Motlhen Posted October 24, 2023 Share Posted October 24, 2023 This save I will play with all player & staff attributes hidden. Instead I will be using as many of the in-game statistics as I can to make squad-selection and transfer decisions. At first, the analysis won't be perfect, but that's part of what I think I'll enjoy - developing the best ways to find the right players. I'll try to build my own profile for each player to keep track of their development and the only time I will look at a players actual attributes will be when they leave the club. I've taken over Conwy Borough in the Welsh 2nd division North at the start of the 24/25 season after they were promoted from the unplayable leagues below. Without any other staff to make recommendations and no attributes, the squad (and one-man U18 squad) were hard to decipher. Squad U18 Squad Attribute-less Player Profile (just to show what it looks like) Stats With my contract starting the day before the 2nd game of pre-season, I downloaded the players stats from the previous season to gauge their performance and used the following to blunder together a tactic and a team selection: Players by Average Rating We had 20 players in our squad, with Toby Jones (7.29) the only real positive stand-out in terms of average rating. At the bottom of this list was Olly Walters (5.34), who the previous manager released after some abysmal performances. They also released Joseff Sharpe (6.4) who was the same age and plays in the same position as Kaminski-Kurlandt (5.76) which seems like a daft decision. That leaves 18 players in the squad for me to focus on. Let's look at goal-scoring next: Shots per 90mins (y-axis), Percentage of Shots on Target (x-axis) & Goals per 90mins (dot-size) Ray Knight (11) scored the most goals, had the best goals per 90 mins ratio (0.28) and had the best shots on target percentage (49%). Our wingers did not contribute very much to the goals - something I'll be hoping to change. Passes Attempted per 90mins (y-axis), Pass Completion Percentage (x-axis) & Assists per 90mins (dot-size) Centre-mid Ethan Hill (9) has the most assists, whilst centre-back Ant Marshall had the highest passes attempted per 90 mins (28.1) and highest pass completion rate (76%). The only player not to assist at least once was one of our strikers. The defending stats would take some more time to put together (there's some formatting issues). For now I looked at the best Headers & Tacklers in the team to help me choose my first XI. Next I'll be seeing how we perform in the friendlies and trying to find the best players to bring to the club using the data from divisions in Wales. 3 Link to post Share on other sites More sharing options...
Motlhen Posted October 24, 2023 Author Share Posted October 24, 2023 (edited) July 2024 Staff I've started my first coaching badge and signed the staff that held the highest qualifications. With the two scouts, I was pleased to get in Ribeiro for extra nations scouting knowledge as well as Doyle for his Welsh knowledge. Goalkeeping Decisions / Transfer Out Jones was last season's first choice keeper, but after an abysmal record of conceding 30 in 10 apps, I decided to gamble on Probert in the first games. Jones subsequently got upset and left. We do have a backup goalkeeper at the club, but he's primarily a striker, so we are definitely still in the market for someone new. Transfers In We've signed 7 players this month - not everyone was our first choice but I'm pretty happy with our acquisitions. First Choice Dave Forbes (21 goals) got the highest Goals per 90 mins ratio (0.64) in the country last season. Ryan Coney had the 2nd highest Pass Completion Ration (91%) in the country as well as decent Tackles per 90 mins (1.87) and Progressive Passes per 90 mins (4.1). Not quite first choice & then players like Danny Holland were found by looking at all non-strikers who's headers won per 90 > 1 and tackles won per 90 > 1 with a high pass completion rate (top 10) and goal scoring (top 10) to find a well-rounded midfielder. Fixtures Our first game was against rivals. ...and it couldn't have gone better! We followed it up by battling for a second win on the spin and we're off to a much better start than I anticipated. I'll see how we go with the current squad until the halfway point through the season and then reevaluate the current squad stats and look again towards the transfer market for improvements. Edited October 25, 2023 by Motlhen Link to post Share on other sites More sharing options...
Motlhen Posted October 25, 2023 Author Share Posted October 25, 2023 Fixtures We have been flying! Despite not yet keeping a clean sheet, we won 6 in a row before defeat to Guilsfield. Goals are coming from all over the park, which is a stark contrast to what the stats suggested from last season. Morgan scored the winning penalty on his debut! But Forbes is out for the next month or so. Looking at his stats, it is clear he'll be a huge miss for us. Awards I switched McCaffery to the left-sided inside forward role and he has been on fire! Link to post Share on other sites More sharing options...
Motlhen Posted October 25, 2023 Author Share Posted October 25, 2023 I thought I'd share the info I've managed to collect on each of my players now that I have some game stats and some second opinions from my staff: Goalkeeper As I mentioned before, picking Probert was a risk. We didn't know much about him apart from what were 3 sub appearances where he didn't concede for Goytre last season. But I chose to start him over recently-departed Aaron Jones' 10 starts with 30 conceded. We've not kept a clean sheet yet, but he's keeping things respectable. Our staff think he has decent handling, but at 34yo he is declining... ..and is rated only slightly higher than our backup goalie, who is primarily a striker! Player Profile: GK Probert (34yo, 184cm, right only) Pros: Handling, Determination Cons: Surplus, Training Rating, Declining Without a marked improvement, we'll definitely be in the market for a new goalkeeper in January. Link to post Share on other sites More sharing options...
