$#@. good luck with that stuff. one website i go to only has info for the last 10-12 years or so. then, you have the problem of conflicting definitions of what a line drive / fly ball is, etc... at this moment in time the data is a bit murky and difficult to use in a precise way. i.e. you can get 2 data sets from the same period of time in the MLB and get 2 completely different results. so, what kind of integrity is there at the moment? not much.

08-26-2016, 04:19 PM	#20
Barkingturtle Minors (Single A) Join Date: Jul 2013 Posts: 99	I just suffered through an August swoon wherein I lost three center-fielders and two of each right and left-fielders for the majority of the month. That's seven injured outfielders, all sitting in the jacuzzi at once. I lost sixteen games in a row, a new personal worst. I fell from contention like seven outfielders leaping from a plane without parachutes. I'm going to blame OOTP's injury engine combined with the data in this thread. It is some small consolation.