Motlhen Posted October 26, 2023 Author Share Posted October 26, 2023 (edited) Digging a bit deeper into the goalkeeping stats for last season, I've found that whilst Jones' Conceded per 90 mins (3.00) was the worst in the whole of Wales, he actually had a positive xG prevented per 90 mins (0.33) which was the joint-10th highest. This points to our defensive frailty maybe not being down to the goalkeeper - maybe I should have done more to try to keep him around! I can hover over the dots to get players info, so using the same chart I looked at the dot highlighted below as it was the lowest Conceded per 90 (0.45) as well as having a positive xG prevented per 90 (0.26). Lee Idzi has been added to my goalkeeper shortlist! He's 36 and plays first team football for Haverfordwest in the Welsh Prem, so he may not be the best target - but this is a glimpse of how I want to use the data to find new players. --- Not our squad, but an interesting insight: --- The above chart limits the data to 'keepers who've played more than 95 minutes. When I looked at all goalkeepers I found a big outlier at the top of the graph: A young keeper playing for Tregaron has conceded 6.62 goals per 90 mins (albeit after playing only 68 minutes of football in total!) Taking a look at his profile, this wasn't just one poor performance against a good team, it appears that 16yo (at the time) Iestyn Llew Rees Greaves conceded a goal in all-but-one of his sub appearances last season. Unsurprisingly, as a result he also managed the lowest average rating (5.10) of all goalkeepers. Edited October 26, 2023 by Motlhen Link to post Share on other sites More sharing options...
Motlhen Posted October 26, 2023 Author Share Posted October 26, 2023 Cr*p! The more I look at the keeper stats, the worse my decision to let Jones go becomes. He was by far and away the safest pair of hands in Wales last season (Saves Held per 90: 2.5), combined with a high Saves% (72%). How he got an average rating of 5.93 for the season baffles me, but points to me using the stats over the ratings (average ratings or scout ratings). Link to post Share on other sites More sharing options...
Motlhen Posted October 26, 2023 Author Share Posted October 26, 2023 Scouting for a new GK I selected this group of keepers who had a low Conceded per 90 mins as well as a high xG Prevented per 90. And then whittled down my options further to high Saves% and high Saves Held per 90. The standout (in the top right corner) was Mansfield's Lewis Webb, he was on loan at Caernarfon Town last season and is out of reach for us unfortunately. I have made an approach for 3 of the 4 others and we'll wait and see if anyone agrees terms: Link to post Share on other sites More sharing options...
Motlhen Posted October 26, 2023 Author Share Posted October 26, 2023 Sep 2024 A month filled with cup games. We managed to get past non-league Bethesda and then Premier league Carmarthen in the Welsh Cup which is huge! But Bangor knocked us out of the only potentially winnable competition and Bala got a 90th and 94th minute double to turn around what would have been another Premier league scalp. New GK We didn't get our first or our second choice, but Williams is a huge improvement and starts from next month onwards. Link to post Share on other sites More sharing options...
DomD Posted October 26, 2023 Share Posted October 26, 2023 (edited) I like the premise of your save. What are using to make the graphs? Edited October 26, 2023 by DomD Link to post Share on other sites More sharing options...
Motlhen Posted October 27, 2023 Author Share Posted October 27, 2023 9 hours ago, DomD said: I like the premise of your save. What are using to make the graphs? Thanks! I put the data into GSheets and connected the sheet to Looker Studio (FKS Data Studio). Link to post Share on other sites More sharing options...
DomD Posted October 27, 2023 Share Posted October 27, 2023 Cool, I'll have to check that out. In your graphs it is obvious what the x and y axis represent, but what do the size of each bubble mean? Is that the number of minutes played? How do you export the data from FM? Link to post Share on other sites More sharing options...
Motlhen Posted October 27, 2023 Author Share Posted October 27, 2023 22 minutes ago, DomD said: Cool, I'll have to check that out. In your graphs it is obvious what the x and y axis represent, but what do the size of each bubble mean? Is that the number of minutes played? How do you export the data from FM? Thanks for pointing that out & yes you are correct! I'm going to edit my previous posts to state that. To export the data, I created the view I wanted in the scouting centre and then selected all (cmd+A) and then saved the data (cmd+P) and when prompted, saved the file as a web page. (Use ctrl instead of cmd for windows) Link to post Share on other sites More sharing options...
WhiteCat33 Posted October 27, 2023 Share Posted October 27, 2023 Great Visualizations!! I've always been a table-person, so designed mine that direction, but can see the appeal to your bubble plots. Your ability to whittle-down to select your new GK looks really functional. Looks promising that it resulted in an upgraded GK. I'll be following to get some Statistic Management fix while I continue my Youth Only save in Barbados. What is your strategy/philosophy on cross-league comparisons? Considering how common it is to find players from other UK leagues I could see that becoming relevant quickly. The most useful metrics I found in my Statistics Managing was finding conditional averages and then percentage ranking players inside those averages. Then I could see if my players were in the bottom/top 25% of statistics I cared about indicating if they were a major liability/asset. Link to post Share on other sites More sharing options...
Motlhen Posted October 27, 2023 Author Share Posted October 27, 2023 2 hours ago, WhiteCat33 said: Great Visualizations!! I've always been a table-person, so designed mine that direction, but can see the appeal to your bubble plots. Your ability to whittle-down to select your new GK looks really functional. Looks promising that it resulted in an upgraded GK. I'll be following to get some Statistic Management fix while I continue my Youth Only save in Barbados. Thanks! Your save in the MLS was one that really spurred my idea for this save. Actually, I am still reading through it slowly, so I am looking forward to finding out how successful you managed to become. 2 hours ago, WhiteCat33 said: What is your strategy/philosophy on cross-league comparisons? Considering how common it is to find players from other UK leagues I could see that becoming relevant quickly. The most useful metrics I found in my Statistics Managing was finding conditional averages and then percentage ranking players inside those averages. Then I could see if my players were in the bottom/top 25% of statistics I cared about indicating if they were a major liability/asset. I've started to think more about how to group players and what averages would be valuable to measure against. At the moment, my method is to group players into 3 groups: our own players, transfer targets (i.e. potential signings according to our scouts with interested in transfer or loan both set to 'doubtful') and then everyone else in Wales. This gives a good base, but I can already think of a few drawbacks of this method including: 1. Players in Wales will include players in unplayable leagues who's matches are run on the faster match engine and may not be representative of how they will behave/perform in the main ME. 2. The lower leagues will have lower performance and could be skewing the averages to lower than we need to compete at the level we're at. Eventually, what I would like to do is to keep both of the Conwy and the Scouting groups, but group the rest of the players into one average for Welsh Premier league players and one average for Welsh 2nd tier players etc so that the comparisons are more concise and direct. If I am managing in a more reputable league (rather than the lowest one in the game) then I might consider including other playable leagues within the comparison, but for now I think it is sufficient to concentrate on Wales. Do you have any tips? 1 Link to post Share on other sites More sharing options...
WhiteCat33 Posted October 28, 2023 Share Posted October 28, 2023 5 hours ago, Motlhen said: Thanks! Your save in the MLS was one that really spurred my idea for this save. Actually, I am still reading through it slowly, so I am looking forward to finding out how successful you managed to become. I'm glad my MLS adventure sparked your interest in designing your own Statistic Managment Tool! That save with the region-restriction to Caribbean truly made the MLS an engaging challenge. Not sure if you've made it to my Part II when I headed to Europe, but very quickly I realized that there weren't nearly enough Caribbean players that were affordable and had statistical performances I could evaluate to sign, so turned into hunting for Caribbean "wonderkids" rather than statistical anomalies. Not limiting what nationalities you draw from will help you significantly in the late game when you're building a European Competition squad. 5 hours ago, Motlhen said: This gives a good base, but I can already think of a few drawbacks of this method including: 1. Players in Wales will include players in unplayable leagues who's matches are run on the faster match engine and may not be representative of how they will behave/perform in the main ME. 2. The lower leagues will have lower performance and could be skewing the averages to lower than we need to compete at the level we're at. I use filters that selects the league that teams are in rather than the country to avoid that very problem. The way I designed my analysis was for horizontal slices across multiple leagues I considered 'at parity'. I never minded the simulated unloaded leagues to find players, as that is where I found some really gem Caribbeans. For you just selecting the tiers of the Welsh leagues you care about should be sufficient to hide the lower league players. 5 hours ago, Motlhen said: but for now I think it is sufficient to concentrate on Wales. Do you have any tips? I like scouting Northern Ireland. You get players for basically free, and I'd argue its a slightly stronger league than Wales so if they perform above average/best at the same tier as you in NI then Wales should be a strong move. I wish the game gave you youth player statistics, as picking up departing youngsters due to good youth team performance (rather than potential) would be a really neat way to play. 14 hours ago, Motlhen said: I've started to think more about how to group players and what averages would be valuable to measure against. At the moment, my method is to group players into 3 groups: our own players, transfer targets (i.e. potential signings according to our scouts with interested in transfer or loan both set to 'doubtful') and then everyone else in Wales. I like the group of the top 3 teams in the league to then create positional archetypes of what 'the best' of whatever role is doing in your league. The other groupings I did was 1000 Minutes, 7.00 Avg rating & Both combined. Even though I don't put much faith in average rating if you have a player who played 1000 minutes and stayed above a 7.00 they tend to be better than average for the league they were in. To do this correctly you need population data (Omniscient Holiday Man) rather than sample data (your scouting crew) as your primary data to build the averages. Then what I did was utilize a secondary dataset with what my scouts found to actually assess individual players' performances. Link to post Share on other sites More sharing options...
Motlhen Posted October 30, 2023 Author Share Posted October 30, 2023 On 28/10/2023 at 15:12, WhiteCat33 said: I'm glad my MLS adventure sparked your interest in designing your own Statistic Managment Tool! That save with the region-restriction to Caribbean truly made the MLS an engaging challenge. Not sure if you've made it to my Part II when I headed to Europe, but very quickly I realized that there weren't nearly enough Caribbean players that were affordable and had statistical performances I could evaluate to sign, so turned into hunting for Caribbean "wonderkids" rather than statistical anomalies. Not limiting what nationalities you draw from will help you significantly in the late game when you're building a European Competition squad. I haven't made it to the 2nd part yet but I am looking forward to it! I've just caught up to your Excel spreadsheet upgrades which I'm finding pretty useful to understand your thought process as I am also trying to go through the process of upgrading my visualisations. On 28/10/2023 at 15:12, WhiteCat33 said: I use filters that selects the league that teams are in rather than the country to avoid that very problem. The way I designed my analysis was for horizontal slices across multiple leagues I considered 'at parity'. I never minded the simulated unloaded leagues to find players, as that is where I found some really gem Caribbeans. For you just selecting the tiers of the Welsh leagues you care about should be sufficient to hide the lower league players. I like scouting Northern Ireland. You get players for basically free, and I'd argue its a slightly stronger league than Wales so if they perform above average/best at the same tier as you in NI then Wales should be a strong move. I wish the game gave you youth player statistics, as picking up departing youngsters due to good youth team performance (rather than potential) would be a really neat way to play. Northern Ireland's 3rd tier is a similar reputation league to the Welsh 2nd tier - maybe it would be good to extend my dataset to include these players too. Agreed, youth player stats would be a huge bonus to any FM player, but especially when playing a stats-based game. On 28/10/2023 at 15:12, WhiteCat33 said: I like the group of the top 3 teams in the league to then create positional archetypes of what 'the best' of whatever role is doing in your league. The other groupings I did was 1000 Minutes, 7.00 Avg rating & Both combined. Even though I don't put much faith in average rating if you have a player who played 1000 minutes and stayed above a 7.00 they tend to be better than average for the league they were in. To do this correctly you need population data (Omniscient Holiday Man) rather than sample data (your scouting crew) as your primary data to build the averages. Then what I did was utilize a secondary dataset with what my scouts found to actually assess individual players' performances. I think your method of including many leagues gives you the ability to make better groupings so I definitely will look into how much info I can get from other similarly-reputable leagues to flesh out the baseline stats. My next step was to take the noise from this graph where each dot represents a player (size of dot equivalent to Goals per 90 minutes): Instead of looking at individual players, grouping the player data by the tier they play in gives a clearer average for each level. Separating ourselves out of this average shows me maybe where we are lacking (shots on target% being closer to tier 3 shows bad finishing ability, despite our conversion rate being higher than tiers 1 & 2). Combining the two- I can see our strikers individually against the tier's averages. This shows me that Ray Knight is the striker closest to the tier 1 & 2 average, whilst Forbes has a poor conversion rate and Davies has a poor shot on target%. Right now we are only comparing to average. There's still value to each of these 3 charts, but I believe that extending the dataset to include data from other divisions would be the best way to start grouping players of high, medium and low performance. 1 Link to post Share on other sites More sharing options...
WhiteCat33 Posted October 30, 2023 Share Posted October 30, 2023 3 hours ago, Motlhen said: Right now we are only comparing to average. There's still value to each of these 3 charts, but I believe that extending the dataset to include data from other divisions would be the best way to start grouping players of high, medium and low performance. I like this last chart! Lets you very clearly see where your strikers stack up against the general striker from each Welsh league. If I was looking to use graphs like this to build scouting filters I'd make a grouping of the top 3 clubs in your division/tier. That way you have a benchmark for what a "promotion calibre" striker looks like in your league and the subjective standard for league success (promotion). I'm assuming you have these graphs for all the key attacking statistics, so combining them all you get the search parameters for scouting. I also notice you have the scouting data included as well, could you auto filter and isolate any players in your dataset that fulfill all/most of the statistics for this player? This automatic scout filtering was a secondary part I was starting to build in my tool before I moved back to a YAC save. Other direction (if I still remembered python) would be to generate a search filter with the statistical player stats to import into the game to search there. Link to post Share on other sites More sharing options...
Motlhen Posted October 30, 2023 Author Share Posted October 30, 2023 7 hours ago, WhiteCat33 said: I like this last chart! Lets you very clearly see where your strikers stack up against the general striker from each Welsh league. If I was looking to use graphs like this to build scouting filters I'd make a grouping of the top 3 clubs in your division/tier. That way you have a benchmark for what a "promotion calibre" striker looks like in your league and the subjective standard for league success (promotion). I'm assuming you have these graphs for all the key attacking statistics, so combining them all you get the search parameters for scouting. I also notice you have the scouting data included as well, could you auto filter and isolate any players in your dataset that fulfill all/most of the statistics for this player? This automatic scout filtering was a secondary part I was starting to build in my tool before I moved back to a YAC save. Other direction (if I still remembered python) would be to generate a search filter with the statistical player stats to import into the game to search there. Yep, that's the idea! I think it would be good to add an extra group of the top 3 as you suggested - I'll try and see if that promotion calibre is easy to create and add to the chart, thanks! & yes there are a few charts for each position now. I have the option to choose a position from a drop-down, as well as whether I want to include players natural in that position or not and from the below charts I think having the left chart for keeping tabs on my own players performance and the right chart for keeping tabs on potential transfer targets gives me a lot of what I need at the moment: Size of each dot represents the average number of minutes played (which I am thinking may not be the best thing for left chart; I'll have a think on that one) Each blue dot on the left represents a tier, split by whether the player was in our scouting suggestions, or in the rest of Wales. On the right, each dot is representative of each player within each group. Left What I can take from the above is that we have 3 clear under-performers in terms of Pass Completion%: Ryan Coney (83% most mins), Dan Evans (82%) & Toby Adams (81%). As a club, we are completing more passes per 90 than average as almost all of our players are to the right of the averages here. Right Josh Griffiths (PC%: 91%, PC/90: 54), Joe Palmer(PC%: 86%, PC/90: 54) & Kyle King (PC%: 90%, PC/90: 58)are the three bigger dots in the top right of the chart, who are performing better than our best pass completion% Ryan Vaughan I've sent our scouts out to find out more about these 3. 1 Link to post Share on other sites More sharing options...
Motlhen Posted November 1, 2023 Author Share Posted November 1, 2023 back to the save... Oct 2024 Our new GK had a rough start as we continued a poor run, but after tinkering with our tactics we got back to winning ways, including only our 2nd clean sheet of the season (the other was in a 0-0 draw). The win against C&C means we are through to the Quarter Final of the Welsh Cup. Looking at the draw, there was one team I wanted to avoid (TNS) and one team I really hoped we'd get - and we did! The prize money from the C&C win has really helped our finances stay positive, although I doubt they will stay that way for long. Link to post Share on other sites More sharing options...
Motlhen Posted November 1, 2023 Author Share Posted November 1, 2023 Nov 2024 We hit 4 wins on the spin before we lost out twice in two tight games. Jones had an incredible game against Flint! A late own goal against Holyhead really hurt as they are a team we should definitely be beating. The league is extremely tight with 3 points between 2nd and 8th. We're at the wrong end of the chasing pack at the moment. Link to post Share on other sites More sharing options...
Motlhen Posted November 1, 2023 Author Share Posted November 1, 2023 Dec 2024 We went into December in 7th chasing 2nd place (3 points off) and finished the year in the same position but now 9 points off of 2nd. After conceding so many goals, reverting to 5-at-the-back got us our 3rd clean sheet of the season and Bartlett managed to net his first goal of the season heading in from a corner. I've completed my first coaching badge & we have also seen the first youth intake preview: It's now time to review the stats for this season up until this point - I'm hoping to make some big signings in January which will help us get back on track. 1 Link to post Share on other sites More sharing options...
Junkhead Posted November 1, 2023 Share Posted November 1, 2023 Where did you find the attributeless skin? Had a look around and can't see one yet for FM24... Link to post Share on other sites More sharing options...
Motlhen Posted November 1, 2023 Author Share Posted November 1, 2023 3 minutes ago, Junkhead said: Where did you find the attributeless skin? Had a look around and can't see one yet for FM24... Hi mate- it's not a skin, you can hide attributes by going to Preferences -> Custom Skin Colour -> Skin Colours and then change the numbers in the column with the header 'A' all to zero, as shown here: Link to post Share on other sites More sharing options...
Junkhead Posted November 1, 2023 Share Posted November 1, 2023 Thanks - appreciate it! 1 Link to post Share on other sites More sharing options...
underbala Posted November 1, 2023 Share Posted November 1, 2023 HI Like your save! i have same plan for playing, but i don't know which key stats are important for each position. Any guide or sites give me some info? For example, CB's: Tackling/90, Heading won/90 etc Link to post Share on other sites More sharing options...
Motlhen Posted November 1, 2023 Author Share Posted November 1, 2023 Goalkeeper We made a goalkeeping improvement already this season. Has Williams been any better than Probert? On the surface it doesn't look like we have: Probert Games: 13 Conceded: 23 Clean Sheets: 1 vs. Williams Games: 12 Conceded: 24 Clean Sheets: 2 Looking deeper, I think Williams has been a big improvement, but the stats above showcase our decline overall defensively: x-axis: xG prevented per 90 minutes y-axis: Goals conceded per 90 minutes size: Average number of minutes played Comparing our two goalkeepers, we can see that whilst Williams has conceded more per 90, he has prevented a considerable amount more than Probert did in a similar number of games. Blue-dot: The average of the top 3 teams from the Welsh Level 2 from the 23/24 season and the current 24/25 season. The idea here, as suggested by @WhiteCat33, is we are comparing performance to promotion candidates - as that is where we want to aim to be! Talking in terms of xG Prevented per 90, Probert is a long way off the ideal, whilst Williams is much closer to the performance of 'keepers in the teams challenging at the top of our league. This chart below is the same as above, but instead of looking at the average, we are looking at each individual player within the promotion challenging teams. Knowing that there are only 3 'keepers that have played more minutes than Williams that have prevented more xG per 90 gives me confidence in our signing. Breaking out the data in the same way, but concentrating on a couple of different GK stats: Williams has a much higher Saves%. Probert has a higher Saves Held% (but I'm favouring a save being made, over the ball being held). Williams has a lower expected save % (xSv%), and actually has the 2nd lowest of all of the 'keepers which shows our goal is under threat from chances the opposition would be more likely to score from. Despite this, he's getting the higher average rating - probably as he has a higher xG prevented from the shots he's faced than Probert does. That was a lot of info to go through to say that I'm happy with my new goalkeeper signing & think that the defence is where we may need some improvements. 1 Link to post Share on other sites More sharing options...
Motlhen Posted November 1, 2023 Author Share Posted November 1, 2023 19 minutes ago, underbala said: HI Like your save! i have same plan for playing, but i don't know which key stats are important for each position. Any guide or sites give me some info? For example, CB's: Tackling/90, Heading won/90 etc Hi mate, thanks! I don't know about any guides or sites, but I know how to find the list of available stats: Go to Scouting -> Players and then click on the drop-down -> Custom -> Customise Current View... This will bring up another window, with another drop-down. I looked at everything under Stats (Chalkboard) - and it is here you can start to decide which stats are best for each position. Good luck! Link to post Share on other sites More sharing options...
WhiteCat33 Posted November 1, 2023 Share Posted November 1, 2023 17 minutes ago, Motlhen said: Goalkeeper We made a goalkeeping improvement already this season. Has Williams been any better than Probert? On the surface it doesn't look like we have: Probert Games: 13 Conceded: 23 Clean Sheets: 1 vs. Williams Games: 12 Conceded: 24 Clean Sheets: 2 Looking deeper, I think Williams has been a big improvement, but the stats above showcase our decline overall defensively: x-axis: xG prevented per 90 minutes y-axis: Goals conceded per 90 minutes size: Average number of minutes played Comparing our two goalkeepers, we can see that whilst Williams has conceded more per 90, he has prevented a considerable amount more than Probert did in a similar number of games. Blue-dot: The average of the top 3 teams from the Welsh Level 2 from the 23/24 season and the current 24/25 season. The idea here, as suggested by @WhiteCat33, is we are comparing performance to promotion candidates - as that is where we want to aim to be! Talking in terms of xG Prevented per 90, Probert is a long way off the ideal, whilst Williams is much closer to the performance of 'keepers in the teams challenging at the top of our league. This chart below is the same as above, but instead of looking at the average, we are looking at each individual player within the promotion challenging teams. Knowing that there are only 3 'keepers that have played more minutes than Williams that have prevented more xG per 90 gives me confidence in our signing. Breaking out the data in the same way, but concentrating on a couple of different GK stats: Williams has a much higher Saves%. Probert has a higher Saves Held% (but I'm favouring a save being made, over the ball being held). Williams has a lower expected save % (xSv%), and actually has the 2nd lowest of all of the 'keepers which shows our goal is under threat from chances the opposition would be more likely to score from. Despite this, he's getting the higher average rating - probably as he has a higher xG prevented from the shots he's faced than Probert does. That was a lot of info to go through to say that I'm happy with my new goalkeeper signing & think that the defence is where we may need some improvements. GK is looking so much better! The xG Prevented/90 with save% were what I relied on the most in my save. Burki at St Louis was an absolute monster on those and was crucial to our MLS domination. Now you need to take a look at those CBs to see how they are putting your GK in the position to need to make all those saves! In FM23 the game broke out total Saves then individually: Held, Parried & Tipped as 4 discrete variables. That way you can get comparative stats to savesheld% for savesparied% & savestipped% on your own. I also liked to look at mistakes & mistakes leading to goals to evaluate GK reliability. Link to post Share on other sites More sharing options...
Motlhen Posted November 1, 2023 Author Share Posted November 1, 2023 13 minutes ago, WhiteCat33 said: GK is looking so much better! The xG Prevented/90 with save% were what I relied on the most in my save. Burki at St Louis was an absolute monster on those and was crucial to our MLS domination. Now you need to take a look at those CBs to see how they are putting your GK in the position to need to make all those saves! In FM23 the game broke out total Saves then individually: Held, Parried & Tipped as 4 discrete variables. That way you can get comparative stats to savesheld% for savesparied% & savestipped% on your own. I also liked to look at mistakes & mistakes leading to goals to evaluate GK reliability. Awesome, thanks! I'll add in those suggestions for the end of season review, although it doesn't seem like Mistakes is available? (Mistakes leading to a goal is though) I had noticed that there were stats for each of held, parried & tipped. I've added those together to calculate the number of saves in total - and then from that I have calculated the Saves% stat. I guess I am not too bothered about parried and tipped individually as they are incorporated into the Saves% stat and then I'm comparing that with the saves held% as I see that as an indicator for good handling. 1 Link to post Share on other sites More sharing options...
Motlhen Posted November 1, 2023 Author Share Posted November 1, 2023 (edited) Central Defenders We signed Glossop at the start of the season, so I want to check in on his progress as well as his centre-back partner Marshall. Over the past few games I have been using our other centre-backs more often to try to gauge their performance and whether they could be swapped in to the starting XI. (Remember we are comparing our defenders to the defenders in the teams pushing for promotion (top 3), the left chart is their average, the right chart is their individuals) Tackling Marshall is much better than the average we are trying to hit. Whelan has also impressed. Glossop has made more tackles - the most actually - but he is slightly less likely to win them. Morgan's tackling has been woeful. If I change my filters to look at all players (not just those from the top 3 teams) and then add in some new filters for Tacklers equal to or better than the promotional average (i.e. Tackles Won% > 80%, Tackles Won per 90 > 1.2 & playing at our level or above) I can start to see some potential candidates to scout (dark blue). This also highlights just how well Marshall has been doing in the Tackling department. Heading Now this first graph is a bit messy, but it highlights a big insight. Glossop's (lack of) heading ability. 35% of Headers Won is extraordinarily low for a centre-back. His number of Headers Won per 90 is also adrift from the rest of the players in our tier, team and the tier above - with his performance in this stat more in line with the Welsh 3rd or 4th tier. Reducing the comparisons to only comparing against the promotion-sides average (I really need a good name for this, any suggestions!?) we can see that Whelan is the only one to meet & surpass what we're hoping for. Marshall (& the 2 others) are not far behind in this department, but we can still see that Glossop is miles away. From Heading & Tackling it's pretty clear that Whelan may be a better choice as a centre-back over Glossop. Changing my filters to look at potential signings (Headers Won per 90 > 4.5, Headers Won% > 68% & playing at our level or above) we get another list of players to scout. Now to see if any of the players within my scouting range fit both criteria? And yep, we have 6 on the list that standout above the thresholds (represented by the dashed lines) we want to hit for both Heading & Tackling: Morgan Pugh-Bevan Craig Rogers Callum Humphries Aaron Hughes Tom Rawlinson Iddon Price I'm not done there with defensive stats though: Key Tackles & Blocks Marshall again showing he is important for us with high Key Tackles per 90. Millar's first positive against his name is a high ratio of blocks. What about the transfer targets we identified? (The light blue in this graph will be the players' performance from last season, whereas the dark blue is this season's performances.) Hughes, Price, Pugh-Bevan & Rogers impressive here. Clearances & Interceptions Morgan is very good at both of these, especially clearances. Glossop is one of the best at Interceptions, too. Whelan is the only one that is slightly below par in these stats. Transfer Targets: Everyone is above both thresholds here. Passing Both Marshall & Glossop show they are reliable ball playing defenders. Whelan showing that maybe he's more of a no-nonsense centre back. Transfer Targets: Rawlinson & Price are the best two passers out of our list of targets. And I think that means Iddon Price is our main target as he is the only one that met every threshold. Let's hope I can get him to sign! If I can, I think he will be paired with Marshall at centre-back - with Whelan our main backup/rotation option. Glossop will be moved into midfield (potentially as a BWM) as he has great tackling & interceptions, but his heading let him down. That was a lot charts, I am sorry. Edited November 2, 2023 by Motlhen 1 Link to post Share on other sites More sharing options...
Motlhen Posted November 2, 2023 Author Share Posted November 2, 2023 We got our man! Although, he is 33 and only rated 2* by our staff. Here's his stats for the past 2 seasons & combined: Compared with centre-backs from the top 3 promotion candidates: If he keeps up his performances this season in a Conwy shirt, I'll be very happy! Link to post Share on other sites More sharing options...
Motlhen Posted November 3, 2023 Author Share Posted November 3, 2023 After repeating a similar process for other positions, I found new targets for LWB, AML, MC & ST but only two of them came off: Striker Bishop will play as our target forward in place of Forbes who has not been consistent enough. The reason I signed Bishop was because he has been a much more clinical striker than Knight. I am hoping for a lot more goals playing him alongside Knight in the more physically demanding role. With two decent strikers up top - it was time to find someone who could provide for them. We have Jones on the right flank with a few backup options, but we had no natural AML so I went on the search and immediately find a suitable candidate. He has created the most Clear Cut Chances and played the most Key passes in the league so far. & from these passes, he's hit a high assists per 90. The midfield and left back targets would not agree to suitable personal terms and/or moved to other clubs. I'm happy with the 3 signings we've made, but knowing it could have been more, I just hope we have improved enough to string together a good run of results. 1 Link to post Share on other sites More sharing options...
Motlhen Posted November 3, 2023 Author Share Posted November 3, 2023 Transfer Out Our first transfer out (of a player I've been using) means we are ready for our first attribute reveal. Morgan only started 3 of the 16 apps for us and from the stats he was only above threshold for both clearances and interceptions which made me think of him as a no-nonsense defender, which I wasn't a fan of using. Although he was young, I doubt he'll improve enough to get to the level we need him at so I didn't fight against the transfer. Will I be kicking myself for letting him go? Spoiler No, I won't. As expected I guess - a technically poor defender. Link to post Share on other sites More sharing options...
Motlhen Posted November 3, 2023 Author Share Posted November 3, 2023 Jan 2025 With the new signings being gelled in to the system and adjustments being made to the tactics to suit them, I'm very happy we've not lost! Link to post Share on other sites More sharing options...
Motlhen Posted November 3, 2023 Author Share Posted November 3, 2023 Feb 2025 After the transfer window, this is how we're lining up: (Luckily, we managed to keep Marshall with a new contract) Apart from for our Welsh Cup Quarter Final match where (devastatingly) our 3 signings are all cup-tied. Fixtures We've remained unbeaten, with 3 big wins on the spin! Two clean sheets in a row after only managing 3 in total previously this season is a great sign too. Iddon Price has contributed at both ends with 3 goals in his first 3 games!!! Bishop is also off the mark! & we're through to the Welsh Cup semis after an emphatic win against Berriew, although we did concede two late goals at 4-0 up. But we've drawn the holders & Welsh Champions. We have nothing to lose in this game - but I'm not expecting to get to the final now. Awards This is a huge sign of how well our defence has played and the improvements we've made paying off! Link to post Share on other sites More sharing options...
Motlhen Posted November 3, 2023 Author Share Posted November 3, 2023 Mar 2025 Bad news. Jones has been our best players this season and losing him for 2 months, including for the Semi-Final against TNS, is a big loss. Good news. The board are happy to upgrade & extend my contract. ...at the end of the month we have the TNS game and with the 3 new signings being cup-tied I've chosen to risk playing both Jones & Forbes despite them both still recovering from injury. I want to give us the best chance. A smash & grab here would mean we are one game away from Europe, which is incredible to think about. TNS showed us their quality. It could've and maybe should've been more than 3. In the league we are still unbeaten this year - and added a couple more clean sheets! We've crept up to 6th with 2 games to go. Link to post Share on other sites More sharing options...
Motlhen Posted November 3, 2023 Author Share Posted November 3, 2023 Apr 2025 Youth Intake Day This is a lot harder to judge (without attributes) than usual. Am I going to have to start some of the top-rated prospects to see how they get on, or will I have to pay more attention to my U19s next season? Fixtures We finished the season with two busy games. Happy to finish 5th and without losing so far in 2025. Hopefully we can keep that up into next season! Link to post Share on other sites More sharing options...
Motlhen Posted November 3, 2023 Author Share Posted November 3, 2023 (edited) Departures We have had a number of departures (which means some more attribute unveiling) some I am okay with and some I was really not expecting. The biggest departure was Iddon Price retiring without prior announcement and no chance to try and talk him out of it. After signing in January, he played 11 games, got 4 goals and a 7.11 average rating in his short stint with us and was integral to our change in fortunes. So what did Price's attributes look like? Spoiler Actually, I am pretty underwhelmed by his stats. This is a perfect example of a player I wouldn't look twice at in terms of attributes, playing way above my expected ability and helping us massively. He will be missed. The other retiree was Paddock. He was part of the squad last season but his stats didn't make him appealing enough to feature in my squad. Spoiler Pretty poor as expected. There have been 3 transfers out too. I'm gutted to be losing RWB Roberts who featured in two full seasons for us (despite what the text in the image below might say.) I know he won a majority of headers and was decent at passing & tackling too. Do his attributes match up? Spoiler No! I'm amazed (in a bad way) by those technical stats. He is a decent athlete for our level but his heading of 2 is very surprising. Roberts is the furthest-right of the orange dots. He Won 7.83 Headers per 90 and 65% of his Headed battles which is one of the best across all defenders (DR, DL or DC) in the whole of the 2nd tier. I guess this means his ability to get to the ball first (jumping reach of 14) means he's winning more headers than most, despite his poor ability when it comes to applying a direction to the headers he wins. Roberts is the bottom dot in the line of 3 orange dots in the top right. His passing on the other hand is baffling. 1 at passing I assume would mean a well-below-par set of stats for passing, but he's 3rd-best of all of our defenders here with 46.2 Passes Completed per 90 and 85.9% Pass Completion. Another disappointing loss was our young, backup striker Davies. A decent backup option, but he didn't do enough to excite me too much for the future - I'm not expecting to miss him. Spoiler As I would have expected I guess. Decent, but nothing spectacular. The final departure was Kaminski-Kurlandt who played terribly last season and remained out of the first team squad. Spoiler Well... Considering Roberts' performances for us, maybe a giant jumping reach of 16 could have served us well!? Beyond that, I'm not surprised he is not very good at all. Edited November 3, 2023 by Motlhen Link to post Share on other sites More sharing options...
underbala Posted November 5, 2023 Share Posted November 5, 2023 hi do you use excel/google spreadsheet? Link to post Share on other sites More sharing options...
Motlhen Posted November 6, 2023 Author Share Posted November 6, 2023 14 hours ago, underbala said: hi do you use excel/google spreadsheet? I use Google Sheets for the data, yep Link to post Share on other sites More sharing options...
Motlhen Posted November 19, 2023 Author Share Posted November 19, 2023 (edited) I have been continuing this save and idea, but without updating here for a while... (I lost a bunch of screenshots and didn't put the effort in to go back through and get them all again) We continued our great end of season form into the new campaign and ended up storming the league, only losing twice. We lost in the Welsh Cup immediately But had a couple of good runs in the other 2 cups Including a disappointing Final loss against Llanwit Major to deny us a double. After promotion and losing in the final, I resigned from Conwy and moved clubs: The club were newly promoted and favourites to go back down. We started terribly with 5 losses on the spin and only started picking up a few wins with a change in tactic. The transfer window didn't open until November, but when it did we had a complete switch in fortunes Which just about helped us stay in the league It's the start of my 2nd season with SP and 4th overall and I'm hoping our singings will help us avoid a relegation battle this season. Edited November 19, 2023 by Motlhen Link to post Share on other sites More sharing options...
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